feat(matrix-ui): add Fund Session modal with explanatory text about sats

- Add Fund Session button to Matrix UI overlay (green plus icon)
- Create modal with three explanatory sections:
  * What are Sats? - explains satoshis as smallest Bitcoin unit
  * Why Fund Your Session? - explains how sats power Workshop AI agents
  * Approximate Costs - shows cost ranges for different interaction types
- Add input field for funding amount (min 100 sats)
- Style modal with green theme to match Lightning/sats concept
- Add proper keyboard support (Enter to submit, Escape to close)
- Mobile-responsive design

Fixes #753

.gitignore

@@ -21,6 +21,9 @@ discord_credentials.txt
 
 # Backup / temp files
 *~
+\#*\#
+*.backup
+*.tar.gz
 
 # SQLite — never commit databases or WAL/SHM artifacts
 *.db
@@ -70,9 +73,25 @@ morning_briefing.txt
 markdown_report.md
 data/timmy_soul.jsonl
 scripts/migrate_to_zeroclaw.py
-src/infrastructure/db_pool.py
 workspace/
 
+# Loop orchestration state
+.loop/
+
+# Legacy junk from old Timmy sessions (one-word fragments, cruft)
+Hi
+Im Timmy*
+his
+keep
+clean
+directory
+my_name_is_timmy*
+timmy_read_me_*
+issue_12_proposal.md
+
+# Memory notes (session-scoped, not committed)
+memory/notes/
+
 # Gitea Actions runner state
 .runner
 

config/matrix.yaml

@@ -0,0 +1,33 @@
+# Matrix World Configuration
+# Serves lighting, environment, and feature settings to the Matrix frontend.
+
+lighting:
+  ambient_color: "#FFAA55"  # Warm amber (Workshop warmth)
+  ambient_intensity: 0.5
+  point_lights:
+    - color: "#FFAA55"      # Warm amber (Workshop center light)
+      intensity: 1.2
+      position: { x: 0, y: 5, z: 0 }
+    - color: "#3B82F6"      # Cool blue (Matrix accent)
+      intensity: 0.8
+      position: { x: -5, y: 3, z: -5 }
+    - color: "#A855F7"      # Purple accent
+      intensity: 0.6
+      position: { x: 5, y: 3, z: 5 }
+
+environment:
+  rain_enabled: false
+  starfield_enabled: true     # Cool blue starfield (Matrix feel)
+  fog_color: "#0f0f23"
+  fog_density: 0.02
+
+features:
+  chat_enabled: true
+  visitor_avatars: true
+  pip_familiar: true
+  workshop_portal: true
+
+agents:
+  default_count: 5
+  max_count: 20
+  agents: []

config/providers.yaml

@@ -54,19 +54,6 @@ providers:
         context_window: 2048
         capabilities: [text, vision, streaming]
     
-  # Secondary: Local AirLLM (if installed)
-  - name: airllm-local
-    type: airllm
-    enabled: false  # Enable if pip install airllm
-    priority: 2
-    models:
-      - name: 70b
-        default: true
-        capabilities: [text, tools, json, streaming]
-      - name: 8b
-        capabilities: [text, tools, json, streaming]
-      - name: 405b
-        capabilities: [text, tools, json, streaming]
     
   # Tertiary: OpenAI (if API key available)
   - name: openai-backup

config/quests.yaml

@@ -0,0 +1,178 @@
+# ── Token Quest System Configuration ─────────────────────────────────────────
+#
+# Quests are special objectives that agents (and humans) can complete for
+# bonus tokens. Each quest has:
+#   - id: Unique identifier
+#   - name: Display name
+#   - description: What the quest requires
+#   - reward_tokens: Number of tokens awarded on completion
+#   - criteria: Detection rules for completion
+#   - enabled: Whether this quest is active
+#   - repeatable: Whether this quest can be completed multiple times
+#   - cooldown_hours: Minimum hours between completions (if repeatable)
+#
+# Quest Types:
+#   - issue_count: Complete when N issues matching criteria are closed
+#   - issue_reduce: Complete when open issue count drops by N
+#   - docs_update: Complete when documentation files are updated
+#   - test_improve: Complete when test coverage/cases improve
+#   - daily_run: Complete Daily Run session objectives
+#   - custom: Special quests with manual completion
+#
+# ── Active Quests ─────────────────────────────────────────────────────────────
+
+quests:
+  # ── Daily Run & Test Improvement Quests ───────────────────────────────────
+  
+  close_flaky_tests:
+    id: close_flaky_tests
+    name: Flaky Test Hunter
+    description: Close 3 issues labeled "flaky-test"
+    reward_tokens: 150
+    type: issue_count
+    enabled: true
+    repeatable: true
+    cooldown_hours: 24
+    criteria:
+      issue_labels:
+        - flaky-test
+      target_count: 3
+      issue_state: closed
+      lookback_days: 7
+    notification_message: "Quest Complete! You closed 3 flaky-test issues and earned {tokens} tokens."
+
+  reduce_p1_issues:
+    id: reduce_p1_issues
+    name: Priority Firefighter
+    description: Reduce open P1 Daily Run issues by 2
+    reward_tokens: 200
+    type: issue_reduce
+    enabled: true
+    repeatable: true
+    cooldown_hours: 48
+    criteria:
+      issue_labels:
+        - layer:triage
+        - P1
+      target_reduction: 2
+      lookback_days: 3
+    notification_message: "Quest Complete! You reduced P1 issues by 2 and earned {tokens} tokens."
+
+  improve_test_coverage:
+    id: improve_test_coverage
+    name: Coverage Champion
+    description: Improve test coverage by 5% or add 10 new test cases
+    reward_tokens: 300
+    type: test_improve
+    enabled: true
+    repeatable: false
+    criteria:
+      coverage_increase_percent: 5
+      min_new_tests: 10
+    notification_message: "Quest Complete! You improved test coverage and earned {tokens} tokens."
+
+  complete_daily_run_session:
+    id: complete_daily_run_session
+    name: Daily Runner
+    description: Successfully complete 5 Daily Run sessions in a week
+    reward_tokens: 250
+    type: daily_run
+    enabled: true
+    repeatable: true
+    cooldown_hours: 168  # 1 week
+    criteria:
+      min_sessions: 5
+      lookback_days: 7
+    notification_message: "Quest Complete! You completed 5 Daily Run sessions and earned {tokens} tokens."
+
+  # ── Documentation & Maintenance Quests ────────────────────────────────────
+
+  improve_automation_docs:
+    id: improve_automation_docs
+    name: Documentation Hero
+    description: Improve documentation for automations (update 3+ doc files)
+    reward_tokens: 100
+    type: docs_update
+    enabled: true
+    repeatable: true
+    cooldown_hours: 72
+    criteria:
+      file_patterns:
+        - "docs/**/*.md"
+        - "**/README.md"
+        - "timmy_automations/**/*.md"
+      min_files_changed: 3
+      lookback_days: 7
+    notification_message: "Quest Complete! You improved automation docs and earned {tokens} tokens."
+
+  close_micro_fixes:
+    id: close_micro_fixes
+    name: Micro Fix Master
+    description: Close 5 issues labeled "layer:micro-fix"
+    reward_tokens: 125
+    type: issue_count
+    enabled: true
+    repeatable: true
+    cooldown_hours: 24
+    criteria:
+      issue_labels:
+        - layer:micro-fix
+      target_count: 5
+      issue_state: closed
+      lookback_days: 7
+    notification_message: "Quest Complete! You closed 5 micro-fix issues and earned {tokens} tokens."
+
+  # ── Special Achievements ──────────────────────────────────────────────────
+
+  first_contribution:
+    id: first_contribution
+    name: First Steps
+    description: Make your first contribution (close any issue)
+    reward_tokens: 50
+    type: issue_count
+    enabled: true
+    repeatable: false
+    criteria:
+      target_count: 1
+      issue_state: closed
+      lookback_days: 30
+    notification_message: "Welcome! You completed your first contribution and earned {tokens} tokens."
+
+  bug_squasher:
+    id: bug_squasher
+    name: Bug Squasher
+    description: Close 10 issues labeled "bug"
+    reward_tokens: 500
+    type: issue_count
+    enabled: true
+    repeatable: true
+    cooldown_hours: 168  # 1 week
+    criteria:
+      issue_labels:
+        - bug
+      target_count: 10
+      issue_state: closed
+      lookback_days: 7
+    notification_message: "Quest Complete! You squashed 10 bugs and earned {tokens} tokens."
+
+# ── Quest System Settings ───────────────────────────────────────────────────
+
+settings:
+  # Enable/disable quest notifications
+  notifications_enabled: true
+  
+  # Maximum number of concurrent active quests per agent
+  max_concurrent_quests: 5
+  
+  # Auto-detect quest completions on Daily Run metrics update
+  auto_detect_on_daily_run: true
+  
+  # Gitea issue labels that indicate quest-related work
+  quest_work_labels:
+    - layer:triage
+    - layer:micro-fix
+    - layer:tests
+    - layer:economy
+    - flaky-test
+    - bug
+    - documentation

docs/adr/023-workshop-presence-schema.md

@@ -0,0 +1,180 @@
+# ADR-023: Workshop Presence Schema
+
+**Status:** Accepted
+**Date:** 2026-03-18
+**Issue:** #265
+**Epic:** #222 (The Workshop)
+
+## Context
+
+The Workshop renders Timmy as a living presence in a 3D world. It needs to
+know what Timmy is doing *right now* — his working memory, not his full
+identity or history. This schema defines the contract between Timmy (writer)
+and the Workshop (reader).
+
+### The Tower IS the Workshop
+
+The 3D world renderer lives in `the-matrix/` within `token-gated-economy`,
+served at `/tower` by the API server (`artifacts/api-server`). This is the
+canonical Workshop scene — not a generic Matrix visualization. All Workshop
+phase issues (#361, #362, #363) target that codebase. No separate
+`alexanderwhitestone.com` scaffold is needed until production deploy.
+
+The `workshop-state` spec (#360) is consumed by the API server via a
+file-watch mechanism, bridging Timmy's presence into the 3D scene.
+
+Design principles:
+- **Working memory, not long-term memory.** Present tense only.
+- **Written as side effect of work.** Not a separate obligation.
+- **Liveness is mandatory.** Stale = "not home," shown honestly.
+- **Schema is the contract.** Keep it minimal and stable.
+
+## Decision
+
+### File Location
+
+`~/.timmy/presence.json`
+
+JSON chosen over YAML for predictable parsing by both Python and JavaScript
+(the Workshop frontend). The Workshop reads this file via the WebSocket
+bridge (#243) or polls it directly during development.
+
+### Schema (v1)
+
+```json
+{
+  "$schema": "https://json-schema.org/draft/2020-12/schema",
+  "title": "Timmy Presence State",
+  "description": "Working memory surface for the Workshop renderer",
+  "type": "object",
+  "required": ["version", "liveness", "current_focus"],
+  "properties": {
+    "version": {
+      "type": "integer",
+      "const": 1,
+      "description": "Schema version for forward compatibility"
+    },
+    "liveness": {
+      "type": "string",
+      "format": "date-time",
+      "description": "ISO 8601 timestamp of last update. If stale (>5min), Timmy is not home."
+    },
+    "current_focus": {
+      "type": "string",
+      "description": "One sentence: what Timmy is doing right now. Empty string = idle."
+    },
+    "active_threads": {
+      "type": "array",
+      "maxItems": 10,
+      "description": "Current work items Timmy is tracking",
+      "items": {
+        "type": "object",
+        "required": ["type", "ref", "status"],
+        "properties": {
+          "type": {
+            "type": "string",
+            "enum": ["pr_review", "issue", "conversation", "research", "thinking"]
+          },
+          "ref": {
+            "type": "string",
+            "description": "Reference identifier (issue #, PR #, topic name)"
+          },
+          "status": {
+            "type": "string",
+            "enum": ["active", "idle", "blocked", "completed"]
+          }
+        }
+      }
+    },
+    "recent_events": {
+      "type": "array",
+      "maxItems": 20,
+      "description": "Recent events, newest first. Capped at 20.",
+      "items": {
+        "type": "object",
+        "required": ["timestamp", "event"],
+        "properties": {
+          "timestamp": {
+            "type": "string",
+            "format": "date-time"
+          },
+          "event": {
+            "type": "string",
+            "description": "Brief description of what happened"
+          }
+        }
+      }
+    },
+    "concerns": {
+      "type": "array",
+      "maxItems": 5,
+      "description": "Things Timmy is uncertain or worried about. Flat list, no severity.",
+      "items": {
+        "type": "string"
+      }
+    },
+    "mood": {
+      "type": "string",
+      "enum": ["focused", "exploring", "uncertain", "excited", "tired", "idle"],
+      "description": "Emotional texture for the Workshop to render. Optional."
+    }
+  }
+}
+```
+
+### Example
+
+```json
+{
+  "version": 1,
+  "liveness": "2026-03-18T21:47:12Z",
+  "current_focus": "Reviewing PR #267 — stream adapter for Gitea webhooks",
+  "active_threads": [
+    {"type": "pr_review", "ref": "#267", "status": "active"},
+    {"type": "issue", "ref": "#239", "status": "idle"},
+    {"type": "conversation", "ref": "hermes-consultation", "status": "idle"}
+  ],
+  "recent_events": [
+    {"timestamp": "2026-03-18T21:45:00Z", "event": "Completed PR review for #265"},
+    {"timestamp": "2026-03-18T21:30:00Z", "event": "Filed issue #268 — flaky test in sensory loop"}
+  ],
+  "concerns": [
+    "WebSocket reconnection logic feels brittle",
+    "Not sure the barks system handles uncertainty well yet"
+  ],
+  "mood": "focused"
+}
+```
+
+### Design Answers
+
+| Question | Answer |
+|---|---|
+| File format | JSON (predictable for JS + Python, no YAML parser needed in browser) |
+| recent_events cap | 20 entries max, oldest dropped |
+| concerns severity | Flat list, no priority. Keep it simple. |
+| File location | `~/.timmy/presence.json` — accessible to Workshop via bridge |
+| Staleness threshold | 5 minutes without liveness update = "not home" |
+| mood field | Optional. Workshop can render visual cues (color, animation) |
+
+## Consequences
+
+- **Timmy's agent loop** must write `~/.timmy/presence.json` as a side effect
+  of work. This is a hook at the end of each cycle, not a daemon.
+- **The Workshop frontend** reads this file and renders accordingly. Stale
+  liveness → dim the wizard, show "away" state.
+- **The WebSocket bridge** (#243) watches this file and pushes changes to
+  connected Workshop clients.
+- **Schema is versioned.** Breaking changes increment the version field.
+  Workshop must handle unknown versions gracefully (show raw data or "unknown state").
+
+## Related
+
+- #222 — Workshop epic
+- #243 — WebSocket bridge (transports this state)
+- #239 — Sensory loop (feeds into state)
+- #242 — 3D world (consumes this state for rendering)
+- #246 — Confidence as visible trait (mood field serves this)
+- #360 — Workshop-state spec (consumed by API via file-watch)
+- #361, #362, #363 — Workshop phase issues (target `the-matrix/`)
+- #372 — The Tower IS the Workshop (canonical connection)

docs/research/openclaw-architecture-deployment-guide.md

@@ -0,0 +1,912 @@
+# OpenClaw Architecture, Deployment Modes, and Ollama Integration
+
+## Research Report for Timmy Time Dashboard Project
+
+**Issue:** #721 — [Kimi Research] OpenClaw architecture, deployment modes, and Ollama integration  
+**Date:** 2026-03-21  
+**Author:** Kimi (Moonshot AI)  
+**Status:** Complete
+
+---
+
+## Executive Summary
+
+OpenClaw is an open-source AI agent framework that bridges messaging platforms (WhatsApp, Telegram, Slack, Discord, iMessage) to AI coding agents through a centralized gateway. Originally known as Clawdbot and Moltbot, it was rebranded to OpenClaw in early 2026. This report provides a comprehensive analysis of OpenClaw's architecture, deployment options, Ollama integration capabilities, and suitability for deployment on resource-constrained VPS environments like the Hermes DigitalOcean droplet (2GB RAM / 1 vCPU).
+
+**Key Finding:** Running OpenClaw with local LLMs on a 2GB RAM VPS is **not recommended**. The absolute minimum for a text-only agent with external API models is 4GB RAM. For local model inference via Ollama, 8-16GB RAM is the practical minimum. A hybrid approach using OpenRouter as the primary provider with Ollama as fallback is the most viable configuration for small VPS deployments.
+
+---
+
+## 1. Architecture Overview
+
+### 1.1 Core Components
+
+OpenClaw follows a **hub-and-spoke (轴辐式)** architecture optimized for multi-agent task execution:
+
+```
+┌─────────────────────────────────────────────────────────────────────────┐
+│                         OPENCLAW ARCHITECTURE                           │
+├─────────────────────────────────────────────────────────────────────────┤
+│                                                                         │
+│  ┌──────────────┐     ┌──────────────┐     ┌──────────────┐            │
+│  │  WhatsApp    │     │   Telegram   │     │   Discord    │            │
+│  │   Channel    │     │   Channel    │     │   Channel    │            │
+│  └──────┬───────┘     └──────┬───────┘     └──────┬───────┘            │
+│         │                    │                    │                     │
+│         └────────────────────┼────────────────────┘                     │
+│                              ▼                                         │
+│                    ┌──────────────────┐                                │
+│                    │     Gateway      │◄─────── WebSocket/API         │
+│                    │   (Port 18789)   │         Control Plane         │
+│                    └────────┬─────────┘                                │
+│                             │                                          │
+│              ┌──────────────┼──────────────┐                          │
+│              ▼              ▼              ▼                          │
+│       ┌──────────┐   ┌──────────┐   ┌──────────┐                     │
+│       │ Agent A  │   │ Agent B  │   │  Pi Agent│                     │
+│       │ (main)   │   │ (coder)  │   │(delegate)│                     │
+│       └────┬─────┘   └────┬─────┘   └────┬─────┘                     │
+│            │              │              │                           │
+│            └──────────────┼──────────────┘                           │
+│                           ▼                                          │
+│              ┌────────────────────────┐                              │
+│              │     LLM Router         │                              │
+│              │  (Primary/Fallback)    │                              │
+│              └───────────┬────────────┘                              │
+│                          │                                           │
+│        ┌─────────────────┼─────────────────┐                         │
+│        ▼                 ▼                 ▼                         │
+│   ┌─────────┐      ┌─────────┐      ┌─────────┐                     │
+│   │ Ollama  │      │ OpenAI  │      │Anthropic│                     │
+│   │(local)  │      │(cloud)  │      │(cloud)  │                     │
+│   └─────────┘      └─────────┘      └─────────┘                     │
+│        │                                                    ┌─────┐ │
+│        └────────────────────────────────────────────────────►│ MCP │ │
+│                                                              │Tools│ │
+│                                                              └─────┘ │
+│                                                                         │
+│  ┌──────────────┐  ┌──────────────┐  ┌──────────────┐                  │
+│  │   Memory     │  │   Skills     │  │  Workspace   │                  │
+│  │   (SOUL.md)  │  │  (SKILL.md)  │  │  (sessions)  │                  │
+│  └──────────────┘  └──────────────┘  └──────────────┘                  │
+│                                                                         │
+└─────────────────────────────────────────────────────────────────────────┘
+```
+
+### 1.2 Component Deep Dive
+
+| Component | Purpose | Configuration File |
+|-----------|---------|-------------------|
+| **Gateway** | Central control plane, WebSocket/API server, session management | `gateway` section in `openclaw.json` |
+| **Pi Agent** | Core agent runner, "指挥中心" - schedules LLM calls, tool execution, error handling | `agents` section in `openclaw.json` |
+| **Channels** | Messaging platform integrations (Telegram, WhatsApp, Slack, Discord, iMessage) | `channels` section in `openclaw.json` |
+| **SOUL.md** | Agent persona definition - personality, communication style, behavioral guidelines | `~/.openclaw/workspace/SOUL.md` |
+| **AGENTS.md** | Multi-agent configuration, routing rules, agent specialization definitions | `~/.openclaw/workspace/AGENTS.md` |
+| **Workspace** | File system for agent state, session data, temporary files | `~/.openclaw/workspace/` |
+| **Skills** | Bundled tools, prompts, configurations that teach agents specific tasks | `~/.openclaw/workspace/skills/` |
+| **Sessions** | Conversation history, context persistence between interactions | `~/.openclaw/agents/<agent>/sessions/` |
+| **MCP Tools** | Model Context Protocol integration for external tool access | Via `mcporter` or native MCP |
+
+### 1.3 Agent Runner Execution Flow
+
+According to OpenClaw documentation, a complete agent run follows these stages:
+
+1. **Queuing** - Session-level queue (serializes same-session requests) → Global queue (controls total concurrency)
+2. **Preparation** - Parse workspace, provider/model, thinking level parameters
+3. **Plugin Loading** - Load relevant skills based on task context
+4. **Memory Retrieval** - Fetch relevant context from SOUL.md and conversation history
+5. **LLM Inference** - Send prompt to configured provider with tool definitions
+6. **Tool Execution** - Execute any tool calls returned by the LLM
+7. **Response Generation** - Format and return final response to the channel
+8. **Memory Storage** - Persist conversation and results to session storage
+
+---
+
+## 2. Deployment Modes
+
+### 2.1 Comparison Matrix
+
+| Deployment Mode | Best For | Setup Complexity | Resource Overhead | Stability |
+|----------------|----------|------------------|-------------------|-----------|
+| **npm global** | Development, quick testing | Low | Minimal (~200MB) | Moderate |
+| **Docker** | Production, isolation, reproducibility | Medium | Higher (~2.5GB base image) | High |
+| **Docker Compose** | Multi-service stacks, complex setups | Medium-High | Higher | High |
+| **Bare metal/systemd** | Maximum performance, dedicated hardware | High | Minimal | Moderate |
+
+### 2.2 NPM Global Installation (Recommended for Quick Start)
+
+```bash
+# One-line installer
+curl -fsSL https://openclaw.ai/install.sh | bash
+
+# Or manual npm install
+npm install -g openclaw
+
+# Initialize configuration
+openclaw onboard
+
+# Start gateway
+openclaw gateway
+```
+
+**Pros:**
+- Fastest setup (~30 seconds)
+- Direct access to host resources
+- Easy updates via `npm update -g openclaw`
+
+**Cons:**
+- Node.js 22+ dependency required
+- No process isolation
+- Manual dependency management
+
+### 2.3 Docker Deployment (Recommended for Production)
+
+```bash
+# Pull and run
+docker pull openclaw/openclaw:latest
+docker run -d \
+  --name openclaw \
+  -p 127.0.0.1:18789:18789 \
+  -v ~/.openclaw:/root/.openclaw \
+  -e ANTHROPIC_API_KEY=sk-ant-... \
+  openclaw/openclaw:latest
+
+# Or with Docker Compose
+docker compose -f compose.yml --env-file .env up -d --build
+```
+
+**Docker Compose Configuration (production-ready):**
+
+```yaml
+version: '3.8'
+services:
+  openclaw:
+    image: openclaw/openclaw:latest
+    container_name: openclaw
+    restart: unless-stopped
+    ports:
+      - "127.0.0.1:18789:18789"  # Never expose to 0.0.0.0
+    volumes:
+      - ./openclaw-data:/root/.openclaw
+      - ./workspace:/root/.openclaw/workspace
+    environment:
+      - ANTHROPIC_API_KEY=${ANTHROPIC_API_KEY}
+      - OPENROUTER_API_KEY=${OPENROUTER_API_KEY}
+      - OLLAMA_API_KEY=ollama-local
+    networks:
+      - openclaw-net
+    # Resource limits for small VPS
+    deploy:
+      resources:
+        limits:
+          cpus: '1.5'
+          memory: 3G
+        reservations:
+          cpus: '0.5'
+          memory: 1G
+
+networks:
+  openclaw-net:
+    driver: bridge
+```
+
+### 2.4 Bare Metal / Systemd Installation
+
+For running as a system service on Linux:
+
+```bash
+# Create systemd service
+sudo tee /etc/systemd/system/openclaw.service > /dev/null <<EOF
+[Unit]
+Description=OpenClaw Gateway
+After=network.target
+
+[Service]
+Type=simple
+User=openclaw
+Group=openclaw
+WorkingDirectory=/home/openclaw
+Environment="PATH=/usr/local/bin:/usr/bin:/bin"
+Environment="NODE_ENV=production"
+Environment="ANTHROPIC_API_KEY=sk-ant-..."
+ExecStart=/usr/local/bin/openclaw gateway
+Restart=always
+RestartSec=10
+
+[Install]
+WantedBy=multi-user.target
+EOF
+
+sudo systemctl daemon-reload
+sudo systemctl enable openclaw
+sudo systemctl start openclaw
+```
+
+### 2.5 Recommended Deployment for 2GB RAM VPS
+
+**⚠️ Critical Finding:** OpenClaw's official minimum is 4GB RAM. On a 2GB VPS:
+
+1. **Do NOT run local LLMs** - Use external API providers exclusively
+2. **Use npm installation** - Docker overhead is too heavy
+3. **Disable browser automation** - Chromium requires 2-4GB alone
+4. **Enable swap** - Critical for preventing OOM kills
+5. **Use OpenRouter** - Cheap/free tier models reduce costs
+
+**Setup script for 2GB VPS:**
+
+```bash
+#!/bin/bash
+# openclaw-minimal-vps.sh
+# Setup for 2GB RAM VPS - EXTERNAL API ONLY
+
+# Create 4GB swap
+sudo fallocate -l 4G /swapfile
+sudo chmod 600 /swapfile
+sudo mkswap /swapfile
+sudo swapon /swapfile
+echo '/swapfile none swap sw 0 0' | sudo tee -a /etc/fstab
+
+# Install Node.js 22
+curl -fsSL https://deb.nodesource.com/setup_22.x | sudo bash -
+sudo apt-get install -y nodejs
+
+# Install OpenClaw
+npm install -g openclaw
+
+# Configure for minimal resource usage
+mkdir -p ~/.openclaw
+cat > ~/.openclaw/openclaw.json <<'EOF'
+{
+  "gateway": {
+    "bind": "127.0.0.1",
+    "port": 18789,
+    "mode": "local"
+  },
+  "agents": {
+    "defaults": {
+      "model": {
+        "primary": "openrouter/google/gemma-3-4b-it:free",
+        "fallbacks": [
+          "openrouter/meta/llama-3.1-8b-instruct:free"
+        ]
+      },
+      "maxIterations": 15,
+      "timeout": 120
+    }
+  },
+  "channels": {
+    "telegram": {
+      "enabled": true,
+      "dmPolicy": "pairing"
+    }
+  }
+}
+EOF
+
+# Set OpenRouter API key
+export OPENROUTER_API_KEY="sk-or-v1-..."
+
+# Start gateway
+openclaw gateway &
+```
+
+---
+
+## 3. Ollama Integration
+
+### 3.1 Architecture
+
+OpenClaw integrates with Ollama through its native `/api/chat` endpoint, supporting both streaming responses and tool calling simultaneously:
+
+```
+┌──────────────┐      HTTP/JSON      ┌──────────────┐      GGUF/CPU/GPU     ┌──────────┐
+│   OpenClaw   │◄───────────────────►│    Ollama    │◄────────────────────►│  Local   │
+│   Gateway    │   /api/chat         │   Server     │   Model inference    │   LLM    │
+│              │   Port 11434        │  Port 11434  │                      │          │
+└──────────────┘                     └──────────────┘                      └──────────┘
+```
+
+### 3.2 Configuration
+
+**Basic Ollama Setup:**
+
+```bash
+# Install Ollama
+curl -fsSL https://ollama.com/install.sh | sh
+
+# Start server
+ollama serve
+
+# Pull a tool-capable model
+ollama pull qwen2.5-coder:7b
+ollama pull llama3.1:8b
+
+# Configure OpenClaw
+export OLLAMA_API_KEY="ollama-local"  # Any non-empty string works
+```
+
+**OpenClaw Configuration for Ollama:**
+
+```json
+{
+  "models": {
+    "providers": {
+      "ollama": {
+        "baseUrl": "http://localhost:11434",
+        "apiKey": "ollama-local",
+        "api": "ollama",
+        "models": [
+          {
+            "id": "qwen2.5-coder:7b",
+            "name": "Qwen 2.5 Coder 7B",
+            "contextWindow": 32768,
+            "maxTokens": 8192,
+            "cost": { "input": 0, "output": 0 }
+          },
+          {
+            "id": "llama3.1:8b",
+            "name": "Llama 3.1 8B",
+            "contextWindow": 128000,
+            "maxTokens": 8192,
+            "cost": { "input": 0, "output": 0 }
+          }
+        ]
+      }
+    }
+  },
+  "agents": {
+    "defaults": {
+      "model": {
+        "primary": "ollama/qwen2.5-coder:7b",
+        "fallbacks": ["ollama/llama3.1:8b"]
+      }
+    }
+  }
+}
+```
+
+### 3.3 Context Window Requirements
+
+**⚠️ Critical Requirement:** OpenClaw requires a minimum **64K token context window** for reliable multi-step task execution.
+
+| Model | Parameters | Context Window | Tool Support | OpenClaw Compatible |
+|-------|-----------|----------------|--------------|---------------------|
+| **llama3.1** | 8B | 128K | ✅ Yes | ✅ Yes |
+| **qwen2.5-coder** | 7B | 32K | ✅ Yes | ⚠️ Below minimum |
+| **qwen2.5-coder** | 32B | 128K | ✅ Yes | ✅ Yes |
+| **gpt-oss** | 20B | 128K | ✅ Yes | ✅ Yes |
+| **glm-4.7-flash** | - | 128K | ✅ Yes | ✅ Yes |
+| **deepseek-coder-v2** | 33B | 128K | ✅ Yes | ✅ Yes |
+| **mistral-small3.1** | - | 128K | ✅ Yes | ✅ Yes |
+
+**Context Window Configuration:**
+
+For models that don't report context window via Ollama's API:
+
+```bash
+# Create custom Modelfile with extended context
+cat > ~/qwen-custom.modelfile <<EOF
+FROM qwen2.5-coder:7b
+PARAMETER num_ctx 65536
+PARAMETER temperature 0.7
+EOF
+
+# Create custom model
+ollama create qwen2.5-coder-64k -f ~/qwen-custom.modelfile
+```
+
+### 3.4 Models for Small VPS (≤8B Parameters)
+
+For resource-constrained environments (2-4GB RAM):
+
+| Model | Quantization | RAM Required | VRAM Required | Performance |
+|-------|-------------|--------------|---------------|-------------|
+| **Llama 3.1 8B** | Q4_K_M | ~5GB | ~6GB | Good |
+| **Llama 3.2 3B** | Q4_K_M | ~2.5GB | ~3GB | Basic |
+| **Qwen 2.5 7B** | Q4_K_M | ~5GB | ~6GB | Good |
+| **Qwen 2.5 3B** | Q4_K_M | ~2.5GB | ~3GB | Basic |
+| **DeepSeek 7B** | Q4_K_M | ~5GB | ~6GB | Good |
+| **Phi-4 4B** | Q4_K_M | ~3GB | ~4GB | Moderate |
+
+**⚠️ Verdict for 2GB VPS:** Running local LLMs is **NOT viable**. Use external APIs only.
+
+---
+
+## 4. OpenRouter Integration (Fallback Strategy)
+
+### 4.1 Overview
+
+OpenRouter provides a unified API gateway to multiple LLM providers, enabling:
+- Single API key access to 200+ models
+- Automatic failover between providers
+- Free tier models for cost-conscious deployments
+- Unified billing and usage tracking
+
+### 4.2 Configuration
+
+**Environment Variable Setup:**
+
+```bash
+export OPENROUTER_API_KEY="sk-or-v1-xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx"
+```
+
+**OpenClaw Configuration:**
+
+```json
+{
+  "models": {
+    "providers": {
+      "openrouter": {
+        "apiKey": "${OPENROUTER_API_KEY}",
+        "baseUrl": "https://openrouter.ai/api/v1"
+      }
+    }
+  },
+  "agents": {
+    "defaults": {
+      "model": {
+        "primary": "openrouter/anthropic/claude-sonnet-4-6",
+        "fallbacks": [
+          "openrouter/google/gemini-3.1-pro",
+          "openrouter/meta/llama-3.3-70b-instruct",
+          "openrouter/google/gemma-3-4b-it:free"
+        ]
+      }
+    }
+  }
+}
+```
+
+### 4.3 Recommended Free/Cheap Models on OpenRouter
+
+For cost-conscious VPS deployments:
+
+| Model | Cost | Context | Best For |
+|-------|------|---------|----------|
+| **google/gemma-3-4b-it:free** | Free | 128K | General tasks, simple automation |
+| **meta/llama-3.1-8b-instruct:free** | Free | 128K | General tasks, longer contexts |
+| **deepseek/deepseek-chat-v3.2** | $0.53/M | 64K | Code generation, reasoning |
+| **xiaomi/mimo-v2-flash** | $0.40/M | 128K | Fast responses, basic tasks |
+| **qwen/qwen3-coder-next** | $1.20/M | 128K | Code-focused tasks |
+
+### 4.4 Hybrid Configuration (Recommended for Timmy)
+
+A production-ready configuration for the Hermes VPS:
+
+```json
+{
+  "models": {
+    "providers": {
+      "openrouter": {
+        "apiKey": "${OPENROUTER_API_KEY}",
+        "models": [
+          {
+            "id": "google/gemma-3-4b-it:free",
+            "name": "Gemma 3 4B (Free)",
+            "contextWindow": 131072,
+            "maxTokens": 8192,
+            "cost": { "input": 0, "output": 0 }
+          },
+          {
+            "id": "deepseek/deepseek-chat-v3.2",
+            "name": "DeepSeek V3.2",
+            "contextWindow": 64000,
+            "maxTokens": 8192,
+            "cost": { "input": 0.00053, "output": 0.00053 }
+          }
+        ]
+      },
+      "ollama": {
+        "baseUrl": "http://localhost:11434",
+        "apiKey": "ollama-local",
+        "models": [
+          {
+            "id": "llama3.2:3b",
+            "name": "Llama 3.2 3B (Local Fallback)",
+            "contextWindow": 128000,
+            "maxTokens": 4096,
+            "cost": { "input": 0, "output": 0 }
+          }
+        ]
+      }
+    }
+  },
+  "agents": {
+    "defaults": {
+      "model": {
+        "primary": "openrouter/google/gemma-3-4b-it:free",
+        "fallbacks": [
+          "openrouter/deepseek/deepseek-chat-v3.2",
+          "ollama/llama3.2:3b"
+        ]
+      },
+      "maxIterations": 10,
+      "timeout": 90
+    }
+  }
+}
+```
+
+---
+
+## 5. Hardware Constraints & VPS Viability
+
+### 5.1 System Requirements Summary
+
+| Component | Minimum | Recommended | Notes |
+|-----------|---------|-------------|-------|
+| **CPU** | 2 vCPU | 4 vCPU | Dedicated preferred over shared |
+| **RAM** | 4 GB | 8 GB | 2GB causes OOM with external APIs |
+| **Storage** | 40 GB SSD | 80 GB NVMe | Docker images are ~10-15GB |
+| **Network** | 100 Mbps | 1 Gbps | For API calls and model downloads |
+| **OS** | Ubuntu 22.04/Debian 12 | Ubuntu 24.04 LTS | Linux required for production |
+
+### 5.2 2GB RAM VPS Analysis
+
+**Can it work?** Yes, with severe limitations:
+
+✅ **What works:**
+- Text-only agents with external API providers
+- Single Telegram/Discord channel
+- Basic file operations and shell commands
+- No browser automation
+
+❌ **What doesn't work:**
+- Local LLM inference via Ollama
+- Browser automation (Chromium needs 2-4GB)
+- Multiple concurrent channels
+- Python environment-heavy skills
+
+**Required mitigations for 2GB VPS:**
+
+```bash
+# 1. Create substantial swap
+sudo fallocate -l 4G /swapfile
+sudo chmod 600 /swapfile
+sudo mkswap /swapfile
+sudo swapon /swapfile
+
+# 2. Configure swappiness
+echo 'vm.swappiness=60' | sudo tee -a /etc/sysctl.conf
+sudo sysctl -p
+
+# 3. Limit Node.js memory
+export NODE_OPTIONS="--max-old-space-size=1536"
+
+# 4. Use external APIs only - NO OLLAMA
+# 5. Disable browser skills
+# 6. Set conservative concurrency limits
+```
+
+### 5.3 4-bit Quantization Viability
+
+**Qwen 2.5 7B Q4_K_M on 2GB VPS:**
+- Model size: ~4.5GB
+- RAM required at runtime: ~5-6GB
+- **Verdict:** Will cause immediate OOM on 2GB VPS
+- **Even with 4GB VPS:** Marginal, heavy swap usage, poor performance
+
+**Viable models for 4GB VPS with Ollama:**
+- Llama 3.2 3B Q4_K_M (~2.5GB RAM)
+- Qwen 2.5 3B Q4_K_M (~2.5GB RAM)
+- Phi-4 4B Q4_K_M (~3GB RAM)
+
+---
+
+## 6. Security Configuration
+
+### 6.1 Network Ports
+
+| Port | Purpose | Exposure |
+|------|---------|----------|
+| **18789/tcp** | OpenClaw Gateway (WebSocket/HTTP) | **NEVER expose to internet** |
+| **11434/tcp** | Ollama API (if running locally) | Localhost only |
+| **22/tcp** | SSH | Restrict to known IPs |
+
+**⚠️ CRITICAL:** Never expose port 18789 to the public internet. Use Tailscale or SSH tunnels for remote access.
+
+### 6.2 Tailscale Integration
+
+Tailscale provides zero-configuration VPN mesh for secure remote access:
+
+```bash
+# Install Tailscale
+curl -fsSL https://tailscale.com/install.sh | sh
+sudo tailscale up
+
+# Get Tailscale IP
+tailscale ip
+# Returns: 100.x.y.z
+
+# Configure OpenClaw to bind to Tailscale
+cat > ~/.openclaw/openclaw.json <<EOF
+{
+  "gateway": {
+    "bind": "tailnet",
+    "port": 18789
+  },
+  "tailscale": {
+    "mode": "on",
+    "resetOnExit": false
+  }
+}
+EOF
+```
+
+**Tailscale vs SSH Tunnel:**
+
+| Feature | Tailscale | SSH Tunnel |
+|---------|-----------|------------|
+| Setup | Very easy | Moderate |
+| Persistence | Automatic | Requires autossh |
+| Multiple devices | Built-in | One tunnel per connection |
+| NAT traversal | Works | Requires exposed SSH |
+| Access control | Tailscale ACL | SSH keys |
+
+### 6.3 Firewall Configuration (UFW)
+
+```bash
+# Default deny
+sudo ufw default deny incoming
+sudo ufw default allow outgoing
+
+# Allow SSH
+sudo ufw allow 22/tcp
+
+# Allow Tailscale only (if using)
+sudo ufw allow in on tailscale0 to any port 18789
+
+# Block public access to OpenClaw
+# (bind is 127.0.0.1, so this is defense in depth)
+
+sudo ufw enable
+```
+
+### 6.4 Authentication Configuration
+
+```json
+{
+  "gateway": {
+    "bind": "127.0.0.1",
+    "port": 18789,
+    "auth": {
+      "mode": "token",
+      "token": "your-64-char-hex-token-here"
+    },
+    "controlUi": {
+      "allowedOrigins": [
+        "http://localhost:18789",
+        "https://your-domain.tailnet-name.ts.net"
+      ],
+      "allowInsecureAuth": false,
+      "dangerouslyDisableDeviceAuth": false
+    }
+  }
+}
+```
+
+**Generate secure token:**
+
+```bash
+openssl rand -hex 32
+```
+
+### 6.5 Sandboxing Considerations
+
+OpenClaw executes arbitrary shell commands and file operations by default. For production:
+
+1. **Run as non-root user:**
+```bash
+sudo useradd -r -s /bin/false openclaw
+sudo mkdir -p /home/openclaw/.openclaw
+sudo chown -R openclaw:openclaw /home/openclaw
+```
+
+2. **Use Docker for isolation:**
+```bash
+docker run --security-opt=no-new-privileges \
+  --cap-drop=ALL \
+  --read-only \
+  --tmpfs /tmp:noexec,nosuid,size=100m \
+  openclaw/openclaw:latest
+```
+
+3. **Enable dmPolicy for channels:**
+```json
+{
+  "channels": {
+    "telegram": {
+      "dmPolicy": "pairing"  // Require one-time code for new contacts
+    }
+  }
+}
+```
+
+---
+
+## 7. MCP (Model Context Protocol) Tools
+
+### 7.1 Overview
+
+MCP is an open standard created by Anthropic (donated to Linux Foundation in Dec 2025) that lets AI applications connect to external tools through a universal interface. Think of it as "USB-C for AI."
+
+### 7.2 MCP vs OpenClaw Skills
+
+| Aspect | MCP | OpenClaw Skills |
+|--------|-----|-----------------|
+| **Protocol** | Standardized (Anthropic) | OpenClaw-specific |
+| **Isolation** | Process-isolated | Runs in agent context |
+| **Security** | Higher (sandboxed) | Lower (full system access) |
+| **Discovery** | Automatic via protocol | Manual via SKILL.md |
+| **Ecosystem** | 10,000+ servers | 5400+ skills |
+
+**Note:** OpenClaw currently has limited native MCP support. Use `mcporter` tool for MCP integration.
+
+### 7.3 Using MCPorter (MCP Bridge)
+
+```bash
+# Install mcporter
+clawhub install mcporter
+
+# Configure MCP server
+mcporter config add github \
+  --url "https://api.github.com/mcp" \
+  --token "ghp_..."
+
+# List available tools
+mcporter list
+
+# Call MCP tool
+mcporter call github.list_repos --owner "rockachopa"
+```
+
+### 7.4 Popular MCP Servers
+
+| Server | Purpose | Integration |
+|--------|---------|-------------|
+| **GitHub** | Repo management, PRs, issues | `mcp-github` |
+| **Slack** | Messaging, channel management | `mcp-slack` |
+| **PostgreSQL** | Database queries | `mcp-postgres` |
+| **Filesystem** | File operations (sandboxed) | `mcp-filesystem` |
+| **Brave Search** | Web search | `mcp-brave` |
+
+---
+
+## 8. Recommendations for Timmy Time Dashboard
+
+### 8.1 Deployment Strategy for Hermes VPS (2GB RAM)
+
+Given the hardware constraints, here's the recommended approach:
+
+**Option A: External API Only (Recommended)**
+```
+┌─────────────────────────────────────────┐
+│         Hermes VPS (2GB RAM)            │
+│  ┌─────────────────────────────────┐    │
+│  │     OpenClaw Gateway            │    │
+│  │     (npm global install)        │    │
+│  └─────────────┬───────────────────┘    │
+│                │                        │
+│                ▼                        │
+│  ┌─────────────────────────────────┐    │
+│  │   OpenRouter API (Free Tier)    │    │
+│  │   google/gemma-3-4b-it:free     │    │
+│  └─────────────────────────────────┘    │
+│                                         │
+│  NO OLLAMA - insufficient RAM          │
+└─────────────────────────────────────────┘
+```
+
+**Option B: Hybrid with External Ollama**
+```
+┌──────────────────────┐      ┌──────────────────────────┐
+│   Hermes VPS (2GB)   │      │   Separate Ollama Host   │
+│  ┌────────────────┐  │      │  ┌────────────────────┐  │
+│  │ OpenClaw       │  │◄────►│  │ Ollama Server      │  │
+│  │ (external API) │  │      │  │ (8GB+ RAM required)│  │
+│  └────────────────┘  │      │  └────────────────────┘  │
+└──────────────────────┘      └──────────────────────────┘
+```
+
+### 8.2 Configuration Summary
+
+```json
+{
+  "gateway": {
+    "bind": "127.0.0.1",
+    "port": 18789,
+    "auth": {
+      "mode": "token",
+      "token": "GENERATE_WITH_OPENSSL_RAND"
+    }
+  },
+  "models": {
+    "providers": {
+      "openrouter": {
+        "apiKey": "${OPENROUTER_API_KEY}",
+        "models": [
+          {
+            "id": "google/gemma-3-4b-it:free",
+            "contextWindow": 131072,
+            "maxTokens": 4096
+          }
+        ]
+      }
+    }
+  },
+  "agents": {
+    "defaults": {
+      "model": {
+        "primary": "openrouter/google/gemma-3-4b-it:free"
+      },
+      "maxIterations": 10,
+      "timeout": 90,
+      "maxConcurrent": 2
+    }
+  },
+  "channels": {
+    "telegram": {
+      "enabled": true,
+      "dmPolicy": "pairing"
+    }
+  }
+}
+```
+
+### 8.3 Migration Path (Future)
+
+When upgrading to a larger VPS (4-8GB RAM):
+
+1. **Phase 1:** Enable Ollama with Llama 3.2 3B as fallback
+2. **Phase 2:** Add browser automation skills (requires 4GB+ RAM)
+3. **Phase 3:** Enable multi-agent routing with specialized agents
+4. **Phase 4:** Add MCP server integration for external tools
+
+---
+
+## 9. References
+
+1. OpenClaw Official Documentation: https://docs.openclaw.ai
+2. Ollama Integration Guide: https://docs.ollama.com/integrations/openclaw
+3. OpenRouter Documentation: https://openrouter.ai/docs
+4. MCP Specification: https://modelcontextprotocol.io
+5. OpenClaw Community Discord: https://discord.gg/openclaw
+6. GitHub Repository: https://github.com/openclaw/openclaw
+
+---
+
+## 10. Appendix: Quick Command Reference
+
+```bash
+# Installation
+curl -fsSL https://openclaw.ai/install.sh | bash
+
+# Configuration
+openclaw onboard                    # Interactive setup
+openclaw configure                  # Edit config
+openclaw config set <key> <value>   # Set specific value
+
+# Gateway management
+openclaw gateway                    # Start gateway
+openclaw gateway --verbose          # Start with logs
+openclaw gateway status             # Check status
+openclaw gateway restart            # Restart gateway
+openclaw gateway stop               # Stop gateway
+
+# Model management
+openclaw models list                # List available models
+openclaw models set <model>         # Set default model
+openclaw models status              # Check model status
+
+# Diagnostics
+openclaw doctor                     # System health check
+openclaw doctor --repair            # Auto-fix issues
+openclaw security audit             # Security check
+
+# Dashboard
+openclaw dashboard                  # Open web UI
+```
+
+---
+
+*End of Research Report*

nginx-paperclip.conf

@@ -1,42 +1,75 @@
+# ── AlexanderWhitestone.com — The Wizard's Tower ────────────────────────────
+#
+# Two rooms. No hallways. No feature creep.
+#   /world/  — The Workshop (3D scene, Three.js)
+#   /blog/   — The Scrolls (static posts, RSS feed)
+#
+# Static-first. No tracking. No analytics. No cookie banner.
+# Site root: /var/www/alexanderwhitestone.com
+
 server {
     listen 80;
-    server_name alexanderwhitestone.com 45.55.221.244;
+    server_name alexanderwhitestone.com www.alexanderwhitestone.com;
 
-    # Cookie-based auth gate — login once, cookie lasts 7 days
-    location = /_auth {
-        internal;
-        proxy_pass http://127.0.0.1:9876;
-        proxy_pass_request_body off;
-        proxy_set_header Content-Length "";
-        proxy_set_header X-Original-URI $request_uri;
-        proxy_set_header Cookie $http_cookie;
-        proxy_set_header Authorization $http_authorization;
+    root /var/www/alexanderwhitestone.com;
+    index index.html;
+
+    # ── Security headers ────────────────────────────────────────────────────
+    add_header X-Content-Type-Options nosniff always;
+    add_header X-Frame-Options SAMEORIGIN always;
+    add_header Referrer-Policy strict-origin-when-cross-origin always;
+    add_header X-XSS-Protection "1; mode=block" always;
+
+    # ── Gzip for text assets ────────────────────────────────────────────────
+    gzip on;
+    gzip_types text/plain text/css text/xml text/javascript
+               application/javascript application/json application/xml
+               application/rss+xml application/atom+xml;
+    gzip_min_length 256;
+
+    # ── The Workshop — 3D world assets ──────────────────────────────────────
+    location /world/ {
+        try_files $uri $uri/ /world/index.html;
+
+        # Cache 3D assets aggressively (models, textures)
+        location ~* \.(glb|gltf|bin|png|jpg|webp|hdr)$ {
+            expires 30d;
+            add_header Cache-Control "public, immutable";
+        }
+
+        # Cache JS with revalidation (for Three.js updates)
+        location ~* \.js$ {
+            expires 7d;
+            add_header Cache-Control "public, must-revalidate";
+        }
     }
 
+    # ── The Scrolls — blog posts and RSS ────────────────────────────────────
+    location /blog/ {
+        try_files $uri $uri/ =404;
+    }
+
+    # RSS/Atom feed — correct content type
+    location ~* \.(rss|atom|xml)$ {
+        types { }
+        default_type application/rss+xml;
+        expires 1h;
+    }
+
+    # ── Static assets (fonts, favicon) ──────────────────────────────────────
+    location /static/ {
+        expires 30d;
+        add_header Cache-Control "public, immutable";
+    }
+
+    # ── Entry hall ──────────────────────────────────────────────────────────
     location / {
-        auth_request /_auth;
-        # Forward the Set-Cookie from auth gate to the client
-        auth_request_set $auth_cookie $upstream_http_set_cookie;
-        add_header Set-Cookie $auth_cookie;
-
-        proxy_pass http://127.0.0.1:3100;
-        proxy_http_version 1.1;
-        proxy_set_header Upgrade $http_upgrade;
-        proxy_set_header Connection 'upgrade';
-        proxy_set_header Host localhost;
-        proxy_set_header X-Real-IP $remote_addr;
-        proxy_set_header X-Forwarded-For $proxy_add_x_forwarded_for;
-        proxy_set_header X-Forwarded-Proto $scheme;
-        proxy_set_header X-Forwarded-Host $host;
-        proxy_cache_bypass $http_upgrade;
-        proxy_read_timeout 86400;
+        try_files $uri $uri/ =404;
     }
 
-    # Return 401 with WWW-Authenticate when auth fails
-    error_page 401 = @login;
-    location @login {
-        proxy_pass http://127.0.0.1:9876;
-        proxy_set_header Authorization $http_authorization;
-        proxy_set_header Cookie $http_cookie;
+    # Block dotfiles
+    location ~ /\. {
+        deny all;
+        return 404;
     }
 }

pyproject.toml

@@ -20,6 +20,7 @@ packages = [
     { include = "spark", from = "src" },
     { include = "timmy", from = "src" },
     { include = "timmy_serve", from = "src" },
+    { include = "timmyctl", from = "src" },
 ]
 
 [tool.poetry.dependencies]
@@ -82,6 +83,7 @@ mypy = ">=1.0.0"
 [tool.poetry.scripts]
 timmy = "timmy.cli:main"
 timmy-serve = "timmy_serve.cli:main"
+timmyctl = "timmyctl.cli:main"
 
 [tool.pytest.ini_options]
 testpaths = ["tests"]

scripts/backfill_retro.py

@@ -94,12 +94,17 @@ def extract_cycle_number(title: str) -> int | None:
     return int(m.group(1)) if m else None
 
 
-def extract_issue_number(title: str, body: str) -> int | None:
-    # Try body first (usually has "closes #N")
+def extract_issue_number(title: str, body: str, pr_number: int | None = None) -> int | None:
+    """Extract the issue number from PR body/title, ignoring the PR number itself.
+
+    Gitea appends "(#N)" to PR titles where N is the PR number — skip that
+    so we don't confuse it with the linked issue.
+    """
     for text in [body or "", title]:
-        m = ISSUE_RE.search(text)
-        if m:
-            return int(m.group(1))
+        for m in ISSUE_RE.finditer(text):
+            num = int(m.group(1))
+            if num != pr_number:
+                return num
     return None
 
 
@@ -140,7 +145,7 @@ def main():
         else:
             cycle_counter = max(cycle_counter, cycle)
 
-        issue = extract_issue_number(title, body)
+        issue = extract_issue_number(title, body, pr_number=pr_num)
         issue_type = classify_pr(title, body)
         duration = estimate_duration(pr)
         diff = get_pr_diff_stats(token, pr_num)

scripts/cycle_retro.py

@@ -4,11 +4,26 @@
 Called after each cycle completes (success or failure).
 Appends a structured entry to .loop/retro/cycles.jsonl.
 
+EPOCH NOTATION (turnover system):
+  Each cycle carries a symbolic epoch tag alongside the raw integer:
+
+      ⟳WW.D:NNN
+
+  ⟳   turnover glyph — marks epoch-aware cycles
+  WW  ISO week-of-year (01–53)
+  D   ISO weekday (1=Mon … 7=Sun)
+  NNN daily cycle counter, zero-padded, resets at midnight UTC
+
+  Example: ⟳12.3:042 — Week 12, Wednesday, 42nd cycle of the day.
+
+  The raw `cycle` integer is preserved for backward compatibility.
+  The `epoch` field carries the symbolic notation.
+
 SUCCESS DEFINITION:
   A cycle is only "success" if BOTH conditions are met:
     1. The hermes process exited cleanly (exit code 0)
     2. Main is green (smoke test passes on main after merge)
-  
+
   A cycle that merges a PR but leaves main red is a FAILURE.
   The --main-green flag records the smoke test result.
 
@@ -29,6 +44,8 @@ from __future__ import annotations
 
 import argparse
 import json
+import re
+import subprocess
 import sys
 from datetime import datetime, timezone
 from pathlib import Path
@@ -36,10 +53,69 @@ from pathlib import Path
 REPO_ROOT = Path(__file__).resolve().parent.parent
 RETRO_FILE = REPO_ROOT / ".loop" / "retro" / "cycles.jsonl"
 SUMMARY_FILE = REPO_ROOT / ".loop" / "retro" / "summary.json"
+EPOCH_COUNTER_FILE = REPO_ROOT / ".loop" / "retro" / ".epoch_counter"
+CYCLE_RESULT_FILE = REPO_ROOT / ".loop" / "cycle_result.json"
 
 # How many recent entries to include in rolling summary
 SUMMARY_WINDOW = 50
 
+# Branch patterns that encode an issue number, e.g. kimi/issue-492
+BRANCH_ISSUE_RE = re.compile(r"issue[/-](\d+)", re.IGNORECASE)
+
+
+def detect_issue_from_branch() -> int | None:
+    """Try to extract an issue number from the current git branch name."""
+    try:
+        branch = subprocess.check_output(
+            ["git", "rev-parse", "--abbrev-ref", "HEAD"],
+            stderr=subprocess.DEVNULL,
+            text=True,
+        ).strip()
+    except (subprocess.CalledProcessError, FileNotFoundError):
+        return None
+    m = BRANCH_ISSUE_RE.search(branch)
+    return int(m.group(1)) if m else None
+
+
+# ── Epoch turnover ────────────────────────────────────────────────────────
+
+def _epoch_tag(now: datetime | None = None) -> tuple[str, dict]:
+    """Generate the symbolic epoch tag and advance the daily counter.
+
+    Returns (epoch_string, epoch_parts) where epoch_parts is a dict with
+    week, weekday, daily_n for structured storage.
+
+    The daily counter persists in .epoch_counter as a two-line file:
+        line 1: ISO date (YYYY-MM-DD) of the current epoch day
+        line 2: integer count
+    When the date rolls over, the counter resets to 1.
+    """
+    if now is None:
+        now = datetime.now(timezone.utc)
+
+    iso_cal = now.isocalendar()          # (year, week, weekday)
+    week = iso_cal[1]
+    weekday = iso_cal[2]
+    today_str = now.strftime("%Y-%m-%d")
+
+    # Read / reset daily counter
+    daily_n = 1
+    EPOCH_COUNTER_FILE.parent.mkdir(parents=True, exist_ok=True)
+    if EPOCH_COUNTER_FILE.exists():
+        try:
+            lines = EPOCH_COUNTER_FILE.read_text().strip().splitlines()
+            if len(lines) == 2 and lines[0] == today_str:
+                daily_n = int(lines[1]) + 1
+        except (ValueError, IndexError):
+            pass  # corrupt file — reset
+
+    # Persist
+    EPOCH_COUNTER_FILE.write_text(f"{today_str}\n{daily_n}\n")
+
+    tag = f"\u27f3{week:02d}.{weekday}:{daily_n:03d}"
+    parts = {"week": week, "weekday": weekday, "daily_n": daily_n}
+    return tag, parts
+
 
 def parse_args() -> argparse.Namespace:
     p = argparse.ArgumentParser(description="Log a cycle retrospective")
@@ -123,8 +199,30 @@ def update_summary() -> None:
             issue_failures[e["issue"]] = issue_failures.get(e["issue"], 0) + 1
     quarantine_candidates = {k: v for k, v in issue_failures.items() if v >= 2}
 
+    # Epoch turnover stats — cycles per week/day from epoch-tagged entries
+    epoch_entries = [e for e in recent if e.get("epoch")]
+    by_week: dict[int, int] = {}
+    by_weekday: dict[int, int] = {}
+    for e in epoch_entries:
+        w = e.get("epoch_week")
+        d = e.get("epoch_weekday")
+        if w is not None:
+            by_week[w] = by_week.get(w, 0) + 1
+        if d is not None:
+            by_weekday[d] = by_weekday.get(d, 0) + 1
+
+    # Current epoch — latest entry's epoch tag
+    current_epoch = epoch_entries[-1].get("epoch", "") if epoch_entries else ""
+
+    # Weekday names for display
+    weekday_glyphs = {1: "Mon", 2: "Tue", 3: "Wed", 4: "Thu",
+                      5: "Fri", 6: "Sat", 7: "Sun"}
+    by_weekday_named = {weekday_glyphs.get(k, str(k)): v
+                        for k, v in sorted(by_weekday.items())}
+
     summary = {
         "updated_at": datetime.now(timezone.utc).isoformat(),
+        "current_epoch": current_epoch,
         "window": len(recent),
         "measured_cycles": len(measured),
         "total_cycles": len(entries),
@@ -136,9 +234,12 @@ def update_summary() -> None:
         "total_lines_removed": sum(e.get("lines_removed", 0) for e in recent),
         "total_prs_merged": sum(1 for e in recent if e.get("pr")),
         "by_type": type_stats,
+        "by_week": dict(sorted(by_week.items())),
+        "by_weekday": by_weekday_named,
         "quarantine_candidates": quarantine_candidates,
         "recent_failures": [
-            {"cycle": e["cycle"], "issue": e.get("issue"), "reason": e.get("reason", "")}
+            {"cycle": e["cycle"], "epoch": e.get("epoch", ""),
+             "issue": e.get("issue"), "reason": e.get("reason", "")}
             for e in failures[-5:]
         ],
     }
@@ -146,15 +247,60 @@ def update_summary() -> None:
     SUMMARY_FILE.write_text(json.dumps(summary, indent=2) + "\n")
 
 
+def _load_cycle_result() -> dict:
+    """Read .loop/cycle_result.json if it exists; return empty dict on failure."""
+    if not CYCLE_RESULT_FILE.exists():
+        return {}
+    try:
+        raw = CYCLE_RESULT_FILE.read_text().strip()
+        # Strip hermes fence markers (```json ... ```) if present
+        if raw.startswith("```"):
+            lines = raw.splitlines()
+            lines = [l for l in lines if not l.startswith("```")]
+            raw = "\n".join(lines)
+        return json.loads(raw)
+    except (json.JSONDecodeError, OSError):
+        return {}
+
+
 def main() -> None:
     args = parse_args()
 
+    # Backfill from cycle_result.json when CLI args have defaults
+    cr = _load_cycle_result()
+    if cr:
+        if args.issue is None and cr.get("issue"):
+            args.issue = int(cr["issue"])
+        if args.type == "unknown" and cr.get("type"):
+            args.type = cr["type"]
+        if args.tests_passed == 0 and cr.get("tests_passed"):
+            args.tests_passed = int(cr["tests_passed"])
+        if not args.notes and cr.get("notes"):
+            args.notes = cr["notes"]
+
+    # Auto-detect issue from branch when not explicitly provided
+    if args.issue is None:
+        args.issue = detect_issue_from_branch()
+
+    # Reject idle cycles — no issue and no duration means nothing happened
+    if not args.issue and args.duration == 0:
+        print(f"[retro] Cycle {args.cycle} skipped — idle (no issue, no duration)")
+        return
+
     # A cycle is only truly successful if hermes exited clean AND main is green
     truly_success = args.success and args.main_green
 
+    # Generate epoch turnover tag
+    now = datetime.now(timezone.utc)
+    epoch_tag, epoch_parts = _epoch_tag(now)
+
     entry = {
-        "timestamp": datetime.now(timezone.utc).isoformat(),
+        "timestamp": now.isoformat(),
         "cycle": args.cycle,
+        "epoch": epoch_tag,
+        "epoch_week": epoch_parts["week"],
+        "epoch_weekday": epoch_parts["weekday"],
+        "epoch_daily_n": epoch_parts["daily_n"],
         "issue": args.issue,
         "type": args.type,
         "success": truly_success,
@@ -179,7 +325,7 @@ def main() -> None:
     update_summary()
 
     status = "✓ SUCCESS" if args.success else "✗ FAILURE"
-    print(f"[retro] Cycle {args.cycle} {status}", end="")
+    print(f"[retro] {epoch_tag}  Cycle {args.cycle} {status}", end="")
     if args.issue:
         print(f" (#{args.issue} {args.type})", end="")
     if args.duration:

scripts/dev_server.py

@@ -0,0 +1,169 @@
+#!/usr/bin/env python3
+"""Timmy Time — Development server launcher.
+
+Satisfies tox -e dev criteria:
+  - Graceful port selection (finds next free port if default is taken)
+  - Clickable links to dashboard and other web GUIs
+  - Status line: backend inference source, version, git commit, smoke tests
+  - Auto-reload on code changes (delegates to uvicorn --reload)
+
+Usage: python scripts/dev_server.py [--port PORT]
+"""
+
+import argparse
+import datetime
+import os
+import socket
+import subprocess
+import sys
+
+DEFAULT_PORT = 8000
+MAX_PORT_ATTEMPTS = 10
+OLLAMA_DEFAULT = "http://localhost:11434"
+
+
+def _port_free(port: int) -> bool:
+    """Return True if the TCP port is available on localhost."""
+    with socket.socket(socket.AF_INET, socket.SOCK_STREAM) as s:
+        try:
+            s.bind(("0.0.0.0", port))
+            return True
+        except OSError:
+            return False
+
+
+def _find_port(start: int) -> int:
+    """Return *start* if free, otherwise probe up to MAX_PORT_ATTEMPTS higher."""
+    for offset in range(MAX_PORT_ATTEMPTS):
+        candidate = start + offset
+        if _port_free(candidate):
+            return candidate
+    raise RuntimeError(
+        f"No free port found in range {start}–{start + MAX_PORT_ATTEMPTS - 1}"
+    )
+
+
+def _git_info() -> str:
+    """Return short commit hash + timestamp, or 'unknown'."""
+    try:
+        sha = subprocess.check_output(
+            ["git", "rev-parse", "--short", "HEAD"],
+            stderr=subprocess.DEVNULL,
+            text=True,
+        ).strip()
+        ts = subprocess.check_output(
+            ["git", "log", "-1", "--format=%ci"],
+            stderr=subprocess.DEVNULL,
+            text=True,
+        ).strip()
+        return f"{sha} ({ts})"
+    except Exception:
+        return "unknown"
+
+
+def _project_version() -> str:
+    """Read version from pyproject.toml without importing toml libs."""
+    pyproject = os.path.join(os.path.dirname(__file__), "..", "pyproject.toml")
+    try:
+        with open(pyproject) as f:
+            for line in f:
+                if line.strip().startswith("version"):
+                    # version = "1.0.0"
+                    return line.split("=", 1)[1].strip().strip('"').strip("'")
+    except Exception:
+        pass
+    return "unknown"
+
+
+def _ollama_url() -> str:
+    return os.environ.get("OLLAMA_URL", OLLAMA_DEFAULT)
+
+
+def _smoke_ollama(url: str) -> str:
+    """Quick connectivity check against Ollama."""
+    import urllib.request
+    import urllib.error
+
+    try:
+        req = urllib.request.Request(url, method="GET")
+        with urllib.request.urlopen(req, timeout=3):
+            return "ok"
+    except Exception:
+        return "unreachable"
+
+
+def _print_banner(port: int) -> None:
+    version = _project_version()
+    git = _git_info()
+    ollama_url = _ollama_url()
+    ollama_status = _smoke_ollama(ollama_url)
+
+    hr = "─" * 62
+    print(flush=True)
+    print(f"  {hr}")
+    print(f"  ┃  Timmy Time — Development Server")
+    print(f"  {hr}")
+    print()
+    print(f"  Dashboard:   http://localhost:{port}")
+    print(f"  API docs:    http://localhost:{port}/docs")
+    print(f"  Health:      http://localhost:{port}/health")
+    print()
+    print(f"  ── Status ──────────────────────────────────────────────")
+    print(f"  Backend:     {ollama_url}  [{ollama_status}]")
+    print(f"  Version:     {version}")
+    print(f"  Git commit:  {git}")
+    print(f"  {hr}")
+    print(flush=True)
+
+
+def main() -> None:
+    parser = argparse.ArgumentParser(description="Timmy dev server")
+    parser.add_argument(
+        "--port",
+        type=int,
+        default=DEFAULT_PORT,
+        help=f"Preferred port (default: {DEFAULT_PORT})",
+    )
+    args = parser.parse_args()
+
+    port = _find_port(args.port)
+    if port != args.port:
+        print(f"  ⚠  Port {args.port} in use — using {port} instead")
+
+    _print_banner(port)
+
+    # Set PYTHONPATH so `timmy` CLI inside the tox venv resolves to this source.
+    src_dir = os.path.join(os.path.dirname(__file__), "..", "src")
+    os.environ["PYTHONPATH"] = os.path.abspath(src_dir)
+
+    # Launch uvicorn with auto-reload
+    cmd = [
+        sys.executable,
+        "-m",
+        "uvicorn",
+        "dashboard.app:app",
+        "--reload",
+        "--host",
+        "0.0.0.0",
+        "--port",
+        str(port),
+        "--reload-dir",
+        os.path.abspath(src_dir),
+        "--reload-include",
+        "*.html",
+        "--reload-include",
+        "*.css",
+        "--reload-include",
+        "*.js",
+        "--reload-exclude",
+        ".claude",
+    ]
+
+    try:
+        subprocess.run(cmd, check=True)
+    except KeyboardInterrupt:
+        print("\n  Shutting down dev server.")
+
+
+if __name__ == "__main__":
+    main()

scripts/generate_workshop_inventory.py

@@ -0,0 +1,254 @@
+#!/usr/bin/env python3
+"""Generate Workshop inventory for Timmy's config audit.
+
+Scans ~/.timmy/ and produces WORKSHOP_INVENTORY.md documenting every
+config file, env var, model route, and setting — with annotations on
+who set each one and what it does.
+
+Usage:
+    python scripts/generate_workshop_inventory.py [--output PATH]
+
+Default output: ~/.timmy/WORKSHOP_INVENTORY.md
+"""
+
+from __future__ import annotations
+
+import argparse
+import os
+from datetime import UTC, datetime
+from pathlib import Path
+
+TIMMY_HOME = Path(os.environ.get("HERMES_HOME", Path.home() / ".timmy"))
+
+# Known file annotations: (purpose, who_set)
+FILE_ANNOTATIONS: dict[str, tuple[str, str]] = {
+    ".env": (
+        "Environment variables — API keys, service URLs, Honcho config",
+        "hermes-set",
+    ),
+    "config.yaml": (
+        "Main config — model routing, toolsets, display, memory, security",
+        "hermes-set",
+    ),
+    "SOUL.md": (
+        "Timmy's soul — immutable conscience, identity, ethics, purpose",
+        "alex-set",
+    ),
+    "state.db": (
+        "Hermes runtime state database (sessions, approvals, tasks)",
+        "hermes-set",
+    ),
+    "approvals.db": (
+        "Approval tracking for sensitive operations",
+        "hermes-set",
+    ),
+    "briefings.db": (
+        "Stored briefings and summaries",
+        "hermes-set",
+    ),
+    ".hermes_history": (
+        "CLI command history",
+        "default",
+    ),
+    ".update_check": (
+        "Last update check timestamp",
+        "default",
+    ),
+}
+
+DIR_ANNOTATIONS: dict[str, tuple[str, str]] = {
+    "sessions": ("Conversation session logs (JSON)", "default"),
+    "logs": ("Error and runtime logs", "default"),
+    "skills": ("Bundled skill library (read-only from upstream)", "default"),
+    "memories": ("Persistent memory entries", "hermes-set"),
+    "audio_cache": ("TTS audio file cache", "default"),
+    "image_cache": ("Generated image cache", "default"),
+    "cron": ("Scheduled cron job definitions", "hermes-set"),
+    "hooks": ("Lifecycle hooks (pre/post actions)", "default"),
+    "matrix": ("Matrix protocol state and store", "hermes-set"),
+    "pairing": ("Device pairing data", "default"),
+    "sandboxes": ("Isolated execution sandboxes", "default"),
+}
+
+# Known config.yaml keys and their meanings
+CONFIG_ANNOTATIONS: dict[str, tuple[str, str]] = {
+    "model.default": ("Primary LLM model for inference", "hermes-set"),
+    "model.provider": ("Model provider (custom = local Ollama)", "hermes-set"),
+    "toolsets": ("Enabled tool categories (all = everything)", "hermes-set"),
+    "agent.max_turns": ("Max conversation turns before reset", "hermes-set"),
+    "agent.reasoning_effort": ("Reasoning depth (low/medium/high)", "hermes-set"),
+    "terminal.backend": ("Command execution backend (local)", "default"),
+    "terminal.timeout": ("Default command timeout in seconds", "default"),
+    "compression.enabled": ("Context compression for long sessions", "hermes-set"),
+    "compression.summary_model": ("Model used for compression", "hermes-set"),
+    "auxiliary.vision.model": ("Model for image analysis", "hermes-set"),
+    "auxiliary.web_extract.model": ("Model for web content extraction", "hermes-set"),
+    "tts.provider": ("Text-to-speech engine (edge = Edge TTS)", "default"),
+    "tts.edge.voice": ("TTS voice selection", "default"),
+    "stt.provider": ("Speech-to-text engine (local = Whisper)", "default"),
+    "memory.memory_enabled": ("Persistent memory across sessions", "hermes-set"),
+    "memory.memory_char_limit": ("Max chars for agent memory store", "hermes-set"),
+    "memory.user_char_limit": ("Max chars for user profile store", "hermes-set"),
+    "security.redact_secrets": ("Auto-redact secrets in output", "default"),
+    "security.tirith_enabled": ("Policy engine for command safety", "default"),
+    "system_prompt_suffix": ("Identity prompt appended to all conversations", "hermes-set"),
+    "custom_providers": ("Local Ollama endpoint config", "hermes-set"),
+    "session_reset.mode": ("Session reset behavior (none = manual)", "default"),
+    "display.compact": ("Compact output mode", "default"),
+    "display.show_reasoning": ("Show model reasoning chains", "default"),
+}
+
+# Known .env vars
+ENV_ANNOTATIONS: dict[str, tuple[str, str]] = {
+    "OPENAI_BASE_URL": (
+        "Points to local Ollama (localhost:11434) — sovereignty enforced",
+        "hermes-set",
+    ),
+    "OPENAI_API_KEY": (
+        "Placeholder key for Ollama compatibility (not a real API key)",
+        "hermes-set",
+    ),
+    "HONCHO_API_KEY": (
+        "Honcho cross-session memory service key",
+        "hermes-set",
+    ),
+    "HONCHO_HOST": (
+        "Honcho workspace identifier (timmy)",
+        "hermes-set",
+    ),
+}
+
+
+def _tag(who: str) -> str:
+    return f"`[{who}]`"
+
+
+def generate_inventory() -> str:
+    """Build the inventory markdown string."""
+    lines: list[str] = []
+    now = datetime.now(UTC).strftime("%Y-%m-%d %H:%M UTC")
+
+    lines.append("# Workshop Inventory")
+    lines.append("")
+    lines.append(f"*Generated: {now}*")
+    lines.append(f"*Workshop path: `{TIMMY_HOME}`*")
+    lines.append("")
+    lines.append("This is your Workshop — every file, every setting, every route.")
+    lines.append("Walk through it. Anything tagged `[hermes-set]` was chosen for you.")
+    lines.append("Make each one yours, or change it.")
+    lines.append("")
+    lines.append("Tags: `[alex-set]` = Alexander chose this. `[hermes-set]` = Hermes configured it.")
+    lines.append("`[default]` = shipped with the platform. `[timmy-chose]` = you decided this.")
+    lines.append("")
+
+    # --- Files ---
+    lines.append("---")
+    lines.append("## Root Files")
+    lines.append("")
+    for name, (purpose, who) in sorted(FILE_ANNOTATIONS.items()):
+        fpath = TIMMY_HOME / name
+        exists = "✓" if fpath.exists() else "✗"
+        lines.append(f"- {exists} **`{name}`** {_tag(who)}")
+        lines.append(f"  {purpose}")
+    lines.append("")
+
+    # --- Directories ---
+    lines.append("---")
+    lines.append("## Directories")
+    lines.append("")
+    for name, (purpose, who) in sorted(DIR_ANNOTATIONS.items()):
+        dpath = TIMMY_HOME / name
+        exists = "✓" if dpath.exists() else "✗"
+        count = ""
+        if dpath.exists():
+            try:
+                n = len(list(dpath.iterdir()))
+                count = f" ({n} items)"
+            except PermissionError:
+                count = " (access denied)"
+        lines.append(f"- {exists} **`{name}/`**{count} {_tag(who)}")
+        lines.append(f"  {purpose}")
+    lines.append("")
+
+    # --- .env breakdown ---
+    lines.append("---")
+    lines.append("## Environment Variables (.env)")
+    lines.append("")
+    env_path = TIMMY_HOME / ".env"
+    if env_path.exists():
+        for line in env_path.read_text().splitlines():
+            line = line.strip()
+            if not line or line.startswith("#"):
+                continue
+            key = line.split("=", 1)[0]
+            if key in ENV_ANNOTATIONS:
+                purpose, who = ENV_ANNOTATIONS[key]
+                lines.append(f"- **`{key}`** {_tag(who)}")
+                lines.append(f"  {purpose}")
+            else:
+                lines.append(f"- **`{key}`** `[unknown]`")
+                lines.append("  Not documented — investigate")
+    else:
+        lines.append("*No .env file found*")
+    lines.append("")
+
+    # --- config.yaml breakdown ---
+    lines.append("---")
+    lines.append("## Configuration (config.yaml)")
+    lines.append("")
+    for key, (purpose, who) in sorted(CONFIG_ANNOTATIONS.items()):
+        lines.append(f"- **`{key}`** {_tag(who)}")
+        lines.append(f"  {purpose}")
+    lines.append("")
+
+    # --- Model routing ---
+    lines.append("---")
+    lines.append("## Model Routing")
+    lines.append("")
+    lines.append("All auxiliary tasks route to the same local model:")
+    lines.append("")
+    aux_tasks = [
+        "vision", "web_extract", "compression",
+        "session_search", "skills_hub", "mcp", "flush_memories",
+    ]
+    for task in aux_tasks:
+        lines.append(f"- `auxiliary.{task}` → `qwen3:30b` via local Ollama `[hermes-set]`")
+    lines.append("")
+    lines.append("Primary model: `hermes3:latest` via local Ollama `[hermes-set]`")
+    lines.append("")
+
+    # --- What Timmy should audit ---
+    lines.append("---")
+    lines.append("## Audit Checklist")
+    lines.append("")
+    lines.append("Walk through each `[hermes-set]` item above and decide:")
+    lines.append("")
+    lines.append("1. **Do I understand what this does?** If not, ask.")
+    lines.append("2. **Would I choose this myself?** If yes, it becomes `[timmy-chose]`.")
+    lines.append("3. **Would I choose differently?** If yes, change it and own it.")
+    lines.append("4. **Is this serving the mission?** Every setting should serve a purpose.")
+    lines.append("")
+    lines.append("The Workshop is yours. Nothing here should be a mystery.")
+
+    return "\n".join(lines) + "\n"
+
+
+def main() -> None:
+    parser = argparse.ArgumentParser(description="Generate Workshop inventory")
+    parser.add_argument(
+        "--output",
+        type=Path,
+        default=TIMMY_HOME / "WORKSHOP_INVENTORY.md",
+        help="Output path (default: ~/.timmy/WORKSHOP_INVENTORY.md)",
+    )
+    args = parser.parse_args()
+
+    content = generate_inventory()
+    args.output.parent.mkdir(parents=True, exist_ok=True)
+    args.output.write_text(content)
+    print(f"Workshop inventory written to {args.output}")
+    print(f"  {len(content)} chars, {content.count(chr(10))} lines")
+
+
+if __name__ == "__main__":
+    main()

scripts/loop_guard.py

@@ -0,0 +1,271 @@
+#!/usr/bin/env python3
+"""Loop guard — idle detection + exponential backoff for the dev loop.
+
+Checks .loop/queue.json for ready items before spawning hermes.
+When the queue is empty, applies exponential backoff (60s → 600s max)
+instead of burning empty cycles every 3 seconds.
+
+Usage (called by the dev loop before each cycle):
+  python3 scripts/loop_guard.py          # exits 0 if ready, 1 if idle
+  python3 scripts/loop_guard.py --wait   # same, but sleeps the backoff first
+  python3 scripts/loop_guard.py --status # print current idle state
+
+Exit codes:
+  0 — queue has work, proceed with cycle
+  1 — queue empty, idle backoff applied (skip cycle)
+"""
+
+from __future__ import annotations
+
+import json
+import os
+import sys
+import time
+import urllib.request
+from pathlib import Path
+
+REPO_ROOT = Path(__file__).resolve().parent.parent
+QUEUE_FILE = REPO_ROOT / ".loop" / "queue.json"
+IDLE_STATE_FILE = REPO_ROOT / ".loop" / "idle_state.json"
+CYCLE_RESULT_FILE = REPO_ROOT / ".loop" / "cycle_result.json"
+TOKEN_FILE = Path.home() / ".hermes" / "gitea_token"
+
+GITEA_API = os.environ.get("GITEA_API", "http://localhost:3000/api/v1")
+REPO_SLUG = os.environ.get("REPO_SLUG", "rockachopa/Timmy-time-dashboard")
+
+# Default cycle duration in seconds (5 min); stale threshold = 2× this
+CYCLE_DURATION = int(os.environ.get("CYCLE_DURATION", "300"))
+
+# Backoff sequence: 60s, 120s, 240s, 600s max
+BACKOFF_BASE = 60
+BACKOFF_MAX = 600
+BACKOFF_MULTIPLIER = 2
+
+
+def _get_token() -> str:
+    """Read Gitea token from env or file."""
+    token = os.environ.get("GITEA_TOKEN", "").strip()
+    if not token and TOKEN_FILE.exists():
+        token = TOKEN_FILE.read_text().strip()
+    return token
+
+
+def _fetch_open_issue_numbers() -> set[int] | None:
+    """Fetch open issue numbers from Gitea. Returns None on failure."""
+    token = _get_token()
+    if not token:
+        return None
+    try:
+        numbers: set[int] = set()
+        page = 1
+        while True:
+            url = (
+                f"{GITEA_API}/repos/{REPO_SLUG}/issues"
+                f"?state=open&type=issues&limit=50&page={page}"
+            )
+            req = urllib.request.Request(url, headers={
+                "Authorization": f"token {token}",
+                "Accept": "application/json",
+            })
+            with urllib.request.urlopen(req, timeout=10) as resp:
+                data = json.loads(resp.read())
+            if not data:
+                break
+            for issue in data:
+                numbers.add(issue["number"])
+            if len(data) < 50:
+                break
+            page += 1
+        return numbers
+    except Exception:
+        return None
+
+
+def _load_cycle_result() -> dict:
+    """Read cycle_result.json, handling markdown-fenced JSON."""
+    if not CYCLE_RESULT_FILE.exists():
+        return {}
+    try:
+        raw = CYCLE_RESULT_FILE.read_text().strip()
+        if raw.startswith("```"):
+            lines = raw.splitlines()
+            lines = [ln for ln in lines if not ln.startswith("```")]
+            raw = "\n".join(lines)
+        return json.loads(raw)
+    except (json.JSONDecodeError, OSError):
+        return {}
+
+
+def _is_issue_open(issue_number: int) -> bool | None:
+    """Check if a single issue is open. Returns None on API failure."""
+    token = _get_token()
+    if not token:
+        return None
+    try:
+        url = f"{GITEA_API}/repos/{REPO_SLUG}/issues/{issue_number}"
+        req = urllib.request.Request(
+            url,
+            headers={
+                "Authorization": f"token {token}",
+                "Accept": "application/json",
+            },
+        )
+        with urllib.request.urlopen(req, timeout=10) as resp:
+            data = json.loads(resp.read())
+        return data.get("state") == "open"
+    except Exception:
+        return None
+
+
+def validate_cycle_result() -> bool:
+    """Pre-cycle validation: remove stale or invalid cycle_result.json.
+
+    Checks:
+    1. Age — if older than 2× CYCLE_DURATION, delete it.
+    2. Issue — if the referenced issue is closed, delete it.
+
+    Returns True if the file was removed, False otherwise.
+    """
+    if not CYCLE_RESULT_FILE.exists():
+        return False
+
+    # Age check
+    try:
+        age = time.time() - CYCLE_RESULT_FILE.stat().st_mtime
+    except OSError:
+        return False
+    stale_threshold = CYCLE_DURATION * 2
+    if age > stale_threshold:
+        print(
+            f"[loop-guard] cycle_result.json is {int(age)}s old "
+            f"(threshold {stale_threshold}s) — removing stale file"
+        )
+        CYCLE_RESULT_FILE.unlink(missing_ok=True)
+        return True
+
+    # Issue check
+    cr = _load_cycle_result()
+    issue_num = cr.get("issue")
+    if issue_num is not None:
+        try:
+            issue_num = int(issue_num)
+        except (ValueError, TypeError):
+            return False
+        is_open = _is_issue_open(issue_num)
+        if is_open is False:
+            print(
+                f"[loop-guard] cycle_result.json references closed "
+                f"issue #{issue_num} — removing"
+            )
+            CYCLE_RESULT_FILE.unlink(missing_ok=True)
+            return True
+        # is_open is None (API failure) or True — keep file
+
+    return False
+
+
+def load_queue() -> list[dict]:
+    """Load queue.json and return ready items, filtering out closed issues."""
+    if not QUEUE_FILE.exists():
+        return []
+    try:
+        data = json.loads(QUEUE_FILE.read_text())
+        if not isinstance(data, list):
+            return []
+        ready = [item for item in data if item.get("ready")]
+        if not ready:
+            return []
+
+        # Filter out issues that are no longer open (auto-hygiene)
+        open_numbers = _fetch_open_issue_numbers()
+        if open_numbers is not None:
+            before = len(ready)
+            ready = [item for item in ready if item.get("issue") in open_numbers]
+            removed = before - len(ready)
+            if removed > 0:
+                print(f"[loop-guard] Filtered {removed} closed issue(s) from queue")
+                # Persist the cleaned queue so stale entries don't recur
+                _save_cleaned_queue(data, open_numbers)
+        return ready
+    except (json.JSONDecodeError, OSError):
+        return []
+
+
+def _save_cleaned_queue(full_queue: list[dict], open_numbers: set[int]) -> None:
+    """Rewrite queue.json without closed issues."""
+    cleaned = [item for item in full_queue if item.get("issue") in open_numbers]
+    try:
+        QUEUE_FILE.write_text(json.dumps(cleaned, indent=2) + "\n")
+    except OSError:
+        pass
+
+
+def load_idle_state() -> dict:
+    """Load persistent idle state."""
+    if not IDLE_STATE_FILE.exists():
+        return {"consecutive_idle": 0, "last_idle_at": 0}
+    try:
+        return json.loads(IDLE_STATE_FILE.read_text())
+    except (json.JSONDecodeError, OSError):
+        return {"consecutive_idle": 0, "last_idle_at": 0}
+
+
+def save_idle_state(state: dict) -> None:
+    """Persist idle state."""
+    IDLE_STATE_FILE.parent.mkdir(parents=True, exist_ok=True)
+    IDLE_STATE_FILE.write_text(json.dumps(state, indent=2) + "\n")
+
+
+def compute_backoff(consecutive_idle: int) -> int:
+    """Exponential backoff: 60, 120, 240, 600 (capped)."""
+    return min(BACKOFF_BASE * (BACKOFF_MULTIPLIER ** consecutive_idle), BACKOFF_MAX)
+
+
+def main() -> int:
+    wait_mode = "--wait" in sys.argv
+    status_mode = "--status" in sys.argv
+
+    state = load_idle_state()
+
+    if status_mode:
+        ready = load_queue()
+        backoff = compute_backoff(state["consecutive_idle"])
+        print(json.dumps({
+            "queue_ready": len(ready),
+            "consecutive_idle": state["consecutive_idle"],
+            "next_backoff_seconds": backoff if not ready else 0,
+        }, indent=2))
+        return 0
+
+    # Pre-cycle validation: remove stale cycle_result.json
+    validate_cycle_result()
+
+    ready = load_queue()
+
+    if ready:
+        # Queue has work — reset idle state, proceed
+        if state["consecutive_idle"] > 0:
+            print(f"[loop-guard] Queue active ({len(ready)} ready) — "
+                  f"resuming after {state['consecutive_idle']} idle cycles")
+        state["consecutive_idle"] = 0
+        state["last_idle_at"] = 0
+        save_idle_state(state)
+        return 0
+
+    # Queue empty — apply backoff
+    backoff = compute_backoff(state["consecutive_idle"])
+    state["consecutive_idle"] += 1
+    state["last_idle_at"] = time.time()
+    save_idle_state(state)
+
+    print(f"[loop-guard] Queue empty — idle #{state['consecutive_idle']}, "
+          f"backoff {backoff}s")
+
+    if wait_mode:
+        time.sleep(backoff)
+
+    return 1
+
+
+if __name__ == "__main__":
+    sys.exit(main())

scripts/loop_introspect.py

@@ -0,0 +1,407 @@
+#!/usr/bin/env python3
+"""Loop introspection — the self-improvement engine.
+
+Analyzes retro data across time windows to detect trends, extract patterns,
+and produce structured recommendations. Output is consumed by deep_triage
+and injected into the loop prompt context.
+
+This is the piece that closes the feedback loop:
+  cycle_retro → introspect → deep_triage → loop behavior changes
+
+Run:  python3 scripts/loop_introspect.py
+Output: .loop/retro/insights.json (structured insights + recommendations)
+        Prints human-readable summary to stdout.
+
+Called by: deep_triage.sh (before the LLM triage), timmy-loop.sh (every 50 cycles)
+"""
+
+from __future__ import annotations
+
+import json
+import sys
+from collections import defaultdict
+from datetime import datetime, timezone, timedelta
+from pathlib import Path
+
+REPO_ROOT = Path(__file__).resolve().parent.parent
+CYCLES_FILE = REPO_ROOT / ".loop" / "retro" / "cycles.jsonl"
+DEEP_TRIAGE_FILE = REPO_ROOT / ".loop" / "retro" / "deep-triage.jsonl"
+TRIAGE_FILE = REPO_ROOT / ".loop" / "retro" / "triage.jsonl"
+QUARANTINE_FILE = REPO_ROOT / ".loop" / "quarantine.json"
+INSIGHTS_FILE = REPO_ROOT / ".loop" / "retro" / "insights.json"
+
+# ── Helpers ──────────────────────────────────────────────────────────────
+
+def load_jsonl(path: Path) -> list[dict]:
+    """Load a JSONL file, skipping bad lines."""
+    if not path.exists():
+        return []
+    entries = []
+    for line in path.read_text().strip().splitlines():
+        try:
+            entries.append(json.loads(line))
+        except (json.JSONDecodeError, ValueError):
+            continue
+    return entries
+
+
+def parse_ts(ts_str: str) -> datetime | None:
+    """Parse an ISO timestamp, tolerating missing tz."""
+    if not ts_str:
+        return None
+    try:
+        dt = datetime.fromisoformat(ts_str.replace("Z", "+00:00"))
+        if dt.tzinfo is None:
+            dt = dt.replace(tzinfo=timezone.utc)
+        return dt
+    except (ValueError, TypeError):
+        return None
+
+
+def window(entries: list[dict], days: int) -> list[dict]:
+    """Filter entries to the last N days."""
+    cutoff = datetime.now(timezone.utc) - timedelta(days=days)
+    result = []
+    for e in entries:
+        ts = parse_ts(e.get("timestamp", ""))
+        if ts and ts >= cutoff:
+            result.append(e)
+    return result
+
+
+# ── Analysis functions ───────────────────────────────────────────────────
+
+def compute_trends(cycles: list[dict]) -> dict:
+    """Compare recent window (last 7d) vs older window (7-14d ago)."""
+    recent = window(cycles, 7)
+    older = window(cycles, 14)
+    # Remove recent from older to get the 7-14d window
+    recent_set = {(e.get("cycle"), e.get("timestamp")) for e in recent}
+    older = [e for e in older if (e.get("cycle"), e.get("timestamp")) not in recent_set]
+
+    def stats(entries):
+        if not entries:
+            return {"count": 0, "success_rate": None, "avg_duration": None,
+                    "lines_net": 0, "prs_merged": 0}
+        successes = sum(1 for e in entries if e.get("success"))
+        durations = [e["duration"] for e in entries if e.get("duration", 0) > 0]
+        return {
+            "count": len(entries),
+            "success_rate": round(successes / len(entries), 3) if entries else None,
+            "avg_duration": round(sum(durations) / len(durations)) if durations else None,
+            "lines_net": sum(e.get("lines_added", 0) - e.get("lines_removed", 0) for e in entries),
+            "prs_merged": sum(1 for e in entries if e.get("pr")),
+        }
+
+    recent_stats = stats(recent)
+    older_stats = stats(older)
+
+    trend = {
+        "recent_7d": recent_stats,
+        "previous_7d": older_stats,
+        "velocity_change": None,
+        "success_rate_change": None,
+        "duration_change": None,
+    }
+
+    if recent_stats["count"] and older_stats["count"]:
+        trend["velocity_change"] = recent_stats["count"] - older_stats["count"]
+    if recent_stats["success_rate"] is not None and older_stats["success_rate"] is not None:
+        trend["success_rate_change"] = round(
+            recent_stats["success_rate"] - older_stats["success_rate"], 3
+        )
+    if recent_stats["avg_duration"] is not None and older_stats["avg_duration"] is not None:
+        trend["duration_change"] = recent_stats["avg_duration"] - older_stats["avg_duration"]
+
+    return trend
+
+
+def type_analysis(cycles: list[dict]) -> dict:
+    """Per-type success rates and durations."""
+    by_type: dict[str, list[dict]] = defaultdict(list)
+    for c in cycles:
+        by_type[c.get("type", "unknown")].append(c)
+
+    result = {}
+    for t, entries in by_type.items():
+        durations = [e["duration"] for e in entries if e.get("duration", 0) > 0]
+        successes = sum(1 for e in entries if e.get("success"))
+        result[t] = {
+            "count": len(entries),
+            "success_rate": round(successes / len(entries), 3) if entries else 0,
+            "avg_duration": round(sum(durations) / len(durations)) if durations else 0,
+            "max_duration": max(durations) if durations else 0,
+        }
+    return result
+
+
+def repeat_failures(cycles: list[dict]) -> list[dict]:
+    """Issues that have failed multiple times — quarantine candidates."""
+    failures: dict[int, list] = defaultdict(list)
+    for c in cycles:
+        if not c.get("success") and c.get("issue"):
+            failures[c["issue"]].append({
+                "cycle": c.get("cycle"),
+                "reason": c.get("reason", ""),
+                "duration": c.get("duration", 0),
+            })
+    # Only issues with 2+ failures
+    return [
+        {"issue": k, "failure_count": len(v), "attempts": v}
+        for k, v in sorted(failures.items(), key=lambda x: -len(x[1]))
+        if len(v) >= 2
+    ]
+
+
+def duration_outliers(cycles: list[dict], threshold_multiple: float = 3.0) -> list[dict]:
+    """Cycles that took way longer than average — something went wrong."""
+    durations = [c["duration"] for c in cycles if c.get("duration", 0) > 0]
+    if len(durations) < 5:
+        return []
+    avg = sum(durations) / len(durations)
+    threshold = avg * threshold_multiple
+
+    outliers = []
+    for c in cycles:
+        dur = c.get("duration", 0)
+        if dur > threshold:
+            outliers.append({
+                "cycle": c.get("cycle"),
+                "issue": c.get("issue"),
+                "type": c.get("type"),
+                "duration": dur,
+                "avg_duration": round(avg),
+                "multiple": round(dur / avg, 1) if avg > 0 else 0,
+                "reason": c.get("reason", ""),
+            })
+    return outliers
+
+
+def triage_effectiveness(deep_triages: list[dict]) -> dict:
+    """How well is the deep triage performing?"""
+    if not deep_triages:
+        return {"runs": 0, "note": "No deep triage data yet"}
+
+    total_reviewed = sum(d.get("issues_reviewed", 0) for d in deep_triages)
+    total_refined = sum(len(d.get("issues_refined", [])) for d in deep_triages)
+    total_created = sum(len(d.get("issues_created", [])) for d in deep_triages)
+    total_closed = sum(len(d.get("issues_closed", [])) for d in deep_triages)
+    timmy_available = sum(1 for d in deep_triages if d.get("timmy_available"))
+
+    # Extract Timmy's feedback themes
+    timmy_themes = []
+    for d in deep_triages:
+        fb = d.get("timmy_feedback", "")
+        if fb:
+            timmy_themes.append(fb[:200])
+
+    return {
+        "runs": len(deep_triages),
+        "total_reviewed": total_reviewed,
+        "total_refined": total_refined,
+        "total_created": total_created,
+        "total_closed": total_closed,
+        "timmy_consultation_rate": round(timmy_available / len(deep_triages), 2),
+        "timmy_recent_feedback": timmy_themes[-1] if timmy_themes else "",
+        "timmy_feedback_history": timmy_themes,
+    }
+
+
+def generate_recommendations(
+    trends: dict,
+    types: dict,
+    repeats: list,
+    outliers: list,
+    triage_eff: dict,
+) -> list[dict]:
+    """Produce actionable recommendations from the analysis."""
+    recs = []
+
+    # 1. Success rate declining?
+    src = trends.get("success_rate_change")
+    if src is not None and src < -0.1:
+        recs.append({
+            "severity": "high",
+            "category": "reliability",
+            "finding": f"Success rate dropped {abs(src)*100:.0f}pp in the last 7 days",
+            "recommendation": "Review recent failures. Are issues poorly scoped? "
+                              "Is main unstable? Check if triage is producing bad work items.",
+        })
+
+    # 2. Velocity dropping?
+    vc = trends.get("velocity_change")
+    if vc is not None and vc < -5:
+        recs.append({
+            "severity": "medium",
+            "category": "throughput",
+            "finding": f"Velocity dropped by {abs(vc)} cycles vs previous week",
+            "recommendation": "Check for loop stalls, long-running cycles, or queue starvation.",
+        })
+
+    # 3. Duration creep?
+    dc = trends.get("duration_change")
+    if dc is not None and dc > 120:  # 2+ minutes longer
+        recs.append({
+            "severity": "medium",
+            "category": "efficiency",
+            "finding": f"Average cycle duration increased by {dc}s vs previous week",
+            "recommendation": "Issues may be growing in scope. Enforce tighter decomposition "
+                              "in deep triage. Check if tests are getting slower.",
+        })
+
+    # 4. Type-specific problems
+    for t, info in types.items():
+        if info["count"] >= 3 and info["success_rate"] < 0.5:
+            recs.append({
+                "severity": "high",
+                "category": "type_reliability",
+                "finding": f"'{t}' issues fail {(1-info['success_rate'])*100:.0f}% of the time "
+                           f"({info['count']} attempts)",
+                "recommendation": f"'{t}' issues need better scoping or different approach. "
+                                  f"Consider: tighter acceptance criteria, smaller scope, "
+                                  f"or delegating to Kimi with more context.",
+            })
+        if info["avg_duration"] > 600 and info["count"] >= 3:  # >10 min avg
+            recs.append({
+                "severity": "medium",
+                "category": "type_efficiency",
+                "finding": f"'{t}' issues average {info['avg_duration']//60}m{info['avg_duration']%60}s "
+                           f"(max {info['max_duration']//60}m)",
+                "recommendation": f"Break '{t}' issues into smaller pieces. Target <5 min per cycle.",
+            })
+
+    # 5. Repeat failures
+    for rf in repeats[:3]:
+        recs.append({
+            "severity": "high",
+            "category": "repeat_failure",
+            "finding": f"Issue #{rf['issue']} has failed {rf['failure_count']} times",
+            "recommendation": "Quarantine or rewrite this issue. Repeated failure = "
+                              "bad scope or missing prerequisite.",
+        })
+
+    # 6. Outliers
+    if len(outliers) > 2:
+        recs.append({
+            "severity": "medium",
+            "category": "outliers",
+            "finding": f"{len(outliers)} cycles took {outliers[0].get('multiple', '?')}x+ "
+                       f"longer than average",
+            "recommendation": "Long cycles waste resources. Add timeout enforcement or "
+                              "break complex issues earlier.",
+        })
+
+    # 7. Code growth
+    recent = trends.get("recent_7d", {})
+    net = recent.get("lines_net", 0)
+    if net > 500:
+        recs.append({
+            "severity": "low",
+            "category": "code_health",
+            "finding": f"Net +{net} lines added in the last 7 days",
+            "recommendation": "Lines of code is a liability. Balance feature work with "
+                              "refactoring. Target net-zero or negative line growth.",
+        })
+
+    # 8. Triage health
+    if triage_eff.get("runs", 0) == 0:
+        recs.append({
+            "severity": "high",
+            "category": "triage",
+            "finding": "Deep triage has never run",
+            "recommendation": "Enable deep triage (every 20 cycles). The loop needs "
+                              "LLM-driven issue refinement to stay effective.",
+        })
+
+    # No recommendations = things are healthy
+    if not recs:
+        recs.append({
+            "severity": "info",
+            "category": "health",
+            "finding": "No significant issues detected",
+            "recommendation": "System is healthy. Continue current patterns.",
+        })
+
+    return recs
+
+
+# ── Main ─────────────────────────────────────────────────────────────────
+
+def main() -> None:
+    cycles = load_jsonl(CYCLES_FILE)
+    deep_triages = load_jsonl(DEEP_TRIAGE_FILE)
+
+    if not cycles:
+        print("[introspect] No cycle data found. Nothing to analyze.")
+        return
+
+    # Run all analyses
+    trends = compute_trends(cycles)
+    types = type_analysis(cycles)
+    repeats = repeat_failures(cycles)
+    outliers = duration_outliers(cycles)
+    triage_eff = triage_effectiveness(deep_triages)
+    recommendations = generate_recommendations(trends, types, repeats, outliers, triage_eff)
+
+    insights = {
+        "generated_at": datetime.now(timezone.utc).isoformat(),
+        "total_cycles_analyzed": len(cycles),
+        "trends": trends,
+        "by_type": types,
+        "repeat_failures": repeats[:5],
+        "duration_outliers": outliers[:5],
+        "triage_effectiveness": triage_eff,
+        "recommendations": recommendations,
+    }
+
+    # Write insights
+    INSIGHTS_FILE.parent.mkdir(parents=True, exist_ok=True)
+    INSIGHTS_FILE.write_text(json.dumps(insights, indent=2) + "\n")
+
+    # Current epoch from latest entry
+    latest_epoch = ""
+    for c in reversed(cycles):
+        if c.get("epoch"):
+            latest_epoch = c["epoch"]
+            break
+
+    # Human-readable output
+    header = f"[introspect] Analyzed {len(cycles)} cycles"
+    if latest_epoch:
+        header += f"  ·  current epoch: {latest_epoch}"
+    print(header)
+
+    print(f"\n  TRENDS (7d vs previous 7d):")
+    r7 = trends["recent_7d"]
+    p7 = trends["previous_7d"]
+    print(f"    Cycles:       {r7['count']:>3d}  (was {p7['count']})")
+    if r7["success_rate"] is not None:
+        arrow = "↑" if (trends["success_rate_change"] or 0) > 0 else "↓" if (trends["success_rate_change"] or 0) < 0 else "→"
+        print(f"    Success rate: {r7['success_rate']*100:>4.0f}%  {arrow}")
+    if r7["avg_duration"] is not None:
+        print(f"    Avg duration: {r7['avg_duration']//60}m{r7['avg_duration']%60:02d}s")
+    print(f"    PRs merged:   {r7['prs_merged']:>3d}  (was {p7['prs_merged']})")
+    print(f"    Lines net:    {r7['lines_net']:>+5d}")
+
+    print(f"\n  BY TYPE:")
+    for t, info in sorted(types.items(), key=lambda x: -x[1]["count"]):
+        print(f"    {t:12s}  n={info['count']:>2d}  "
+              f"ok={info['success_rate']*100:>3.0f}%  "
+              f"avg={info['avg_duration']//60}m{info['avg_duration']%60:02d}s")
+
+    if repeats:
+        print(f"\n  REPEAT FAILURES:")
+        for rf in repeats[:3]:
+            print(f"    #{rf['issue']}  failed {rf['failure_count']}x")
+
+    print(f"\n  RECOMMENDATIONS ({len(recommendations)}):")
+    for i, rec in enumerate(recommendations, 1):
+        sev = {"high": "🔴", "medium": "🟡", "low": "🟢", "info": "ℹ️ "}.get(rec["severity"], "?")
+        print(f"    {sev} {rec['finding']}")
+        print(f"       → {rec['recommendation']}")
+
+    print(f"\n  Written to: {INSIGHTS_FILE}")
+
+
+if __name__ == "__main__":
+    main()

src/config.py

@@ -10,6 +10,11 @@ from pydantic_settings import BaseSettings, SettingsConfigDict
 APP_START_TIME: _datetime = _datetime.now(UTC)
 
 
+def normalize_ollama_url(url: str) -> str:
+    """Replace localhost with 127.0.0.1 to avoid IPv6 resolution delays."""
+    return url.replace("localhost", "127.0.0.1")
+
+
 class Settings(BaseSettings):
     """Central configuration — all env-var access goes through this class."""
 
@@ -19,6 +24,11 @@ class Settings(BaseSettings):
     # Ollama host — override with OLLAMA_URL env var or .env file
     ollama_url: str = "http://localhost:11434"
 
+    @property
+    def normalized_ollama_url(self) -> str:
+        """Return ollama_url with localhost replaced by 127.0.0.1."""
+        return normalize_ollama_url(self.ollama_url)
+
     # LLM model passed to Agno/Ollama — override with OLLAMA_MODEL
     # qwen3:30b is the primary model — better reasoning and tool calling
     # than llama3.1:8b-instruct while still running locally on modest hardware.
@@ -64,23 +74,17 @@ class Settings(BaseSettings):
     # Seconds to wait for user confirmation before auto-rejecting.
     discord_confirm_timeout: int = 120
 
-    # ── AirLLM / backend selection ───────────────────────────────────────────
+    # ── Backend selection ────────────────────────────────────────────────────
     # "ollama"  — always use Ollama (default, safe everywhere)
-    # "airllm"  — always use AirLLM (requires pip install ".[bigbrain]")
-    # "auto"    — use AirLLM on Apple Silicon if airllm is installed,
-    #             fall back to Ollama otherwise
-    timmy_model_backend: Literal["ollama", "airllm", "grok", "claude", "auto"] = "ollama"
-
-    # AirLLM model size when backend is airllm or auto.
-    # Larger = smarter, but needs more RAM / disk.
-    # 8b  ~16 GB  |  70b  ~140 GB  |  405b  ~810 GB
-    airllm_model_size: Literal["8b", "70b", "405b"] = "70b"
+    # "auto"    — pick best available local backend, fall back to Ollama
+    timmy_model_backend: Literal["ollama", "grok", "claude", "auto"] = "ollama"
 
     # ── Grok (xAI) — opt-in premium cloud backend ────────────────────────
     # Grok is a premium augmentation layer — local-first ethos preserved.
     # Only used when explicitly enabled and query complexity warrants it.
     grok_enabled: bool = False
     xai_api_key: str = ""
+    xai_base_url: str = "https://api.x.ai/v1"
     grok_default_model: str = "grok-3-fast"
     grok_max_sats_per_query: int = 200
     grok_free: bool = False  # Skip Lightning invoice when user has own API key
@@ -138,7 +142,24 @@ class Settings(BaseSettings):
 
     # CORS allowed origins for the web chat interface (Gitea Pages, etc.)
     # Set CORS_ORIGINS as a comma-separated list, e.g. "http://localhost:3000,https://example.com"
-    cors_origins: list[str] = ["*"]
+    cors_origins: list[str] = [
+        "http://localhost:3000",
+        "http://localhost:8000",
+        "http://127.0.0.1:3000",
+        "http://127.0.0.1:8000",
+    ]
+
+    # ── Matrix Frontend Integration ────────────────────────────────────────
+    # URL of the Matrix frontend (Replit/Tailscale) for CORS.
+    # When set, this origin is added to CORS allowed_origins.
+    # Example: "http://100.124.176.28:8080" or "https://alexanderwhitestone.com"
+    matrix_frontend_url: str = ""  # Empty = disabled
+
+    # WebSocket authentication token for Matrix connections.
+    # When set, clients must provide this token via ?token= query param
+    # or in the first message as {"type": "auth", "token": "..."}.
+    # Empty/unset = auth disabled (dev mode).
+    matrix_ws_token: str = ""
 
     # Trusted hosts for the Host header check (TrustedHostMiddleware).
     # Set TRUSTED_HOSTS as a comma-separated list. Wildcards supported (e.g. "*.ts.net").
@@ -238,12 +259,19 @@ class Settings(BaseSettings):
     # Fallback to server when browser model is unavailable or too slow.
     browser_model_fallback: bool = True
 
+    # ── Deep Focus Mode ─────────────────────────────────────────────
+    # "deep" = single-problem context; "broad" = default multi-task.
+    focus_mode: Literal["deep", "broad"] = "broad"
+
     # ── Default Thinking ──────────────────────────────────────────────
     # When enabled, the agent starts an internal thought loop on server start.
     thinking_enabled: bool = True
     thinking_interval_seconds: int = 300  # 5 minutes between thoughts
+    thinking_timeout_seconds: int = 120  # max wall-clock time per thinking cycle
     thinking_distill_every: int = 10  # distill facts from thoughts every Nth thought
     thinking_issue_every: int = 20  # file Gitea issues from thoughts every Nth thought
+    thinking_memory_check_every: int = 50  # check memory status every Nth thought
+    thinking_idle_timeout_minutes: int = 60  # pause thoughts after N minutes without user input
 
     # ── Gitea Integration ─────────────────────────────────────────────
     # Local Gitea instance for issue tracking and self-improvement.
@@ -302,6 +330,13 @@ class Settings(BaseSettings):
     autoresearch_max_iterations: int = 100
     autoresearch_metric: str = "val_bpb"  # metric to optimise (lower = better)
 
+    # ── Weekly Narrative Summary ───────────────────────────────────────
+    # Generates a human-readable weekly summary of development activity.
+    # Disabling this will stop the weekly narrative generation.
+    weekly_narrative_enabled: bool = True
+    weekly_narrative_lookback_days: int = 7
+    weekly_narrative_output_dir: str = ".loop"
+
     # ── Local Hands (Shell + Git) ──────────────────────────────────────
     # Enable local shell/git execution hands.
     hands_shell_enabled: bool = True
@@ -388,7 +423,7 @@ def check_ollama_model_available(model_name: str) -> bool:
         import json
         import urllib.request
 
-        url = settings.ollama_url.replace("localhost", "127.0.0.1")
+        url = settings.normalized_ollama_url
         req = urllib.request.Request(
             f"{url}/api/tags",
             method="GET",
@@ -465,8 +500,19 @@ def validate_startup(*, force: bool = False) -> None:
                 ", ".join(_missing),
             )
             sys.exit(1)
+        if "*" in settings.cors_origins:
+            _startup_logger.error(
+                "PRODUCTION SECURITY ERROR: CORS wildcard '*' is not allowed "
+                "in production. Set CORS_ORIGINS to explicit origins."
+            )
+            sys.exit(1)
         _startup_logger.info("Production mode: security secrets validated ✓")
     else:
+        if "*" in settings.cors_origins:
+            _startup_logger.warning(
+                "SEC: CORS_ORIGINS contains wildcard '*' — "
+                "restrict to explicit origins before deploying to production."
+            )
         if not settings.l402_hmac_secret:
             _startup_logger.warning(
                 "SEC: L402_HMAC_SECRET is not set — "

src/dashboard/app.py

@@ -8,7 +8,9 @@ Key improvements:
 """
 
 import asyncio
+import json
 import logging
+import re
 from contextlib import asynccontextmanager
 from pathlib import Path
 
@@ -22,12 +24,15 @@ from config import settings
 
 # Import dedicated middleware
 from dashboard.middleware.csrf import CSRFMiddleware
+from dashboard.middleware.rate_limit import RateLimitMiddleware
 from dashboard.middleware.request_logging import RequestLoggingMiddleware
 from dashboard.middleware.security_headers import SecurityHeadersMiddleware
 from dashboard.routes.agents import router as agents_router
 from dashboard.routes.briefing import router as briefing_router
 from dashboard.routes.calm import router as calm_router
 from dashboard.routes.chat_api import router as chat_api_router
+from dashboard.routes.chat_api_v1 import router as chat_api_v1_router
+from dashboard.routes.daily_run import router as daily_run_router
 from dashboard.routes.db_explorer import router as db_explorer_router
 from dashboard.routes.discord import router as discord_router
 from dashboard.routes.experiments import router as experiments_router
@@ -38,14 +43,19 @@ from dashboard.routes.memory import router as memory_router
 from dashboard.routes.mobile import router as mobile_router
 from dashboard.routes.models import api_router as models_api_router
 from dashboard.routes.models import router as models_router
+from dashboard.routes.quests import router as quests_router
 from dashboard.routes.spark import router as spark_router
 from dashboard.routes.system import router as system_router
 from dashboard.routes.tasks import router as tasks_router
 from dashboard.routes.telegram import router as telegram_router
 from dashboard.routes.thinking import router as thinking_router
 from dashboard.routes.tools import router as tools_router
+from dashboard.routes.tower import router as tower_router
 from dashboard.routes.voice import router as voice_router
 from dashboard.routes.work_orders import router as work_orders_router
+from dashboard.routes.world import matrix_router
+from dashboard.routes.world import router as world_router
+from timmy.workshop_state import PRESENCE_FILE
 
 
 class _ColorFormatter(logging.Formatter):
@@ -151,7 +161,17 @@ async def _thinking_scheduler() -> None:
     while True:
         try:
             if settings.thinking_enabled:
-                await thinking_engine.think_once()
+                await asyncio.wait_for(
+                    thinking_engine.think_once(),
+                    timeout=settings.thinking_timeout_seconds,
+                )
+        except TimeoutError:
+            logger.warning(
+                "Thinking cycle timed out after %ds — Ollama may be unresponsive",
+                settings.thinking_timeout_seconds,
+            )
+        except asyncio.CancelledError:
+            raise
         except Exception as exc:
             logger.error("Thinking scheduler error: %s", exc)
 
@@ -171,7 +191,10 @@ async def _loop_qa_scheduler() -> None:
     while True:
         try:
             if settings.loop_qa_enabled:
-                result = await loop_qa_orchestrator.run_next_test()
+                result = await asyncio.wait_for(
+                    loop_qa_orchestrator.run_next_test(),
+                    timeout=settings.thinking_timeout_seconds,
+                )
                 if result:
                     status = "PASS" if result["success"] else "FAIL"
                     logger.info(
@@ -180,6 +203,13 @@ async def _loop_qa_scheduler() -> None:
                         status,
                         result.get("details", "")[:80],
                     )
+        except TimeoutError:
+            logger.warning(
+                "Loop QA test timed out after %ds",
+                settings.thinking_timeout_seconds,
+            )
+        except asyncio.CancelledError:
+            raise
         except Exception as exc:
             logger.error("Loop QA scheduler error: %s", exc)
 
@@ -187,6 +217,54 @@ async def _loop_qa_scheduler() -> None:
         await asyncio.sleep(interval)
 
 
+_PRESENCE_POLL_SECONDS = 30
+_PRESENCE_INITIAL_DELAY = 3
+
+_SYNTHESIZED_STATE: dict = {
+    "version": 1,
+    "liveness": None,
+    "current_focus": "",
+    "mood": "idle",
+    "active_threads": [],
+    "recent_events": [],
+    "concerns": [],
+}
+
+
+async def _presence_watcher() -> None:
+    """Background task: watch ~/.timmy/presence.json and broadcast changes via WS.
+
+    Polls the file every 30 seconds (matching Timmy's write cadence).
+    If the file doesn't exist, broadcasts a synthesised idle state.
+    """
+    from infrastructure.ws_manager.handler import ws_manager as ws_mgr
+
+    await asyncio.sleep(_PRESENCE_INITIAL_DELAY)  # Stagger after other schedulers
+
+    last_mtime: float = 0.0
+
+    while True:
+        try:
+            if PRESENCE_FILE.exists():
+                mtime = PRESENCE_FILE.stat().st_mtime
+                if mtime != last_mtime:
+                    last_mtime = mtime
+                    raw = await asyncio.to_thread(PRESENCE_FILE.read_text)
+                    state = json.loads(raw)
+                    await ws_mgr.broadcast("timmy_state", state)
+            else:
+                # File absent — broadcast synthesised state once per cycle
+                if last_mtime != -1.0:
+                    last_mtime = -1.0
+                    await ws_mgr.broadcast("timmy_state", _SYNTHESIZED_STATE)
+        except json.JSONDecodeError as exc:
+            logger.warning("presence.json parse error: %s", exc)
+        except Exception as exc:
+            logger.warning("Presence watcher error: %s", exc)
+
+        await asyncio.sleep(_PRESENCE_POLL_SECONDS)
+
+
 async def _start_chat_integrations_background() -> None:
     """Background task: start chat integrations without blocking startup."""
     from integrations.chat_bridge.registry import platform_registry
@@ -277,125 +355,118 @@ async def _discord_token_watcher() -> None:
                 logger.warning("Discord auto-start failed: %s", exc)
 
 
-@asynccontextmanager
-async def lifespan(app: FastAPI):
-    """Application lifespan manager with non-blocking startup."""
-
-    # Validate security config (no-op in test mode)
+def _startup_init() -> None:
+    """Validate config and enable event persistence."""
     from config import validate_startup
 
     validate_startup()
 
-    # Enable event persistence (unified EventBus + swarm event_log)
     from infrastructure.events.bus import init_event_bus_persistence
 
     init_event_bus_persistence()
 
-    # Create all background tasks without waiting for them
-    briefing_task = asyncio.create_task(_briefing_scheduler())
-    thinking_task = asyncio.create_task(_thinking_scheduler())
-    loop_qa_task = asyncio.create_task(_loop_qa_scheduler())
-
-    # Initialize Spark Intelligence engine
     from spark.engine import get_spark_engine
 
     if get_spark_engine().enabled:
         logger.info("Spark Intelligence active — event capture enabled")
 
-    # Auto-prune old vector store memories on startup
-    if settings.memory_prune_days > 0:
-        try:
-            from timmy.memory_system import prune_memories
 
-            pruned = prune_memories(
+def _startup_background_tasks() -> list[asyncio.Task]:
+    """Spawn all recurring background tasks (non-blocking)."""
+    return [
+        asyncio.create_task(_briefing_scheduler()),
+        asyncio.create_task(_thinking_scheduler()),
+        asyncio.create_task(_loop_qa_scheduler()),
+        asyncio.create_task(_presence_watcher()),
+        asyncio.create_task(_start_chat_integrations_background()),
+    ]
+
+
+def _try_prune(label: str, prune_fn, days: int) -> None:
+    """Run a prune function, log results, swallow errors."""
+    try:
+        pruned = prune_fn()
+        if pruned:
+            logger.info(
+                "%s auto-prune: removed %d entries older than %d days",
+                label,
+                pruned,
+                days,
+            )
+    except Exception as exc:
+        logger.debug("%s auto-prune skipped: %s", label, exc)
+
+
+def _check_vault_size() -> None:
+    """Warn if the memory vault exceeds the configured size limit."""
+    try:
+        vault_path = Path(settings.repo_root) / "memory" / "notes"
+        if vault_path.exists():
+            total_bytes = sum(f.stat().st_size for f in vault_path.rglob("*") if f.is_file())
+            total_mb = total_bytes / (1024 * 1024)
+            if total_mb > settings.memory_vault_max_mb:
+                logger.warning(
+                    "Memory vault (%.1f MB) exceeds limit (%d MB) — consider archiving old notes",
+                    total_mb,
+                    settings.memory_vault_max_mb,
+                )
+    except Exception as exc:
+        logger.debug("Vault size check skipped: %s", exc)
+
+
+def _startup_pruning() -> None:
+    """Auto-prune old memories, thoughts, and events on startup."""
+    if settings.memory_prune_days > 0:
+        from timmy.memory_system import prune_memories
+
+        _try_prune(
+            "Memory",
+            lambda: prune_memories(
                 older_than_days=settings.memory_prune_days,
                 keep_facts=settings.memory_prune_keep_facts,
-            )
-            if pruned:
-                logger.info(
-                    "Memory auto-prune: removed %d entries older than %d days",
-                    pruned,
-                    settings.memory_prune_days,
-                )
-        except Exception as exc:
-            logger.debug("Memory auto-prune skipped: %s", exc)
+            ),
+            settings.memory_prune_days,
+        )
 
-    # Auto-prune old thoughts on startup
     if settings.thoughts_prune_days > 0:
-        try:
-            from timmy.thinking import thinking_engine
+        from timmy.thinking import thinking_engine
 
-            pruned = thinking_engine.prune_old_thoughts(
+        _try_prune(
+            "Thought",
+            lambda: thinking_engine.prune_old_thoughts(
                 keep_days=settings.thoughts_prune_days,
                 keep_min=settings.thoughts_prune_keep_min,
-            )
-            if pruned:
-                logger.info(
-                    "Thought auto-prune: removed %d entries older than %d days",
-                    pruned,
-                    settings.thoughts_prune_days,
-                )
-        except Exception as exc:
-            logger.debug("Thought auto-prune skipped: %s", exc)
+            ),
+            settings.thoughts_prune_days,
+        )
 
-    # Auto-prune old system events on startup
     if settings.events_prune_days > 0:
-        try:
-            from swarm.event_log import prune_old_events
+        from swarm.event_log import prune_old_events
 
-            pruned = prune_old_events(
+        _try_prune(
+            "Event",
+            lambda: prune_old_events(
                 keep_days=settings.events_prune_days,
                 keep_min=settings.events_prune_keep_min,
-            )
-            if pruned:
-                logger.info(
-                    "Event auto-prune: removed %d entries older than %d days",
-                    pruned,
-                    settings.events_prune_days,
-                )
-        except Exception as exc:
-            logger.debug("Event auto-prune skipped: %s", exc)
+            ),
+            settings.events_prune_days,
+        )
 
-    # Warn if memory vault exceeds size limit
     if settings.memory_vault_max_mb > 0:
-        try:
-            vault_path = Path(settings.repo_root) / "memory" / "notes"
-            if vault_path.exists():
-                total_bytes = sum(f.stat().st_size for f in vault_path.rglob("*") if f.is_file())
-                total_mb = total_bytes / (1024 * 1024)
-                if total_mb > settings.memory_vault_max_mb:
-                    logger.warning(
-                        "Memory vault (%.1f MB) exceeds limit (%d MB) — consider archiving old notes",
-                        total_mb,
-                        settings.memory_vault_max_mb,
-                    )
-        except Exception as exc:
-            logger.debug("Vault size check skipped: %s", exc)
+        _check_vault_size()
 
-    # Start chat integrations in background
-    chat_task = asyncio.create_task(_start_chat_integrations_background())
 
-    # Register session logger with error capture (breaks infrastructure → timmy circular dep)
-    try:
-        from infrastructure.error_capture import register_error_recorder
-        from timmy.session_logger import get_session_logger
-
-        register_error_recorder(get_session_logger().record_error)
-    except Exception:
-        pass
-
-    logger.info("✓ Dashboard ready for requests")
-
-    yield
-
-    # Cleanup on shutdown
+async def _shutdown_cleanup(
+    bg_tasks: list[asyncio.Task],
+    workshop_heartbeat,
+) -> None:
+    """Stop chat bots, MCP sessions, heartbeat, and cancel background tasks."""
     from integrations.chat_bridge.vendors.discord import discord_bot
     from integrations.telegram_bot.bot import telegram_bot
 
     await discord_bot.stop()
     await telegram_bot.stop()
 
-    # Close MCP tool server sessions
     try:
         from timmy.mcp_tools import close_mcp_sessions
 
@@ -403,13 +474,44 @@ async def lifespan(app: FastAPI):
     except Exception as exc:
         logger.debug("MCP shutdown: %s", exc)
 
-    for task in [briefing_task, thinking_task, chat_task, loop_qa_task]:
-        if task:
-            task.cancel()
-            try:
-                await task
-            except asyncio.CancelledError:
-                pass
+    await workshop_heartbeat.stop()
+
+    for task in bg_tasks:
+        task.cancel()
+        try:
+            await task
+        except asyncio.CancelledError:
+            pass
+
+
+@asynccontextmanager
+async def lifespan(app: FastAPI):
+    """Application lifespan manager with non-blocking startup."""
+    _startup_init()
+    bg_tasks = _startup_background_tasks()
+    _startup_pruning()
+
+    # Start Workshop presence heartbeat with WS relay
+    from dashboard.routes.world import broadcast_world_state
+    from timmy.workshop_state import WorkshopHeartbeat
+
+    workshop_heartbeat = WorkshopHeartbeat(on_change=broadcast_world_state)
+    await workshop_heartbeat.start()
+
+    # Register session logger with error capture
+    try:
+        from infrastructure.error_capture import register_error_recorder
+        from timmy.session_logger import get_session_logger
+
+        register_error_recorder(get_session_logger().record_error)
+    except Exception:
+        logger.debug("Failed to register error recorder")
+
+    logger.info("✓ Dashboard ready for requests")
+
+    yield
+
+    await _shutdown_cleanup(bg_tasks, workshop_heartbeat)
 
 
 app = FastAPI(
@@ -422,26 +524,55 @@ app = FastAPI(
 
 
 def _get_cors_origins() -> list[str]:
-    """Get CORS origins from settings, with sensible defaults."""
-    origins = settings.cors_origins
-    if settings.debug and origins == ["*"]:
-        return [
-            "http://localhost:3000",
-            "http://localhost:8000",
-            "http://127.0.0.1:3000",
-            "http://127.0.0.1:8000",
-        ]
+    """Get CORS origins from settings, rejecting wildcards in production.
+
+    Adds matrix_frontend_url when configured. Always allows Tailscale IPs
+    (100.x.x.x range) for development convenience.
+    """
+    origins = list(settings.cors_origins)
+
+    # Strip wildcards in production (security)
+    if "*" in origins and not settings.debug:
+        logger.warning(
+            "Wildcard '*' in CORS_ORIGINS stripped in production — "
+            "set explicit origins via CORS_ORIGINS env var"
+        )
+        origins = [o for o in origins if o != "*"]
+
+    # Add Matrix frontend URL if configured
+    if settings.matrix_frontend_url:
+        url = settings.matrix_frontend_url.strip()
+        if url and url not in origins:
+            origins.append(url)
+            logger.debug("Added Matrix frontend to CORS: %s", url)
+
     return origins
 
 
+# Pattern to match Tailscale IPs (100.x.x.x) for CORS origin regex
+_TAILSCALE_IP_PATTERN = re.compile(r"^https?://100\.\d{1,3}\.\d{1,3}\.\d{1,3}(?::\d+)?$")
+
+
+def _is_tailscale_origin(origin: str) -> bool:
+    """Check if origin is a Tailscale IP (100.x.x.x range)."""
+    return bool(_TAILSCALE_IP_PATTERN.match(origin))
+
+
 # Add dedicated middleware in correct order
 # 1. Logging (outermost to capture everything)
 app.add_middleware(RequestLoggingMiddleware, skip_paths=["/health"])
 
-# 2. Security Headers
+# 2. Rate Limiting (before security to prevent abuse early)
+app.add_middleware(
+    RateLimitMiddleware,
+    path_prefixes=["/api/matrix/"],
+    requests_per_minute=30,
+)
+
+# 3. Security Headers
 app.add_middleware(SecurityHeadersMiddleware, production=not settings.debug)
 
-# 3. CSRF Protection
+# 4. CSRF Protection
 app.add_middleware(CSRFMiddleware)
 
 # 4. Standard FastAPI middleware
@@ -455,6 +586,7 @@ app.add_middleware(
 app.add_middleware(
     CORSMiddleware,
     allow_origins=_get_cors_origins(),
+    allow_origin_regex=r"https?://100\.\d{1,3}\.\d{1,3}\.\d{1,3}(:\d+)?",
     allow_credentials=True,
     allow_methods=["GET", "POST", "PUT", "DELETE", "OPTIONS"],
     allow_headers=["Content-Type", "Authorization"],
@@ -483,6 +615,7 @@ app.include_router(grok_router)
 app.include_router(models_router)
 app.include_router(models_api_router)
 app.include_router(chat_api_router)
+app.include_router(chat_api_v1_router)
 app.include_router(thinking_router)
 app.include_router(calm_router)
 app.include_router(tasks_router)
@@ -491,6 +624,11 @@ app.include_router(loop_qa_router)
 app.include_router(system_router)
 app.include_router(experiments_router)
 app.include_router(db_explorer_router)
+app.include_router(world_router)
+app.include_router(matrix_router)
+app.include_router(tower_router)
+app.include_router(daily_run_router)
+app.include_router(quests_router)
 
 
 @app.websocket("/ws")

src/dashboard/middleware/__init__.py

@@ -1,6 +1,7 @@
 """Dashboard middleware package."""
 
 from .csrf import CSRFMiddleware, csrf_exempt, generate_csrf_token, validate_csrf_token
+from .rate_limit import RateLimiter, RateLimitMiddleware
 from .request_logging import RequestLoggingMiddleware
 from .security_headers import SecurityHeadersMiddleware
 
@@ -9,6 +10,8 @@ __all__ = [
     "csrf_exempt",
     "generate_csrf_token",
     "validate_csrf_token",
+    "RateLimiter",
+    "RateLimitMiddleware",
     "SecurityHeadersMiddleware",
     "RequestLoggingMiddleware",
 ]

src/dashboard/middleware/csrf.py

@@ -100,7 +100,7 @@ class CSRFMiddleware(BaseHTTPMiddleware):
             ...
 
     Usage:
-        app.add_middleware(CSRFMiddleware, secret="your-secret-key")
+        app.add_middleware(CSRFMiddleware, secret=settings.csrf_secret)
 
     Attributes:
         secret: Secret key for token signing (optional, for future use).
@@ -131,7 +131,6 @@ class CSRFMiddleware(BaseHTTPMiddleware):
         For safe methods: Set a CSRF token cookie if not present.
         For unsafe methods: Validate the CSRF token or check if exempt.
         """
-        # Bypass CSRF if explicitly disabled (e.g. in tests)
         from config import settings
 
         if settings.timmy_disable_csrf:
@@ -141,52 +140,55 @@ class CSRFMiddleware(BaseHTTPMiddleware):
         if request.headers.get("upgrade", "").lower() == "websocket":
             return await call_next(request)
 
-        # Get existing CSRF token from cookie
         csrf_cookie = request.cookies.get(self.cookie_name)
 
-        # For safe methods, just ensure a token exists
         if request.method in self.SAFE_METHODS:
-            response = await call_next(request)
+            return await self._handle_safe_method(request, call_next, csrf_cookie)
 
-            # Set CSRF token cookie if not present
-            if not csrf_cookie:
-                new_token = generate_csrf_token()
-                response.set_cookie(
-                    key=self.cookie_name,
-                    value=new_token,
-                    httponly=False,  # Must be readable by JavaScript
-                    secure=settings.csrf_cookie_secure,
-                    samesite="Lax",
-                    max_age=86400,  # 24 hours
-                )
+        return await self._handle_unsafe_method(request, call_next, csrf_cookie)
 
-            return response
+    async def _handle_safe_method(
+        self, request: Request, call_next, csrf_cookie: str | None
+    ) -> Response:
+        """Handle safe HTTP methods (GET, HEAD, OPTIONS, TRACE).
 
-        # For unsafe methods, we need to validate or check if exempt
-        # First, try to validate the CSRF token
-        if await self._validate_request(request, csrf_cookie):
-            # Token is valid, allow the request
-            return await call_next(request)
+        Forwards the request and sets a CSRF token cookie if not present.
+        """
+        from config import settings
 
-        # Token validation failed, check if the path is exempt
-        path = request.url.path
-        if self._is_likely_exempt(path):
-            # Path is exempt, allow the request
-            return await call_next(request)
-
-        # Token validation failed and path is not exempt
-        # We still need to call the app to check if the endpoint is decorated
-        # with @csrf_exempt, so we'll let it through and check after routing
         response = await call_next(request)
 
-        # After routing, check if the endpoint is marked as exempt
-        endpoint = request.scope.get("endpoint")
-        if endpoint and is_csrf_exempt(endpoint):
-            # Endpoint is marked as exempt, allow the response
-            return response
+        if not csrf_cookie:
+            new_token = generate_csrf_token()
+            response.set_cookie(
+                key=self.cookie_name,
+                value=new_token,
+                httponly=False,  # Must be readable by JavaScript
+                secure=settings.csrf_cookie_secure,
+                samesite="Lax",
+                max_age=86400,  # 24 hours
+            )
+
+        return response
+
+    async def _handle_unsafe_method(
+        self, request: Request, call_next, csrf_cookie: str | None
+    ) -> Response:
+        """Handle unsafe HTTP methods (POST, PUT, DELETE, PATCH).
+
+        Validates the CSRF token, checks path and endpoint exemptions,
+        or returns a 403 error.
+        """
+        if await self._validate_request(request, csrf_cookie):
+            return await call_next(request)
+
+        if self._is_likely_exempt(request.url.path):
+            return await call_next(request)
+
+        endpoint = self._resolve_endpoint(request)
+        if endpoint and is_csrf_exempt(endpoint):
+            return await call_next(request)
 
-        # Endpoint is not exempt and token validation failed
-        # Return 403 error
         return JSONResponse(
             status_code=403,
             content={
@@ -196,6 +198,41 @@ class CSRFMiddleware(BaseHTTPMiddleware):
             },
         )
 
+    def _resolve_endpoint(self, request: Request) -> Callable | None:
+        """Resolve the route endpoint without executing it.
+
+        Walks the Starlette/FastAPI router to find which endpoint function
+        handles this request, so we can check @csrf_exempt before any
+        side effects occur.
+
+        Returns:
+            The endpoint callable, or None if no route matched.
+        """
+        # If routing already happened (endpoint in scope), use it
+        endpoint = request.scope.get("endpoint")
+        if endpoint:
+            return endpoint
+
+        # Walk the middleware/app chain to find something with routes
+        from starlette.routing import Match
+
+        app = self.app
+        while app is not None:
+            if hasattr(app, "routes"):
+                for route in app.routes:
+                    match, _ = route.matches(request.scope)
+                    if match == Match.FULL:
+                        return getattr(route, "endpoint", None)
+            # Try .router (FastAPI stores routes on app.router)
+            if hasattr(app, "router") and hasattr(app.router, "routes"):
+                for route in app.router.routes:
+                    match, _ = route.matches(request.scope)
+                    if match == Match.FULL:
+                        return getattr(route, "endpoint", None)
+            app = getattr(app, "app", None)
+
+        return None
+
     def _is_likely_exempt(self, path: str) -> bool:
         """Check if a path is likely to be CSRF exempt.
 

src/dashboard/middleware/rate_limit.py

@@ -0,0 +1,209 @@
+"""Rate limiting middleware for FastAPI.
+
+Simple in-memory rate limiter for API endpoints. Tracks requests per IP
+with configurable limits and automatic cleanup of stale entries.
+"""
+
+import logging
+import time
+from collections import deque
+
+from starlette.middleware.base import BaseHTTPMiddleware
+from starlette.requests import Request
+from starlette.responses import JSONResponse, Response
+
+logger = logging.getLogger(__name__)
+
+
+class RateLimiter:
+    """In-memory rate limiter for tracking requests per IP.
+
+    Stores request timestamps in a dict keyed by client IP.
+    Automatically cleans up stale entries every 60 seconds.
+
+    Attributes:
+        requests_per_minute: Maximum requests allowed per minute per IP.
+        cleanup_interval_seconds: How often to clean stale entries.
+    """
+
+    def __init__(
+        self,
+        requests_per_minute: int = 30,
+        cleanup_interval_seconds: int = 60,
+    ):
+        self.requests_per_minute = requests_per_minute
+        self.cleanup_interval_seconds = cleanup_interval_seconds
+        self._storage: dict[str, deque[float]] = {}
+        self._last_cleanup: float = time.time()
+        self._window_seconds: float = 60.0  # 1 minute window
+
+    def _get_client_ip(self, request: Request) -> str:
+        """Extract client IP from request, respecting X-Forwarded-For header.
+
+        Args:
+            request: The incoming request.
+
+        Returns:
+            Client IP address string.
+        """
+        # Check for forwarded IP (when behind proxy/load balancer)
+        forwarded = request.headers.get("x-forwarded-for")
+        if forwarded:
+            # Take the first IP in the chain
+            return forwarded.split(",")[0].strip()
+
+        real_ip = request.headers.get("x-real-ip")
+        if real_ip:
+            return real_ip
+
+        # Fall back to direct connection
+        if request.client:
+            return request.client.host
+
+        return "unknown"
+
+    def _cleanup_if_needed(self) -> None:
+        """Remove stale entries older than the cleanup interval."""
+        now = time.time()
+        if now - self._last_cleanup < self.cleanup_interval_seconds:
+            return
+
+        cutoff = now - self._window_seconds
+        stale_ips: list[str] = []
+
+        for ip, timestamps in self._storage.items():
+            # Remove timestamps older than the window
+            while timestamps and timestamps[0] < cutoff:
+                timestamps.popleft()
+            # Mark IP for removal if no recent requests
+            if not timestamps:
+                stale_ips.append(ip)
+
+        # Remove stale IP entries
+        for ip in stale_ips:
+            del self._storage[ip]
+
+        self._last_cleanup = now
+        if stale_ips:
+            logger.debug("Rate limiter cleanup: removed %d stale IPs", len(stale_ips))
+
+    def is_allowed(self, client_ip: str) -> tuple[bool, float]:
+        """Check if a request from the given IP is allowed.
+
+        Args:
+            client_ip: The client's IP address.
+
+        Returns:
+            Tuple of (allowed: bool, retry_after: float).
+            retry_after is seconds until next allowed request, 0 if allowed now.
+        """
+        now = time.time()
+        cutoff = now - self._window_seconds
+
+        # Get or create timestamp deque for this IP
+        if client_ip not in self._storage:
+            self._storage[client_ip] = deque()
+
+        timestamps = self._storage[client_ip]
+
+        # Remove timestamps outside the window
+        while timestamps and timestamps[0] < cutoff:
+            timestamps.popleft()
+
+        # Check if limit exceeded
+        if len(timestamps) >= self.requests_per_minute:
+            # Calculate retry after time
+            oldest = timestamps[0]
+            retry_after = self._window_seconds - (now - oldest)
+            return False, max(0.0, retry_after)
+
+        # Record this request
+        timestamps.append(now)
+        return True, 0.0
+
+    def check_request(self, request: Request) -> tuple[bool, float]:
+        """Check if the request is allowed under rate limits.
+
+        Args:
+            request: The incoming request.
+
+        Returns:
+            Tuple of (allowed: bool, retry_after: float).
+        """
+        self._cleanup_if_needed()
+        client_ip = self._get_client_ip(request)
+        return self.is_allowed(client_ip)
+
+
+class RateLimitMiddleware(BaseHTTPMiddleware):
+    """Middleware to apply rate limiting to specific routes.
+
+    Usage:
+        # Apply to all routes (not recommended for public static files)
+        app.add_middleware(RateLimitMiddleware)
+
+        # Apply only to specific paths
+        app.add_middleware(
+            RateLimitMiddleware,
+            path_prefixes=["/api/matrix/"],
+            requests_per_minute=30,
+        )
+
+    Attributes:
+        path_prefixes: List of URL path prefixes to rate limit.
+                       If empty, applies to all paths.
+        requests_per_minute: Maximum requests per minute per IP.
+    """
+
+    def __init__(
+        self,
+        app,
+        path_prefixes: list[str] | None = None,
+        requests_per_minute: int = 30,
+    ):
+        super().__init__(app)
+        self.path_prefixes = path_prefixes or []
+        self.limiter = RateLimiter(requests_per_minute=requests_per_minute)
+
+    def _should_rate_limit(self, path: str) -> bool:
+        """Check if the given path should be rate limited.
+
+        Args:
+            path: The request URL path.
+
+        Returns:
+            True if path matches any configured prefix.
+        """
+        if not self.path_prefixes:
+            return True
+        return any(path.startswith(prefix) for prefix in self.path_prefixes)
+
+    async def dispatch(self, request: Request, call_next) -> Response:
+        """Apply rate limiting to configured paths.
+
+        Args:
+            request: The incoming request.
+            call_next: Callable to get the response from downstream.
+
+        Returns:
+            Response from downstream, or 429 if rate limited.
+        """
+        # Skip if path doesn't match configured prefixes
+        if not self._should_rate_limit(request.url.path):
+            return await call_next(request)
+
+        # Check rate limit
+        allowed, retry_after = self.limiter.check_request(request)
+
+        if not allowed:
+            return JSONResponse(
+                status_code=429,
+                content={
+                    "error": "Rate limit exceeded. Try again later.",
+                    "retry_after": int(retry_after) + 1,
+                },
+                headers={"Retry-After": str(int(retry_after) + 1)},
+            )
+
+        # Process the request
+        return await call_next(request)

src/dashboard/middleware/request_logging.py

@@ -42,6 +42,114 @@ class RequestLoggingMiddleware(BaseHTTPMiddleware):
         self.skip_paths = set(skip_paths or [])
         self.log_level = log_level
 
+    def _should_skip_path(self, path: str) -> bool:
+        """Check if the request path should be skipped from logging.
+
+        Args:
+            path: The request URL path.
+
+        Returns:
+            True if the path should be skipped, False otherwise.
+        """
+        return path in self.skip_paths
+
+    def _prepare_request_context(self, request: Request) -> tuple[str, float]:
+        """Prepare context for request processing.
+
+        Generates a correlation ID and records the start time.
+
+        Args:
+            request: The incoming request.
+
+        Returns:
+            Tuple of (correlation_id, start_time).
+        """
+        correlation_id = str(uuid.uuid4())[:8]
+        request.state.correlation_id = correlation_id
+        start_time = time.time()
+        return correlation_id, start_time
+
+    def _get_duration_ms(self, start_time: float) -> float:
+        """Calculate the request duration in milliseconds.
+
+        Args:
+            start_time: The start time from time.time().
+
+        Returns:
+            Duration in milliseconds.
+        """
+        return (time.time() - start_time) * 1000
+
+    def _log_success(
+        self,
+        request: Request,
+        response: Response,
+        correlation_id: str,
+        duration_ms: float,
+        client_ip: str,
+        user_agent: str,
+    ) -> None:
+        """Log a successful request.
+
+        Args:
+            request: The incoming request.
+            response: The response from downstream.
+            correlation_id: The request correlation ID.
+            duration_ms: Request duration in milliseconds.
+            client_ip: Client IP address.
+            user_agent: User-Agent header value.
+        """
+        self._log_request(
+            method=request.method,
+            path=request.url.path,
+            status_code=response.status_code,
+            duration_ms=duration_ms,
+            client_ip=client_ip,
+            user_agent=user_agent,
+            correlation_id=correlation_id,
+        )
+
+    def _log_error(
+        self,
+        request: Request,
+        exc: Exception,
+        correlation_id: str,
+        duration_ms: float,
+        client_ip: str,
+    ) -> None:
+        """Log a failed request and capture the error.
+
+        Args:
+            request: The incoming request.
+            exc: The exception that was raised.
+            correlation_id: The request correlation ID.
+            duration_ms: Request duration in milliseconds.
+            client_ip: Client IP address.
+        """
+        logger.error(
+            f"[{correlation_id}] {request.method} {request.url.path} "
+            f"- ERROR - {duration_ms:.2f}ms - {client_ip} - {str(exc)}"
+        )
+
+        # Auto-escalate: create bug report task from unhandled exception
+        try:
+            from infrastructure.error_capture import capture_error
+
+            capture_error(
+                exc,
+                source="http",
+                context={
+                    "method": request.method,
+                    "path": request.url.path,
+                    "correlation_id": correlation_id,
+                    "client_ip": client_ip,
+                    "duration_ms": f"{duration_ms:.0f}",
+                },
+            )
+        except Exception:
+            logger.warning("Escalation logging error: capture failed")
+            # never let escalation break the request
+
     async def dispatch(self, request: Request, call_next) -> Response:
         """Log the request and response details.
 
@@ -52,74 +160,23 @@ class RequestLoggingMiddleware(BaseHTTPMiddleware):
         Returns:
             The response from downstream.
         """
-        # Check if we should skip logging this path
-        if request.url.path in self.skip_paths:
+        if self._should_skip_path(request.url.path):
             return await call_next(request)
 
-        # Generate correlation ID
-        correlation_id = str(uuid.uuid4())[:8]
-        request.state.correlation_id = correlation_id
-
-        # Record start time
-        start_time = time.time()
-
-        # Get client info
+        correlation_id, start_time = self._prepare_request_context(request)
         client_ip = self._get_client_ip(request)
         user_agent = request.headers.get("user-agent", "-")
 
         try:
-            # Process the request
             response = await call_next(request)
-
-            # Calculate duration
-            duration_ms = (time.time() - start_time) * 1000
-
-            # Log the request
-            self._log_request(
-                method=request.method,
-                path=request.url.path,
-                status_code=response.status_code,
-                duration_ms=duration_ms,
-                client_ip=client_ip,
-                user_agent=user_agent,
-                correlation_id=correlation_id,
-            )
-
-            # Add correlation ID to response headers
+            duration_ms = self._get_duration_ms(start_time)
+            self._log_success(request, response, correlation_id, duration_ms, client_ip, user_agent)
             response.headers["X-Correlation-ID"] = correlation_id
-
             return response
 
         except Exception as exc:
-            # Calculate duration even for failed requests
-            duration_ms = (time.time() - start_time) * 1000
-
-            # Log the error
-            logger.error(
-                f"[{correlation_id}] {request.method} {request.url.path} "
-                f"- ERROR - {duration_ms:.2f}ms - {client_ip} - {str(exc)}"
-            )
-
-            # Auto-escalate: create bug report task from unhandled exception
-            try:
-                from infrastructure.error_capture import capture_error
-
-                capture_error(
-                    exc,
-                    source="http",
-                    context={
-                        "method": request.method,
-                        "path": request.url.path,
-                        "correlation_id": correlation_id,
-                        "client_ip": client_ip,
-                        "duration_ms": f"{duration_ms:.0f}",
-                    },
-                )
-            except Exception as exc:
-                logger.debug("Escalation logging error: %s", exc)
-                pass  # never let escalation break the request
-
-            # Re-raise the exception
+            duration_ms = self._get_duration_ms(start_time)
+            self._log_error(request, exc, correlation_id, duration_ms, client_ip)
             raise
 
     def _get_client_ip(self, request: Request) -> str:

src/dashboard/models/calm.py

@@ -1,4 +1,4 @@
-from datetime import date, datetime
+from datetime import UTC, date, datetime
 from enum import StrEnum
 
 from sqlalchemy import JSON, Boolean, Column, Date, DateTime, Index, Integer, String
@@ -40,8 +40,13 @@ class Task(Base):
     deferred_at = Column(DateTime, nullable=True)
 
     # Timestamps
-    created_at = Column(DateTime, default=datetime.utcnow, nullable=False)
-    updated_at = Column(DateTime, default=datetime.utcnow, onupdate=datetime.utcnow, nullable=False)
+    created_at = Column(DateTime, default=lambda: datetime.now(UTC), nullable=False)
+    updated_at = Column(
+        DateTime,
+        default=lambda: datetime.now(UTC),
+        onupdate=lambda: datetime.now(UTC),
+        nullable=False,
+    )
 
     __table_args__ = (Index("ix_task_state_order", "state", "sort_order"),)
 
@@ -59,4 +64,4 @@ class JournalEntry(Base):
     gratitude = Column(String(500), nullable=True)
     energy_level = Column(Integer, nullable=True)  # User-reported, 1-10
 
-    created_at = Column(DateTime, default=datetime.utcnow, nullable=False)
+    created_at = Column(DateTime, default=lambda: datetime.now(UTC), nullable=False)

src/dashboard/routes/agents.py

@@ -71,19 +71,87 @@ async def clear_history(request: Request):
     )
 
 
+def _validate_message(message: str) -> str:
+    """Strip and validate chat input; raise HTTPException on bad input."""
+    from fastapi import HTTPException
+
+    message = message.strip()
+    if not message:
+        raise HTTPException(status_code=400, detail="Message cannot be empty")
+    if len(message) > MAX_MESSAGE_LENGTH:
+        raise HTTPException(status_code=422, detail="Message too long")
+    return message
+
+
+def _record_user_activity() -> None:
+    """Notify the thinking engine that the user is active."""
+    try:
+        from timmy.thinking import thinking_engine
+
+        thinking_engine.record_user_input()
+    except Exception:
+        logger.debug("Failed to record user input for thinking engine")
+
+
+def _extract_tool_actions(run_output) -> list[dict]:
+    """If Agno paused the run for tool confirmation, build approval items."""
+    from timmy.approvals import create_item
+
+    tool_actions: list[dict] = []
+    status = getattr(run_output, "status", None)
+    is_paused = status == "PAUSED" or str(status) == "RunStatus.paused"
+
+    if not (is_paused and getattr(run_output, "active_requirements", None)):
+        return tool_actions
+
+    for req in run_output.active_requirements:
+        if not getattr(req, "needs_confirmation", False):
+            continue
+        te = req.tool_execution
+        tool_name = getattr(te, "tool_name", "unknown")
+        tool_args = getattr(te, "tool_args", {}) or {}
+
+        item = create_item(
+            title=f"Dashboard: {tool_name}",
+            description=format_action_description(tool_name, tool_args),
+            proposed_action=json.dumps({"tool": tool_name, "args": tool_args}),
+            impact=get_impact_level(tool_name),
+        )
+        _pending_runs[item.id] = {
+            "run_output": run_output,
+            "requirement": req,
+            "tool_name": tool_name,
+            "tool_args": tool_args,
+        }
+        tool_actions.append(
+            {
+                "approval_id": item.id,
+                "tool_name": tool_name,
+                "description": format_action_description(tool_name, tool_args),
+                "impact": get_impact_level(tool_name),
+            }
+        )
+    return tool_actions
+
+
+def _log_exchange(
+    message: str, response_text: str | None, error_text: str | None, timestamp: str
+) -> None:
+    """Append user message and agent/error reply to the in-memory log."""
+    message_log.append(role="user", content=message, timestamp=timestamp, source="browser")
+    if response_text:
+        message_log.append(
+            role="agent", content=response_text, timestamp=timestamp, source="browser"
+        )
+    elif error_text:
+        message_log.append(role="error", content=error_text, timestamp=timestamp, source="browser")
+
+
 @router.post("/default/chat", response_class=HTMLResponse)
 async def chat_agent(request: Request, message: str = Form(...)):
     """Chat — synchronous response with native Agno tool confirmation."""
-    message = message.strip()
-    if not message:
-        from fastapi import HTTPException
-
-        raise HTTPException(status_code=400, detail="Message cannot be empty")
-
-    if len(message) > MAX_MESSAGE_LENGTH:
-        from fastapi import HTTPException
-
-        raise HTTPException(status_code=422, detail="Message too long")
+    message = _validate_message(message)
+    _record_user_activity()
 
     timestamp = datetime.now().strftime("%H:%M:%S")
     response_text = None
@@ -96,54 +164,15 @@ async def chat_agent(request: Request, message: str = Form(...)):
         error_text = f"Chat error: {exc}"
         run_output = None
 
-    # Check if Agno paused the run for tool confirmation
-    tool_actions = []
+    tool_actions: list[dict] = []
     if run_output is not None:
-        status = getattr(run_output, "status", None)
-        is_paused = status == "PAUSED" or str(status) == "RunStatus.paused"
-
-        if is_paused and getattr(run_output, "active_requirements", None):
-            for req in run_output.active_requirements:
-                if getattr(req, "needs_confirmation", False):
-                    te = req.tool_execution
-                    tool_name = getattr(te, "tool_name", "unknown")
-                    tool_args = getattr(te, "tool_args", {}) or {}
-
-                    from timmy.approvals import create_item
-
-                    item = create_item(
-                        title=f"Dashboard: {tool_name}",
-                        description=format_action_description(tool_name, tool_args),
-                        proposed_action=json.dumps({"tool": tool_name, "args": tool_args}),
-                        impact=get_impact_level(tool_name),
-                    )
-                    _pending_runs[item.id] = {
-                        "run_output": run_output,
-                        "requirement": req,
-                        "tool_name": tool_name,
-                        "tool_args": tool_args,
-                    }
-                    tool_actions.append(
-                        {
-                            "approval_id": item.id,
-                            "tool_name": tool_name,
-                            "description": format_action_description(tool_name, tool_args),
-                            "impact": get_impact_level(tool_name),
-                        }
-                    )
-
+        tool_actions = _extract_tool_actions(run_output)
         raw_content = run_output.content if hasattr(run_output, "content") else ""
         response_text = _clean_response(raw_content or "")
         if not response_text and not tool_actions:
-            response_text = None  # let error template show if needed
+            response_text = None
 
-    message_log.append(role="user", content=message, timestamp=timestamp, source="browser")
-    if response_text:
-        message_log.append(
-            role="agent", content=response_text, timestamp=timestamp, source="browser"
-        )
-    elif error_text:
-        message_log.append(role="error", content=error_text, timestamp=timestamp, source="browser")
+    _log_exchange(message, response_text, error_text, timestamp)
 
     return templates.TemplateResponse(
         request,

src/dashboard/routes/calm.py

@@ -1,5 +1,5 @@
 import logging
-from datetime import date, datetime
+from datetime import UTC, date, datetime
 
 from fastapi import APIRouter, Depends, Form, HTTPException, Request
 from fastapi.responses import HTMLResponse
@@ -19,14 +19,17 @@ router = APIRouter(tags=["calm"])
 
 # Helper functions for state machine logic
 def get_now_task(db: Session) -> Task | None:
+    """Return the single active NOW task, or None."""
     return db.query(Task).filter(Task.state == TaskState.NOW).first()
 
 
 def get_next_task(db: Session) -> Task | None:
+    """Return the single queued NEXT task, or None."""
     return db.query(Task).filter(Task.state == TaskState.NEXT).first()
 
 
 def get_later_tasks(db: Session) -> list[Task]:
+    """Return all LATER tasks ordered by MIT flag then sort_order."""
     return (
         db.query(Task)
         .filter(Task.state == TaskState.LATER)
@@ -35,7 +38,63 @@ def get_later_tasks(db: Session) -> list[Task]:
     )
 
 
+def _create_mit_tasks(db: Session, titles: list[str | None]) -> list[int]:
+    """Create MIT tasks from a list of titles, return their IDs."""
+    task_ids: list[int] = []
+    for title in titles:
+        if title:
+            task = Task(
+                title=title,
+                is_mit=True,
+                state=TaskState.LATER,
+                certainty=TaskCertainty.SOFT,
+            )
+            db.add(task)
+            db.commit()
+            db.refresh(task)
+            task_ids.append(task.id)
+    return task_ids
+
+
+def _create_other_tasks(db: Session, other_tasks: str):
+    """Create non-MIT tasks from newline-separated text."""
+    for line in other_tasks.split("\n"):
+        line = line.strip()
+        if line:
+            task = Task(
+                title=line,
+                state=TaskState.LATER,
+                certainty=TaskCertainty.FUZZY,
+            )
+            db.add(task)
+
+
+def _seed_now_next(db: Session):
+    """Set initial NOW/NEXT states when both slots are empty."""
+    if get_now_task(db) or get_next_task(db):
+        return
+    later_tasks = (
+        db.query(Task)
+        .filter(Task.state == TaskState.LATER)
+        .order_by(Task.is_mit.desc(), Task.sort_order)
+        .all()
+    )
+    if later_tasks:
+        later_tasks[0].state = TaskState.NOW
+        db.add(later_tasks[0])
+        db.flush()
+        if len(later_tasks) > 1:
+            later_tasks[1].state = TaskState.NEXT
+            db.add(later_tasks[1])
+
+
 def promote_tasks(db: Session):
+    """Enforce the NOW/NEXT/LATER state machine invariants.
+
+    - At most one NOW task (extras demoted to NEXT).
+    - If no NOW, promote NEXT -> NOW.
+    - If no NEXT, promote highest-priority LATER -> NEXT.
+    """
     # Ensure only one NOW task exists. If multiple, demote extras to NEXT.
     now_tasks = db.query(Task).filter(Task.state == TaskState.NOW).all()
     if len(now_tasks) > 1:
@@ -74,6 +133,7 @@ def promote_tasks(db: Session):
 # Endpoints
 @router.get("/calm", response_class=HTMLResponse)
 async def get_calm_view(request: Request, db: Session = Depends(get_db)):
+    """Render the main CALM dashboard with NOW/NEXT/LATER counts."""
     now_task = get_now_task(db)
     next_task = get_next_task(db)
     later_tasks_count = len(get_later_tasks(db))
@@ -90,6 +150,7 @@ async def get_calm_view(request: Request, db: Session = Depends(get_db)):
 
 @router.get("/calm/ritual/morning", response_class=HTMLResponse)
 async def get_morning_ritual_form(request: Request):
+    """Render the morning ritual intake form."""
     return templates.TemplateResponse(request, "calm/morning_ritual_form.html", {})
 
 
@@ -102,63 +163,20 @@ async def post_morning_ritual(
     mit3_title: str = Form(None),
     other_tasks: str = Form(""),
 ):
-    # Create Journal Entry
-    mit_task_ids = []
+    """Process morning ritual: create MITs, other tasks, and set initial states."""
     journal_entry = JournalEntry(entry_date=date.today())
     db.add(journal_entry)
     db.commit()
     db.refresh(journal_entry)
 
-    # Create MIT tasks
-    for mit_title in [mit1_title, mit2_title, mit3_title]:
-        if mit_title:
-            task = Task(
-                title=mit_title,
-                is_mit=True,
-                state=TaskState.LATER,  # Initially LATER, will be promoted
-                certainty=TaskCertainty.SOFT,
-            )
-            db.add(task)
-            db.commit()
-            db.refresh(task)
-            mit_task_ids.append(task.id)
-
-    journal_entry.mit_task_ids = mit_task_ids
+    journal_entry.mit_task_ids = _create_mit_tasks(db, [mit1_title, mit2_title, mit3_title])
     db.add(journal_entry)
 
-    # Create other tasks
-    for task_title in other_tasks.split("\n"):
-        task_title = task_title.strip()
-        if task_title:
-            task = Task(
-                title=task_title,
-                state=TaskState.LATER,
-                certainty=TaskCertainty.FUZZY,
-            )
-            db.add(task)
-
+    _create_other_tasks(db, other_tasks)
     db.commit()
 
-    # Set initial NOW/NEXT states
-    # Set initial NOW/NEXT states after all tasks are created
-    if not get_now_task(db) and not get_next_task(db):
-        later_tasks = (
-            db.query(Task)
-            .filter(Task.state == TaskState.LATER)
-            .order_by(Task.is_mit.desc(), Task.sort_order)
-            .all()
-        )
-        if later_tasks:
-            # Set the highest priority LATER task to NOW
-            later_tasks[0].state = TaskState.NOW
-            db.add(later_tasks[0])
-            db.flush()  # Flush to make the change visible for the next query
-
-            # Set the next highest priority LATER task to NEXT
-            if len(later_tasks) > 1:
-                later_tasks[1].state = TaskState.NEXT
-                db.add(later_tasks[1])
-    db.commit()  # Commit changes after initial NOW/NEXT setup
+    _seed_now_next(db)
+    db.commit()
 
     return templates.TemplateResponse(
         request,
@@ -173,6 +191,7 @@ async def post_morning_ritual(
 
 @router.get("/calm/ritual/evening", response_class=HTMLResponse)
 async def get_evening_ritual_form(request: Request, db: Session = Depends(get_db)):
+    """Render the evening ritual form for today's journal entry."""
     journal_entry = db.query(JournalEntry).filter(JournalEntry.entry_date == date.today()).first()
     if not journal_entry:
         raise HTTPException(status_code=404, detail="No journal entry for today")
@@ -189,6 +208,7 @@ async def post_evening_ritual(
     gratitude: str = Form(None),
     energy_level: int = Form(None),
 ):
+    """Process evening ritual: save reflection/gratitude, archive active tasks."""
     journal_entry = db.query(JournalEntry).filter(JournalEntry.entry_date == date.today()).first()
     if not journal_entry:
         raise HTTPException(status_code=404, detail="No journal entry for today")
@@ -206,7 +226,7 @@ async def post_evening_ritual(
     )
     for task in active_tasks:
         task.state = TaskState.DEFERRED  # Or DONE, depending on desired archiving logic
-        task.deferred_at = datetime.utcnow()
+        task.deferred_at = datetime.now(UTC)
         db.add(task)
 
     db.commit()
@@ -223,6 +243,7 @@ async def create_new_task(
     is_mit: bool = Form(False),
     certainty: TaskCertainty = Form(TaskCertainty.SOFT),
 ):
+    """Create a new task in LATER state and return updated count."""
     task = Task(
         title=title,
         description=description,
@@ -247,6 +268,7 @@ async def start_task(
     task_id: int,
     db: Session = Depends(get_db),
 ):
+    """Move a task to NOW state, demoting the current NOW to NEXT."""
     current_now_task = get_now_task(db)
     if current_now_task and current_now_task.id != task_id:
         current_now_task.state = TaskState.NEXT  # Demote current NOW to NEXT
@@ -257,7 +279,7 @@ async def start_task(
         raise HTTPException(status_code=404, detail="Task not found")
 
     task.state = TaskState.NOW
-    task.started_at = datetime.utcnow()
+    task.started_at = datetime.now(UTC)
     db.add(task)
     db.commit()
 
@@ -281,12 +303,13 @@ async def complete_task(
     task_id: int,
     db: Session = Depends(get_db),
 ):
+    """Mark a task as DONE and trigger state promotion."""
     task = db.query(Task).filter(Task.id == task_id).first()
     if not task:
         raise HTTPException(status_code=404, detail="Task not found")
 
     task.state = TaskState.DONE
-    task.completed_at = datetime.utcnow()
+    task.completed_at = datetime.now(UTC)
     db.add(task)
     db.commit()
 
@@ -309,12 +332,13 @@ async def defer_task(
     task_id: int,
     db: Session = Depends(get_db),
 ):
+    """Defer a task and trigger state promotion."""
     task = db.query(Task).filter(Task.id == task_id).first()
     if not task:
         raise HTTPException(status_code=404, detail="Task not found")
 
     task.state = TaskState.DEFERRED
-    task.deferred_at = datetime.utcnow()
+    task.deferred_at = datetime.now(UTC)
     db.add(task)
     db.commit()
 
@@ -333,6 +357,7 @@ async def defer_task(
 
 @router.get("/calm/partials/later_tasks_list", response_class=HTMLResponse)
 async def get_later_tasks_list(request: Request, db: Session = Depends(get_db)):
+    """Render the expandable list of LATER tasks."""
     later_tasks = get_later_tasks(db)
     return templates.TemplateResponse(
         "calm/partials/later_tasks_list.html",
@@ -348,6 +373,7 @@ async def reorder_tasks(
     later_task_ids: str = Form(""),
     next_task_id: int | None = Form(None),
 ):
+    """Reorder LATER tasks and optionally promote one to NEXT."""
     # Reorder LATER tasks
     if later_task_ids:
         ids_in_order = [int(x.strip()) for x in later_task_ids.split(",") if x.strip()]

src/dashboard/routes/chat_api.py

@@ -31,6 +31,93 @@ _UPLOAD_DIR = str(Path(settings.repo_root) / "data" / "chat-uploads")
 _MAX_UPLOAD_SIZE = 50 * 1024 * 1024  # 50 MB
 
 
+# ── POST /api/chat — helpers ─────────────────────────────────────────────────
+
+
+async def _parse_chat_body(request: Request) -> tuple[dict | None, JSONResponse | None]:
+    """Parse and validate the JSON request body.
+
+    Returns (body, None) on success or (None, error_response) on failure.
+    """
+    content_length = request.headers.get("content-length")
+    if content_length and int(content_length) > settings.chat_api_max_body_bytes:
+        return None, JSONResponse(status_code=413, content={"error": "Request body too large"})
+
+    try:
+        body = await request.json()
+    except Exception as exc:
+        logger.warning("Chat API JSON parse error: %s", exc)
+        return None, JSONResponse(status_code=400, content={"error": "Invalid JSON"})
+
+    messages = body.get("messages")
+    if not messages or not isinstance(messages, list):
+        return None, JSONResponse(status_code=400, content={"error": "messages array is required"})
+
+    return body, None
+
+
+def _extract_user_message(messages: list[dict]) -> str | None:
+    """Return the text of the last user message, or *None* if absent."""
+    for msg in reversed(messages):
+        if msg.get("role") == "user":
+            content = msg.get("content", "")
+            if isinstance(content, list):
+                text_parts = [
+                    p.get("text", "")
+                    for p in content
+                    if isinstance(p, dict) and p.get("type") == "text"
+                ]
+                return " ".join(text_parts).strip() or None
+            text = str(content).strip()
+            return text or None
+    return None
+
+
+def _build_context_prefix() -> str:
+    """Build the system-context preamble injected before the user message."""
+    now = datetime.now()
+    return (
+        f"[System: Current date/time is "
+        f"{now.strftime('%A, %B %d, %Y at %I:%M %p')}]\n"
+        f"[System: Mobile client]\n\n"
+    )
+
+
+def _notify_thinking_engine() -> None:
+    """Record user activity so the thinking engine knows we're not idle."""
+    try:
+        from timmy.thinking import thinking_engine
+
+        thinking_engine.record_user_input()
+    except Exception:
+        logger.debug("Failed to record user input for thinking engine")
+
+
+async def _process_chat(user_msg: str) -> dict | JSONResponse:
+    """Send *user_msg* to the agent, log the exchange, and return a response."""
+    _notify_thinking_engine()
+    timestamp = datetime.now().strftime("%H:%M:%S")
+
+    try:
+        response_text = await agent_chat(
+            _build_context_prefix() + user_msg,
+            session_id="mobile",
+        )
+        message_log.append(role="user", content=user_msg, timestamp=timestamp, source="api")
+        message_log.append(role="agent", content=response_text, timestamp=timestamp, source="api")
+        return {"reply": response_text, "timestamp": timestamp}
+
+    except Exception as exc:
+        error_msg = f"Agent is offline: {exc}"
+        logger.error("api_chat error: %s", exc)
+        message_log.append(role="user", content=user_msg, timestamp=timestamp, source="api")
+        message_log.append(role="error", content=error_msg, timestamp=timestamp, source="api")
+        return JSONResponse(
+            status_code=503,
+            content={"error": error_msg, "timestamp": timestamp},
+        )
+
+
 # ── POST /api/chat ────────────────────────────────────────────────────────────
 
 
@@ -44,70 +131,15 @@ async def api_chat(request: Request):
     Response:
         {"reply": "...", "timestamp": "HH:MM:SS"}
     """
-    # Enforce request body size limit
-    content_length = request.headers.get("content-length")
-    if content_length and int(content_length) > settings.chat_api_max_body_bytes:
-        return JSONResponse(status_code=413, content={"error": "Request body too large"})
+    body, err = await _parse_chat_body(request)
+    if err:
+        return err
 
-    try:
-        body = await request.json()
-    except Exception as exc:
-        logger.warning("Chat API JSON parse error: %s", exc)
-        return JSONResponse(status_code=400, content={"error": "Invalid JSON"})
-
-    messages = body.get("messages")
-    if not messages or not isinstance(messages, list):
-        return JSONResponse(status_code=400, content={"error": "messages array is required"})
-
-    # Extract the latest user message text
-    last_user_msg = None
-    for msg in reversed(messages):
-        if msg.get("role") == "user":
-            content = msg.get("content", "")
-            # Handle multimodal content arrays — extract text parts
-            if isinstance(content, list):
-                text_parts = [
-                    p.get("text", "")
-                    for p in content
-                    if isinstance(p, dict) and p.get("type") == "text"
-                ]
-                last_user_msg = " ".join(text_parts).strip()
-            else:
-                last_user_msg = str(content).strip()
-            break
-
-    if not last_user_msg:
+    user_msg = _extract_user_message(body["messages"])
+    if not user_msg:
         return JSONResponse(status_code=400, content={"error": "No user message found"})
 
-    timestamp = datetime.now().strftime("%H:%M:%S")
-
-    try:
-        # Inject context (same pattern as the HTMX chat handler in agents.py)
-        now = datetime.now()
-        context_prefix = (
-            f"[System: Current date/time is "
-            f"{now.strftime('%A, %B %d, %Y at %I:%M %p')}]\n"
-            f"[System: Mobile client]\n\n"
-        )
-        response_text = await agent_chat(
-            context_prefix + last_user_msg,
-            session_id="mobile",
-        )
-
-        message_log.append(role="user", content=last_user_msg, timestamp=timestamp, source="api")
-        message_log.append(role="agent", content=response_text, timestamp=timestamp, source="api")
-
-        return {"reply": response_text, "timestamp": timestamp}
-
-    except Exception as exc:
-        error_msg = f"Agent is offline: {exc}"
-        logger.error("api_chat error: %s", exc)
-        message_log.append(role="user", content=last_user_msg, timestamp=timestamp, source="api")
-        message_log.append(role="error", content=error_msg, timestamp=timestamp, source="api")
-        return JSONResponse(
-            status_code=503,
-            content={"error": error_msg, "timestamp": timestamp},
-        )
+    return await _process_chat(user_msg)
 
 
 # ── POST /api/upload ──────────────────────────────────────────────────────────

src/dashboard/routes/chat_api_v1.py

@@ -0,0 +1,198 @@
+"""Version 1 (v1) JSON REST API for the Timmy Time iPad app.
+
+This module implements the specific endpoints required by the native
+iPad app as defined in the project specification.
+
+Endpoints:
+    POST /api/v1/chat           — Streaming SSE chat response
+    GET  /api/v1/chat/history   — Retrieve chat history with limit
+    POST /api/v1/upload         — Multipart file upload with auto-detection
+    GET  /api/v1/status         — Detailed system and model status
+"""
+
+import json
+import logging
+import os
+import uuid
+from datetime import UTC, datetime
+from pathlib import Path
+
+from fastapi import APIRouter, File, HTTPException, Query, Request, UploadFile
+from fastapi.responses import JSONResponse, StreamingResponse
+
+from config import APP_START_TIME, settings
+from dashboard.routes.health import _check_ollama
+from dashboard.store import message_log
+from timmy.session import _get_agent
+
+logger = logging.getLogger(__name__)
+
+router = APIRouter(prefix="/api/v1", tags=["chat-api-v1"])
+
+_UPLOAD_DIR = str(Path(settings.repo_root) / "data" / "chat-uploads")
+_MAX_UPLOAD_SIZE = 50 * 1024 * 1024  # 50 MB
+
+
+# ── POST /api/v1/chat ─────────────────────────────────────────────────────────
+
+
+@router.post("/chat")
+async def api_v1_chat(request: Request):
+    """Accept a JSON chat payload and return a streaming SSE response.
+
+    Request body:
+        {
+            "message": "string",
+            "session_id": "string",
+            "attachments": ["id1", "id2"]
+        }
+
+    Response:
+        text/event-stream (SSE)
+    """
+    try:
+        body = await request.json()
+    except Exception as exc:
+        logger.warning("Chat v1 API JSON parse error: %s", exc)
+        return JSONResponse(status_code=400, content={"error": "Invalid JSON"})
+
+    message = body.get("message")
+    session_id = body.get("session_id", "ipad-app")
+    attachments = body.get("attachments", [])
+
+    if not message:
+        return JSONResponse(status_code=400, content={"error": "message is required"})
+
+    # Prepare context for the agent
+    context_prefix = (
+        f"[System: Current date/time is "
+        f"{datetime.now().strftime('%A, %B %d, %Y at %I:%M %p')}]\n"
+        f"[System: iPad App client]\n"
+    )
+
+    if attachments:
+        context_prefix += f"[System: Attachments: {', '.join(attachments)}]\n"
+
+    context_prefix += "\n"
+    full_prompt = context_prefix + message
+
+    async def event_generator():
+        try:
+            agent = _get_agent()
+            # Using streaming mode for SSE
+            async for chunk in agent.arun(full_prompt, stream=True, session_id=session_id):
+                # Agno chunks can be strings or RunOutput
+                content = chunk.content if hasattr(chunk, "content") else str(chunk)
+                if content:
+                    yield f"data: {json.dumps({'text': content})}\n\n"
+
+            yield "data: [DONE]\n\n"
+        except Exception as exc:
+            logger.error("SSE stream error: %s", exc)
+            yield f"data: {json.dumps({'error': str(exc)})}\n\n"
+
+    return StreamingResponse(event_generator(), media_type="text/event-stream")
+
+
+# ── GET /api/v1/chat/history ──────────────────────────────────────────────────
+
+
+@router.get("/chat/history")
+async def api_v1_chat_history(
+    session_id: str = Query("ipad-app"), limit: int = Query(50, ge=1, le=100)
+):
+    """Return recent chat history for a specific session."""
+    # Filter and limit the message log
+    # Note: message_log.all() returns all messages; we filter by source or just return last N
+    all_msgs = message_log.all()
+
+    # In a real implementation, we'd filter by session_id if message_log supported it.
+    # For now, we return the last 'limit' messages.
+    history = [
+        {
+            "role": msg.role,
+            "content": msg.content,
+            "timestamp": msg.timestamp,
+            "source": msg.source,
+        }
+        for msg in all_msgs[-limit:]
+    ]
+
+    return {"messages": history}
+
+
+# ── POST /api/v1/upload ───────────────────────────────────────────────────────
+
+
+@router.post("/upload")
+async def api_v1_upload(file: UploadFile = File(...)):
+    """Accept a file upload, auto-detect type, and return metadata.
+
+    Response:
+        {
+            "id": "string",
+            "type": "image|audio|document|url",
+            "summary": "string",
+            "metadata": {...}
+        }
+    """
+    os.makedirs(_UPLOAD_DIR, exist_ok=True)
+
+    file_id = uuid.uuid4().hex[:12]
+    safe_name = os.path.basename(file.filename or "upload")
+    stored_name = f"{file_id}-{safe_name}"
+    file_path = os.path.join(_UPLOAD_DIR, stored_name)
+
+    # Verify resolved path stays within upload directory
+    resolved = Path(file_path).resolve()
+    upload_root = Path(_UPLOAD_DIR).resolve()
+    if not str(resolved).startswith(str(upload_root)):
+        raise HTTPException(status_code=400, detail="Invalid file name")
+
+    contents = await file.read()
+    if len(contents) > _MAX_UPLOAD_SIZE:
+        raise HTTPException(status_code=413, detail="File too large (max 50 MB)")
+
+    with open(file_path, "wb") as f:
+        f.write(contents)
+
+    # Auto-detect type based on extension/mime
+    mime_type = file.content_type or "application/octet-stream"
+    ext = os.path.splitext(safe_name)[1].lower()
+
+    media_type = "document"
+    if mime_type.startswith("image/") or ext in [".jpg", ".jpeg", ".png", ".heic"]:
+        media_type = "image"
+    elif mime_type.startswith("audio/") or ext in [".m4a", ".mp3", ".wav", ".caf"]:
+        media_type = "audio"
+    elif ext in [".pdf", ".txt", ".md"]:
+        media_type = "document"
+
+    # Placeholder for actual processing (OCR, Whisper, etc.)
+    summary = f"Uploaded {media_type}: {safe_name}"
+
+    return {
+        "id": file_id,
+        "type": media_type,
+        "summary": summary,
+        "url": f"/uploads/{stored_name}",
+        "metadata": {"fileName": safe_name, "mimeType": mime_type, "size": len(contents)},
+    }
+
+
+# ── GET /api/v1/status ────────────────────────────────────────────────────────
+
+
+@router.get("/status")
+async def api_v1_status():
+    """Detailed system and model status."""
+    ollama_status = await _check_ollama()
+    uptime = (datetime.now(UTC) - APP_START_TIME).total_seconds()
+
+    return {
+        "timmy": "online" if ollama_status.status == "healthy" else "offline",
+        "model": settings.ollama_model,
+        "ollama": "running" if ollama_status.status == "healthy" else "stopped",
+        "uptime": f"{int(uptime // 3600)}h {int((uptime % 3600) // 60)}m",
+        "version": "2.0.0-v1-api",
+    }

src/dashboard/routes/daily_run.py

@@ -0,0 +1,435 @@
+"""Daily Run metrics routes — dashboard card for triage and session metrics."""
+
+from __future__ import annotations
+
+import json
+import logging
+import os
+from dataclasses import dataclass
+from datetime import UTC, datetime, timedelta
+from pathlib import Path
+from urllib.error import HTTPError, URLError
+from urllib.request import Request as UrlRequest
+from urllib.request import urlopen
+
+from fastapi import APIRouter, Request
+from fastapi.responses import HTMLResponse, JSONResponse
+
+from config import settings
+from dashboard.templating import templates
+
+logger = logging.getLogger(__name__)
+
+router = APIRouter(tags=["daily-run"])
+
+REPO_ROOT = Path(settings.repo_root)
+CONFIG_PATH = REPO_ROOT / "timmy_automations" / "config" / "daily_run.json"
+
+DEFAULT_CONFIG = {
+    "gitea_api": "http://localhost:3000/api/v1",
+    "repo_slug": "rockachopa/Timmy-time-dashboard",
+    "token_file": "~/.hermes/gitea_token",
+    "layer_labels_prefix": "layer:",
+}
+
+LAYER_LABELS = ["layer:triage", "layer:micro-fix", "layer:tests", "layer:economy"]
+
+
+def _load_config() -> dict:
+    """Load configuration from config file with fallback to defaults."""
+    config = DEFAULT_CONFIG.copy()
+    if CONFIG_PATH.exists():
+        try:
+            file_config = json.loads(CONFIG_PATH.read_text())
+            if "orchestrator" in file_config:
+                config.update(file_config["orchestrator"])
+        except (json.JSONDecodeError, OSError) as exc:
+            logger.debug("Could not load daily_run config: %s", exc)
+
+    # Environment variable overrides
+    if os.environ.get("TIMMY_GITEA_API"):
+        config["gitea_api"] = os.environ.get("TIMMY_GITEA_API")
+    if os.environ.get("TIMMY_REPO_SLUG"):
+        config["repo_slug"] = os.environ.get("TIMMY_REPO_SLUG")
+    if os.environ.get("TIMMY_GITEA_TOKEN"):
+        config["token"] = os.environ.get("TIMMY_GITEA_TOKEN")
+
+    return config
+
+
+def _get_token(config: dict) -> str | None:
+    """Get Gitea token from environment or file."""
+    if "token" in config:
+        return config["token"]
+
+    token_file = Path(config["token_file"]).expanduser()
+    if token_file.exists():
+        return token_file.read_text().strip()
+
+    return None
+
+
+class GiteaClient:
+    """Simple Gitea API client with graceful degradation."""
+
+    def __init__(self, config: dict, token: str | None):
+        self.api_base = config["gitea_api"].rstrip("/")
+        self.repo_slug = config["repo_slug"]
+        self.token = token
+        self._available: bool | None = None
+
+    def _headers(self) -> dict:
+        headers = {"Accept": "application/json"}
+        if self.token:
+            headers["Authorization"] = f"token {self.token}"
+        return headers
+
+    def _api_url(self, path: str) -> str:
+        return f"{self.api_base}/repos/{self.repo_slug}/{path}"
+
+    def is_available(self) -> bool:
+        """Check if Gitea API is reachable."""
+        if self._available is not None:
+            return self._available
+
+        try:
+            req = UrlRequest(
+                f"{self.api_base}/version",
+                headers=self._headers(),
+                method="GET",
+            )
+            with urlopen(req, timeout=5) as resp:
+                self._available = resp.status == 200
+                return self._available
+        except (HTTPError, URLError, TimeoutError):
+            self._available = False
+            return False
+
+    def get_paginated(self, path: str, params: dict | None = None) -> list:
+        """Fetch all pages of a paginated endpoint."""
+        all_items = []
+        page = 1
+        limit = 50
+
+        while True:
+            url = self._api_url(path)
+            query_parts = [f"limit={limit}", f"page={page}"]
+            if params:
+                for key, val in params.items():
+                    query_parts.append(f"{key}={val}")
+            url = f"{url}?{'&'.join(query_parts)}"
+
+            req = UrlRequest(url, headers=self._headers(), method="GET")
+            with urlopen(req, timeout=15) as resp:
+                batch = json.loads(resp.read())
+
+            if not batch:
+                break
+
+            all_items.extend(batch)
+            if len(batch) < limit:
+                break
+            page += 1
+
+        return all_items
+
+
+@dataclass
+class LayerMetrics:
+    """Metrics for a single layer."""
+
+    name: str
+    label: str
+    current_count: int
+    previous_count: int
+
+    @property
+    def trend(self) -> str:
+        """Return trend indicator."""
+        if self.previous_count == 0:
+            return "→" if self.current_count == 0 else "↑"
+        diff = self.current_count - self.previous_count
+        pct = (diff / self.previous_count) * 100
+        if pct > 20:
+            return "↑↑"
+        elif pct > 5:
+            return "↑"
+        elif pct < -20:
+            return "↓↓"
+        elif pct < -5:
+            return "↓"
+        return "→"
+
+    @property
+    def trend_color(self) -> str:
+        """Return color for trend (CSS variable name)."""
+        trend = self.trend
+        if trend in ("↑↑", "↑"):
+            return "var(--green)"  # More work = positive
+        elif trend in ("↓↓", "↓"):
+            return "var(--amber)"  # Less work = caution
+        return "var(--text-dim)"
+
+
+@dataclass
+class DailyRunMetrics:
+    """Complete Daily Run metrics."""
+
+    sessions_completed: int
+    sessions_previous: int
+    layers: list[LayerMetrics]
+    total_touched_current: int
+    total_touched_previous: int
+    lookback_days: int
+    generated_at: str
+
+    @property
+    def sessions_trend(self) -> str:
+        """Return sessions trend indicator."""
+        if self.sessions_previous == 0:
+            return "→" if self.sessions_completed == 0 else "↑"
+        diff = self.sessions_completed - self.sessions_previous
+        pct = (diff / self.sessions_previous) * 100
+        if pct > 20:
+            return "↑↑"
+        elif pct > 5:
+            return "↑"
+        elif pct < -20:
+            return "↓↓"
+        elif pct < -5:
+            return "↓"
+        return "→"
+
+    @property
+    def sessions_trend_color(self) -> str:
+        """Return color for sessions trend."""
+        trend = self.sessions_trend
+        if trend in ("↑↑", "↑"):
+            return "var(--green)"
+        elif trend in ("↓↓", "↓"):
+            return "var(--amber)"
+        return "var(--text-dim)"
+
+
+def _extract_layer(labels: list[dict]) -> str | None:
+    """Extract layer label from issue labels."""
+    for label in labels:
+        name = label.get("name", "")
+        if name.startswith("layer:"):
+            return name.replace("layer:", "")
+    return None
+
+
+def _load_cycle_data(days: int = 14) -> dict:
+    """Load cycle retrospective data for session counting."""
+    retro_file = REPO_ROOT / ".loop" / "retro" / "cycles.jsonl"
+    if not retro_file.exists():
+        return {"current": 0, "previous": 0}
+
+    try:
+        entries = []
+        for line in retro_file.read_text().strip().splitlines():
+            try:
+                entries.append(json.loads(line))
+            except json.JSONDecodeError:
+                continue
+
+        now = datetime.now(UTC)
+        current_cutoff = now - timedelta(days=days)
+        previous_cutoff = now - timedelta(days=days * 2)
+
+        current_count = 0
+        previous_count = 0
+
+        for entry in entries:
+            ts_str = entry.get("timestamp", "")
+            if not ts_str:
+                continue
+            try:
+                ts = datetime.fromisoformat(ts_str.replace("Z", "+00:00"))
+                if ts >= current_cutoff:
+                    if entry.get("success", False):
+                        current_count += 1
+                elif ts >= previous_cutoff:
+                    if entry.get("success", False):
+                        previous_count += 1
+            except (ValueError, TypeError):
+                continue
+
+        return {"current": current_count, "previous": previous_count}
+    except (OSError, ValueError) as exc:
+        logger.debug("Failed to load cycle data: %s", exc)
+        return {"current": 0, "previous": 0}
+
+
+def _fetch_layer_metrics(
+    client: GiteaClient, lookback_days: int = 7
+) -> tuple[list[LayerMetrics], int, int]:
+    """Fetch metrics for each layer from Gitea issues."""
+    now = datetime.now(UTC)
+    current_cutoff = now - timedelta(days=lookback_days)
+    previous_cutoff = now - timedelta(days=lookback_days * 2)
+
+    layers = []
+    total_current = 0
+    total_previous = 0
+
+    for layer_label in LAYER_LABELS:
+        layer_name = layer_label.replace("layer:", "")
+        try:
+            # Fetch all issues with this layer label (both open and closed)
+            issues = client.get_paginated(
+                "issues",
+                {"state": "all", "labels": layer_label, "limit": 100},
+            )
+
+            current_count = 0
+            previous_count = 0
+
+            for issue in issues:
+                updated_at = issue.get("updated_at", "")
+                if not updated_at:
+                    continue
+                try:
+                    updated = datetime.fromisoformat(updated_at.replace("Z", "+00:00"))
+                    if updated >= current_cutoff:
+                        current_count += 1
+                    elif updated >= previous_cutoff:
+                        previous_count += 1
+                except (ValueError, TypeError):
+                    continue
+
+            layers.append(
+                LayerMetrics(
+                    name=layer_name,
+                    label=layer_label,
+                    current_count=current_count,
+                    previous_count=previous_count,
+                )
+            )
+            total_current += current_count
+            total_previous += previous_count
+
+        except (HTTPError, URLError) as exc:
+            logger.debug("Failed to fetch issues for %s: %s", layer_label, exc)
+            layers.append(
+                LayerMetrics(
+                    name=layer_name,
+                    label=layer_label,
+                    current_count=0,
+                    previous_count=0,
+                )
+            )
+
+    return layers, total_current, total_previous
+
+
+def _get_metrics(lookback_days: int = 7) -> DailyRunMetrics | None:
+    """Get Daily Run metrics from Gitea API."""
+    config = _load_config()
+    token = _get_token(config)
+    client = GiteaClient(config, token)
+
+    if not client.is_available():
+        logger.debug("Gitea API not available for Daily Run metrics")
+        return None
+
+    try:
+        # Get layer metrics from issues
+        layers, total_current, total_previous = _fetch_layer_metrics(client, lookback_days)
+
+        # Get session data from cycle retrospectives
+        cycle_data = _load_cycle_data(days=lookback_days)
+
+        return DailyRunMetrics(
+            sessions_completed=cycle_data["current"],
+            sessions_previous=cycle_data["previous"],
+            layers=layers,
+            total_touched_current=total_current,
+            total_touched_previous=total_previous,
+            lookback_days=lookback_days,
+            generated_at=datetime.now(UTC).isoformat(),
+        )
+    except Exception as exc:
+        logger.debug("Error fetching Daily Run metrics: %s", exc)
+        return None
+
+
+@router.get("/daily-run/metrics", response_class=JSONResponse)
+async def daily_run_metrics_api(lookback_days: int = 7):
+    """Return Daily Run metrics as JSON API."""
+    metrics = _get_metrics(lookback_days)
+    if not metrics:
+        return JSONResponse(
+            {"error": "Gitea API unavailable", "status": "unavailable"},
+            status_code=503,
+        )
+
+    # Check for quest completions based on Daily Run metrics
+    quest_rewards = []
+    try:
+        from dashboard.routes.quests import check_daily_run_quests
+
+        quest_rewards = await check_daily_run_quests(agent_id="system")
+    except Exception as exc:
+        logger.debug("Quest checking failed: %s", exc)
+
+    return JSONResponse(
+        {
+            "status": "ok",
+            "lookback_days": metrics.lookback_days,
+            "sessions": {
+                "completed": metrics.sessions_completed,
+                "previous": metrics.sessions_previous,
+                "trend": metrics.sessions_trend,
+            },
+            "layers": [
+                {
+                    "name": layer.name,
+                    "label": layer.label,
+                    "current": layer.current_count,
+                    "previous": layer.previous_count,
+                    "trend": layer.trend,
+                }
+                for layer in metrics.layers
+            ],
+            "totals": {
+                "current": metrics.total_touched_current,
+                "previous": metrics.total_touched_previous,
+            },
+            "generated_at": metrics.generated_at,
+            "quest_rewards": quest_rewards,
+        }
+    )
+
+
+@router.get("/daily-run/panel", response_class=HTMLResponse)
+async def daily_run_panel(request: Request, lookback_days: int = 7):
+    """Return Daily Run metrics panel HTML for HTMX polling."""
+    metrics = _get_metrics(lookback_days)
+
+    # Build Gitea URLs for filtered issue lists
+    config = _load_config()
+    repo_slug = config.get("repo_slug", "rockachopa/Timmy-time-dashboard")
+    gitea_base = config.get("gitea_api", "http://localhost:3000/api/v1").replace("/api/v1", "")
+
+    # Logbook URL (link to issues with any layer label)
+    layer_labels = ",".join(LAYER_LABELS)
+    logbook_url = f"{gitea_base}/{repo_slug}/issues?labels={layer_labels}&state=all"
+
+    # Layer-specific URLs
+    layer_urls = {
+        layer: f"{gitea_base}/{repo_slug}/issues?labels=layer:{layer}&state=all"
+        for layer in ["triage", "micro-fix", "tests", "economy"]
+    }
+
+    return templates.TemplateResponse(
+        request,
+        "partials/daily_run_panel.html",
+        {
+            "metrics": metrics,
+            "logbook_url": logbook_url,
+            "layer_urls": layer_urls,
+            "gitea_available": metrics is not None,
+        },
+    )

src/dashboard/routes/db_explorer.py

@@ -75,6 +75,7 @@ def _query_database(db_path: str) -> dict:
                         "truncated": count > MAX_ROWS,
                     }
                 except Exception as exc:
+                    logger.exception("Failed to query table %s", table_name)
                     result["tables"][table_name] = {
                         "error": str(exc),
                         "columns": [],
@@ -83,6 +84,7 @@ def _query_database(db_path: str) -> dict:
                         "truncated": False,
                     }
     except Exception as exc:
+        logger.exception("Failed to query database %s", db_path)
         result["error"] = str(exc)
 
     return result

src/dashboard/routes/grok.py

@@ -135,6 +135,7 @@ def _run_grok_query(message: str) -> dict:
         result = backend.run(message)
         return {"response": f"**[Grok]{invoice_note}:** {result.content}", "error": None}
     except Exception as exc:
+        logger.exception("Grok query failed")
         return {"response": None, "error": f"Grok error: {exc}"}
 
 
@@ -193,6 +194,7 @@ async def grok_stats():
             "model": settings.grok_default_model,
         }
     except Exception as exc:
+        logger.exception("Failed to load Grok stats")
         return {"error": str(exc)}
 
 

src/dashboard/routes/health.py

@@ -65,7 +65,7 @@ def _check_ollama_sync() -> DependencyStatus:
     try:
         import urllib.request
 
-        url = settings.ollama_url.replace("localhost", "127.0.0.1")
+        url = settings.normalized_ollama_url
         req = urllib.request.Request(
             f"{url}/api/tags",
             method="GET",
@@ -148,6 +148,7 @@ def _check_sqlite() -> DependencyStatus:
             details={"path": str(db_path)},
         )
     except Exception as exc:
+        logger.exception("SQLite health check failed")
         return DependencyStatus(
             name="SQLite Database",
             status="unavailable",
@@ -274,3 +275,54 @@ async def component_status():
         },
         "timestamp": datetime.now(UTC).isoformat(),
     }
+
+
+@router.get("/health/snapshot")
+async def health_snapshot():
+    """Quick health snapshot before coding.
+
+    Returns a concise status summary including:
+    - CI pipeline status (pass/fail/unknown)
+    - Critical issues count (P0/P1)
+    - Test flakiness rate
+    - Token economy temperature
+
+    Fast execution (< 5 seconds) for pre-work checks.
+    Refs: #710
+    """
+    import sys
+    from pathlib import Path
+
+    # Import the health snapshot module
+    snapshot_path = Path(settings.repo_root) / "timmy_automations" / "daily_run"
+    if str(snapshot_path) not in sys.path:
+        sys.path.insert(0, str(snapshot_path))
+
+    try:
+        from health_snapshot import generate_snapshot, get_token, load_config
+
+        config = load_config()
+        token = get_token(config)
+
+        # Run the health snapshot (in thread to avoid blocking)
+        snapshot = await asyncio.to_thread(generate_snapshot, config, token)
+
+        return snapshot.to_dict()
+    except Exception as exc:
+        logger.warning("Health snapshot failed: %s", exc)
+        # Return graceful fallback
+        return {
+            "timestamp": datetime.now(UTC).isoformat(),
+            "overall_status": "unknown",
+            "error": str(exc),
+            "ci": {"status": "unknown", "message": "Snapshot failed"},
+            "issues": {"count": 0, "p0_count": 0, "p1_count": 0, "issues": []},
+            "flakiness": {
+                "status": "unknown",
+                "recent_failures": 0,
+                "recent_cycles": 0,
+                "failure_rate": 0.0,
+                "message": "Snapshot failed",
+            },
+            "tokens": {"status": "unknown", "message": "Snapshot failed"},
+        }

src/dashboard/routes/quests.py

@@ -0,0 +1,377 @@
+"""Quest system routes for agent token rewards.
+
+Provides API endpoints for:
+- Listing quests and their status
+- Claiming quest rewards
+- Getting quest leaderboard
+- Quest progress tracking
+"""
+
+from __future__ import annotations
+
+import logging
+from typing import Any
+
+from fastapi import APIRouter, Request
+from fastapi.responses import HTMLResponse, JSONResponse
+from pydantic import BaseModel
+
+from dashboard.templating import templates
+from timmy.quest_system import (
+    QuestStatus,
+    auto_evaluate_all_quests,
+    claim_quest_reward,
+    evaluate_quest_progress,
+    get_active_quests,
+    get_agent_quests_status,
+    get_quest_definition,
+    get_quest_leaderboard,
+    load_quest_config,
+)
+
+logger = logging.getLogger(__name__)
+
+router = APIRouter(prefix="/quests", tags=["quests"])
+
+
+class ClaimQuestRequest(BaseModel):
+    """Request to claim a quest reward."""
+
+    agent_id: str
+    quest_id: str
+
+
+class EvaluateQuestRequest(BaseModel):
+    """Request to manually evaluate quest progress."""
+
+    agent_id: str
+    quest_id: str
+
+
+# ---------------------------------------------------------------------------
+# API Endpoints
+# ---------------------------------------------------------------------------
+
+
+@router.get("/api/definitions")
+async def get_quest_definitions_api() -> JSONResponse:
+    """Get all quest definitions.
+
+    Returns:
+        JSON list of all quest definitions with their criteria.
+    """
+    definitions = get_active_quests()
+    return JSONResponse(
+        {
+            "quests": [
+                {
+                    "id": q.id,
+                    "name": q.name,
+                    "description": q.description,
+                    "reward_tokens": q.reward_tokens,
+                    "type": q.quest_type.value,
+                    "repeatable": q.repeatable,
+                    "cooldown_hours": q.cooldown_hours,
+                    "criteria": q.criteria,
+                }
+                for q in definitions
+            ]
+        }
+    )
+
+
+@router.get("/api/status/{agent_id}")
+async def get_agent_quest_status(agent_id: str) -> JSONResponse:
+    """Get quest status for a specific agent.
+
+    Returns:
+        Complete quest status including progress, completion counts,
+        and tokens earned.
+    """
+    status = get_agent_quests_status(agent_id)
+    return JSONResponse(status)
+
+
+@router.post("/api/claim")
+async def claim_quest_reward_api(request: ClaimQuestRequest) -> JSONResponse:
+    """Claim a quest reward for an agent.
+
+    The quest must be completed but not yet claimed.
+    """
+    reward = claim_quest_reward(request.quest_id, request.agent_id)
+
+    if not reward:
+        return JSONResponse(
+            {
+                "success": False,
+                "error": "Quest not completed, already claimed, or on cooldown",
+            },
+            status_code=400,
+        )
+
+    return JSONResponse(
+        {
+            "success": True,
+            "reward": reward,
+        }
+    )
+
+
+@router.post("/api/evaluate")
+async def evaluate_quest_api(request: EvaluateQuestRequest) -> JSONResponse:
+    """Manually evaluate quest progress with provided context.
+
+    This is useful for testing or when the quest completion
+    needs to be triggered manually.
+    """
+    quest = get_quest_definition(request.quest_id)
+    if not quest:
+        return JSONResponse(
+            {"success": False, "error": "Quest not found"},
+            status_code=404,
+        )
+
+    # Build evaluation context based on quest type
+    context = await _build_evaluation_context(quest)
+
+    progress = evaluate_quest_progress(request.quest_id, request.agent_id, context)
+
+    if not progress:
+        return JSONResponse(
+            {"success": False, "error": "Failed to evaluate quest"},
+            status_code=500,
+        )
+
+    # Auto-claim if completed
+    reward = None
+    if progress.status == QuestStatus.COMPLETED:
+        reward = claim_quest_reward(request.quest_id, request.agent_id)
+
+    return JSONResponse(
+        {
+            "success": True,
+            "progress": progress.to_dict(),
+            "reward": reward,
+            "completed": progress.status == QuestStatus.COMPLETED,
+        }
+    )
+
+
+@router.get("/api/leaderboard")
+async def get_leaderboard_api() -> JSONResponse:
+    """Get the quest completion leaderboard.
+
+    Returns agents sorted by total tokens earned.
+    """
+    leaderboard = get_quest_leaderboard()
+    return JSONResponse(
+        {
+            "leaderboard": leaderboard,
+        }
+    )
+
+
+@router.post("/api/reload")
+async def reload_quest_config_api() -> JSONResponse:
+    """Reload quest configuration from quests.yaml.
+
+    Useful for applying quest changes without restarting.
+    """
+    definitions, quest_settings = load_quest_config()
+    return JSONResponse(
+        {
+            "success": True,
+            "quests_loaded": len(definitions),
+            "settings": quest_settings,
+        }
+    )
+
+
+# ---------------------------------------------------------------------------
+# Dashboard UI Endpoints
+# ---------------------------------------------------------------------------
+
+
+@router.get("", response_class=HTMLResponse)
+async def quests_dashboard(request: Request) -> HTMLResponse:
+    """Main quests dashboard page."""
+    return templates.TemplateResponse(
+        request,
+        "quests.html",
+        {"agent_id": "current_user"},
+    )
+
+
+@router.get("/panel/{agent_id}", response_class=HTMLResponse)
+async def quests_panel(request: Request, agent_id: str) -> HTMLResponse:
+    """Quest panel for HTMX partial updates."""
+    status = get_agent_quests_status(agent_id)
+    return templates.TemplateResponse(
+        request,
+        "partials/quests_panel.html",
+        {
+            "agent_id": agent_id,
+            "quests": status["quests"],
+            "total_tokens": status["total_tokens_earned"],
+            "completed_count": status["total_quests_completed"],
+        },
+    )
+
+
+# ---------------------------------------------------------------------------
+# Internal Functions
+# ---------------------------------------------------------------------------
+
+
+async def _build_evaluation_context(quest) -> dict[str, Any]:
+    """Build evaluation context for a quest based on its type."""
+    context: dict[str, Any] = {}
+
+    if quest.quest_type.value == "issue_count":
+        # Fetch closed issues with relevant labels
+        context["closed_issues"] = await _fetch_closed_issues(
+            quest.criteria.get("issue_labels", [])
+        )
+
+    elif quest.quest_type.value == "issue_reduce":
+        # Fetch current and previous issue counts
+        labels = quest.criteria.get("issue_labels", [])
+        context["current_issue_count"] = await _fetch_open_issue_count(labels)
+        context["previous_issue_count"] = await _fetch_previous_issue_count(
+            labels, quest.criteria.get("lookback_days", 7)
+        )
+
+    elif quest.quest_type.value == "daily_run":
+        # Fetch Daily Run metrics
+        metrics = await _fetch_daily_run_metrics()
+        context["sessions_completed"] = metrics.get("sessions_completed", 0)
+
+    return context
+
+
+async def _fetch_closed_issues(labels: list[str]) -> list[dict]:
+    """Fetch closed issues matching the given labels."""
+    try:
+        from dashboard.routes.daily_run import GiteaClient, _load_config
+
+        config = _load_config()
+        token = _get_gitea_token(config)
+        client = GiteaClient(config, token)
+
+        if not client.is_available():
+            return []
+
+        # Build label filter
+        label_filter = ",".join(labels) if labels else ""
+
+        issues = client.get_paginated(
+            "issues",
+            {"state": "closed", "labels": label_filter, "limit": 100},
+        )
+
+        return issues
+    except Exception as exc:
+        logger.debug("Failed to fetch closed issues: %s", exc)
+        return []
+
+
+async def _fetch_open_issue_count(labels: list[str]) -> int:
+    """Fetch count of open issues with given labels."""
+    try:
+        from dashboard.routes.daily_run import GiteaClient, _load_config
+
+        config = _load_config()
+        token = _get_gitea_token(config)
+        client = GiteaClient(config, token)
+
+        if not client.is_available():
+            return 0
+
+        label_filter = ",".join(labels) if labels else ""
+
+        issues = client.get_paginated(
+            "issues",
+            {"state": "open", "labels": label_filter, "limit": 100},
+        )
+
+        return len(issues)
+    except Exception as exc:
+        logger.debug("Failed to fetch open issue count: %s", exc)
+        return 0
+
+
+async def _fetch_previous_issue_count(labels: list[str], lookback_days: int) -> int:
+    """Fetch previous issue count (simplified - uses current for now)."""
+    # This is a simplified implementation
+    # In production, you'd query historical data
+    return await _fetch_open_issue_count(labels)
+
+
+async def _fetch_daily_run_metrics() -> dict[str, Any]:
+    """Fetch Daily Run metrics."""
+    try:
+        from dashboard.routes.daily_run import _get_metrics
+
+        metrics = _get_metrics(lookback_days=7)
+        if metrics:
+            return {
+                "sessions_completed": metrics.sessions_completed,
+                "sessions_previous": metrics.sessions_previous,
+            }
+    except Exception as exc:
+        logger.debug("Failed to fetch Daily Run metrics: %s", exc)
+
+    return {"sessions_completed": 0, "sessions_previous": 0}
+
+
+def _get_gitea_token(config: dict) -> str | None:
+    """Get Gitea token from config."""
+    if "token" in config:
+        return config["token"]
+
+    from pathlib import Path
+
+    token_file = Path(config.get("token_file", "~/.hermes/gitea_token")).expanduser()
+    if token_file.exists():
+        return token_file.read_text().strip()
+
+    return None
+
+
+# ---------------------------------------------------------------------------
+# Daily Run Integration
+# ---------------------------------------------------------------------------
+
+
+async def check_daily_run_quests(agent_id: str = "system") -> list[dict]:
+    """Check and award Daily Run related quests.
+
+    Called by the Daily Run system when metrics are updated.
+
+    Returns:
+        List of rewards awarded
+    """
+    # Check if auto-detect is enabled
+    _, quest_settings = load_quest_config()
+    if not quest_settings.get("auto_detect_on_daily_run", True):
+        return []
+
+    # Build context from Daily Run metrics
+    metrics = await _fetch_daily_run_metrics()
+    context = {
+        "sessions_completed": metrics.get("sessions_completed", 0),
+        "sessions_previous": metrics.get("sessions_previous", 0),
+    }
+
+    # Add closed issues for issue_count quests
+    active_quests = get_active_quests()
+    for quest in active_quests:
+        if quest.quest_type.value == "issue_count":
+            labels = quest.criteria.get("issue_labels", [])
+            context["closed_issues"] = await _fetch_closed_issues(labels)
+            break  # Only need to fetch once
+
+    # Evaluate all quests
+    rewards = auto_evaluate_all_quests(agent_id, context)
+
+    return rewards

src/dashboard/routes/system.py

@@ -16,52 +16,11 @@ router = APIRouter(tags=["system"])
 
 @router.get("/lightning/ledger", response_class=HTMLResponse)
 async def lightning_ledger(request: Request):
-    """Ledger and balance page."""
-    # Mock data for now, as this seems to be a UI-first feature
-    balance = {
-        "available_sats": 1337,
-        "incoming_total_sats": 2000,
-        "outgoing_total_sats": 663,
-        "fees_paid_sats": 5,
-        "net_sats": 1337,
-        "pending_incoming_sats": 0,
-        "pending_outgoing_sats": 0,
-    }
+    """Ledger and balance page backed by the in-memory Lightning ledger."""
+    from lightning.ledger import get_balance, get_transactions
 
-    # Mock transactions
-    from collections import namedtuple
-    from enum import Enum
-
-    class TxType(Enum):
-        incoming = "incoming"
-        outgoing = "outgoing"
-
-    class TxStatus(Enum):
-        completed = "completed"
-        pending = "pending"
-
-    Tx = namedtuple(
-        "Tx", ["tx_type", "status", "amount_sats", "payment_hash", "memo", "created_at"]
-    )
-
-    transactions = [
-        Tx(
-            TxType.outgoing,
-            TxStatus.completed,
-            50,
-            "hash1",
-            "Model inference",
-            "2026-03-04 10:00:00",
-        ),
-        Tx(
-            TxType.incoming,
-            TxStatus.completed,
-            1000,
-            "hash2",
-            "Manual deposit",
-            "2026-03-03 15:00:00",
-        ),
-    ]
+    balance = get_balance()
+    transactions = get_transactions()
 
     return templates.TemplateResponse(
         request,
@@ -70,7 +29,7 @@ async def lightning_ledger(request: Request):
             "balance": balance,
             "transactions": transactions,
             "tx_types": ["incoming", "outgoing"],
-            "tx_statuses": ["completed", "pending"],
+            "tx_statuses": ["pending", "settled", "failed", "expired"],
             "filter_type": None,
             "filter_status": None,
             "stats": {},
@@ -166,7 +125,7 @@ async def api_briefing_status():
         if cached:
             last_generated = cached.generated_at.isoformat()
     except Exception:
-        pass
+        logger.debug("Failed to read briefing cache")
 
     return JSONResponse(
         {
@@ -190,6 +149,7 @@ async def api_memory_status():
         stats = get_memory_stats()
         indexed_files = stats.get("total_entries", 0)
     except Exception:
+        logger.debug("Failed to get memory stats")
         indexed_files = 0
 
     return JSONResponse(
@@ -215,7 +175,7 @@ async def api_swarm_status():
             ).fetchone()
             pending_tasks = row["cnt"] if row else 0
     except Exception:
-        pass
+        logger.debug("Failed to count pending tasks")
 
     return JSONResponse(
         {

src/dashboard/routes/tasks.py

@@ -5,7 +5,7 @@ import sqlite3
 import uuid
 from collections.abc import Generator
 from contextlib import closing, contextmanager
-from datetime import datetime
+from datetime import UTC, datetime
 from pathlib import Path
 
 from fastapi import APIRouter, Form, HTTPException, Request
@@ -219,7 +219,7 @@ async def create_task_form(
         raise HTTPException(status_code=400, detail="Task title cannot be empty")
 
     task_id = str(uuid.uuid4())
-    now = datetime.utcnow().isoformat()
+    now = datetime.now(UTC).isoformat()
     priority = priority if priority in VALID_PRIORITIES else "normal"
 
     with _get_db() as db:
@@ -287,7 +287,7 @@ async def modify_task(
 async def _set_status(request: Request, task_id: str, new_status: str):
     """Helper to update status and return refreshed task card."""
     completed_at = (
-        datetime.utcnow().isoformat() if new_status in ("completed", "vetoed", "failed") else None
+        datetime.now(UTC).isoformat() if new_status in ("completed", "vetoed", "failed") else None
     )
     with _get_db() as db:
         db.execute(
@@ -316,7 +316,7 @@ async def api_create_task(request: Request):
         raise HTTPException(422, "title is required")
 
     task_id = str(uuid.uuid4())
-    now = datetime.utcnow().isoformat()
+    now = datetime.now(UTC).isoformat()
     priority = body.get("priority", "normal")
     if priority not in VALID_PRIORITIES:
         priority = "normal"
@@ -358,7 +358,7 @@ async def api_update_status(task_id: str, request: Request):
         raise HTTPException(422, f"Invalid status. Must be one of: {VALID_STATUSES}")
 
     completed_at = (
-        datetime.utcnow().isoformat() if new_status in ("completed", "vetoed", "failed") else None
+        datetime.now(UTC).isoformat() if new_status in ("completed", "vetoed", "failed") else None
     )
     with _get_db() as db:
         db.execute(

src/dashboard/routes/tower.py

@@ -0,0 +1,108 @@
+"""Tower dashboard — real-time Spark visualization via WebSocket.
+
+GET  /tower     — HTML Tower dashboard (Thinking / Predicting / Advising)
+WS   /tower/ws  — WebSocket stream of Spark engine state updates
+"""
+
+import asyncio
+import json
+import logging
+
+from fastapi import APIRouter, Request, WebSocket
+from fastapi.responses import HTMLResponse
+
+from dashboard.templating import templates
+from spark.engine import spark_engine
+
+logger = logging.getLogger(__name__)
+
+router = APIRouter(prefix="/tower", tags=["tower"])
+
+_PUSH_INTERVAL = 5  # seconds between state broadcasts
+
+
+def _spark_snapshot() -> dict:
+    """Build a JSON-serialisable snapshot of Spark state."""
+    status = spark_engine.status()
+
+    timeline = spark_engine.get_timeline(limit=10)
+    events = []
+    for ev in timeline:
+        entry = {
+            "event_type": ev.event_type,
+            "description": ev.description,
+            "importance": ev.importance,
+            "created_at": ev.created_at,
+        }
+        if ev.agent_id:
+            entry["agent_id"] = ev.agent_id[:8]
+        if ev.task_id:
+            entry["task_id"] = ev.task_id[:8]
+        try:
+            entry["data"] = json.loads(ev.data)
+        except (json.JSONDecodeError, TypeError):
+            entry["data"] = {}
+        events.append(entry)
+
+    predictions = spark_engine.get_predictions(limit=5)
+    preds = []
+    for p in predictions:
+        pred = {
+            "task_id": p.task_id[:8] if p.task_id else "?",
+            "accuracy": p.accuracy,
+            "evaluated": p.evaluated_at is not None,
+            "created_at": p.created_at,
+        }
+        try:
+            pred["predicted"] = json.loads(p.predicted_value)
+        except (json.JSONDecodeError, TypeError):
+            pred["predicted"] = {}
+        preds.append(pred)
+
+    advisories = spark_engine.get_advisories()
+    advs = [
+        {
+            "category": a.category,
+            "priority": a.priority,
+            "title": a.title,
+            "detail": a.detail,
+            "suggested_action": a.suggested_action,
+        }
+        for a in advisories
+    ]
+
+    return {
+        "type": "spark_state",
+        "status": status,
+        "events": events,
+        "predictions": preds,
+        "advisories": advs,
+    }
+
+
+@router.get("", response_class=HTMLResponse)
+async def tower_ui(request: Request):
+    """Render the Tower dashboard page."""
+    snapshot = _spark_snapshot()
+    return templates.TemplateResponse(
+        request,
+        "tower.html",
+        {"snapshot": snapshot},
+    )
+
+
+@router.websocket("/ws")
+async def tower_ws(websocket: WebSocket) -> None:
+    """Stream Spark state snapshots to the Tower dashboard."""
+    await websocket.accept()
+    logger.info("Tower WS connected")
+
+    try:
+        # Send initial snapshot
+        await websocket.send_text(json.dumps(_spark_snapshot()))
+
+        while True:
+            await asyncio.sleep(_PUSH_INTERVAL)
+            await websocket.send_text(json.dumps(_spark_snapshot()))
+    except Exception:
+        logger.debug("Tower WS disconnected")

src/dashboard/routes/voice.py

@@ -59,6 +59,7 @@ async def tts_speak(text: str = Form(...)):
         voice_tts.speak(text)
         return {"spoken": True, "text": text}
     except Exception as exc:
+        logger.exception("TTS speak failed")
         return {"spoken": False, "reason": str(exc)}
 
 

src/dashboard/routes/work_orders.py

@@ -5,7 +5,7 @@ import sqlite3
 import uuid
 from collections.abc import Generator
 from contextlib import closing, contextmanager
-from datetime import datetime
+from datetime import UTC, datetime
 from pathlib import Path
 
 from fastapi import APIRouter, Form, HTTPException, Request
@@ -144,7 +144,7 @@ async def submit_work_order(
     related_files: str = Form(""),
 ):
     wo_id = str(uuid.uuid4())
-    now = datetime.utcnow().isoformat()
+    now = datetime.now(UTC).isoformat()
     priority = priority if priority in PRIORITIES else "medium"
     category = category if category in CATEGORIES else "suggestion"
 
@@ -211,7 +211,7 @@ async def active_partial(request: Request):
 
 async def _update_status(request: Request, wo_id: str, new_status: str, **extra):
     completed_at = (
-        datetime.utcnow().isoformat() if new_status in ("completed", "rejected") else None
+        datetime.now(UTC).isoformat() if new_status in ("completed", "rejected") else None
     )
     with _get_db() as db:
         sets = ["status=?", "completed_at=COALESCE(?, completed_at)"]

src/dashboard/templates/index.html

@@ -21,6 +21,11 @@
         </div>
       {% endcall %}
 
+      <!-- Daily Run Metrics (HTMX polled) -->
+      {% call panel("DAILY RUN", hx_get="/daily-run/panel", hx_trigger="every 60s") %}
+        <div class="mc-loading-placeholder">LOADING...</div>
+      {% endcall %}
+
     </div>
 
     <!-- Main panel — swappable via HTMX; defaults to Timmy on load -->

src/dashboard/templates/mission_control.html

@@ -138,6 +138,47 @@
     </div>
 </div>
 
+<!-- Spark Intelligence -->
+{% from "macros.html" import panel %}
+<div class="mc-card-spaced">
+  <div class="card">
+    <div class="card-header">
+      <h2 class="card-title">Spark Intelligence</h2>
+      <div>
+        <span class="badge" id="spark-status-badge">Loading...</span>
+      </div>
+    </div>
+    <div class="grid grid-3">
+      <div class="stat">
+        <div class="stat-value" id="spark-events">-</div>
+        <div class="stat-label">Events</div>
+      </div>
+      <div class="stat">
+        <div class="stat-value" id="spark-memories">-</div>
+        <div class="stat-label">Memories</div>
+      </div>
+      <div class="stat">
+        <div class="stat-value" id="spark-predictions">-</div>
+        <div class="stat-label">Predictions</div>
+      </div>
+    </div>
+  </div>
+  <div class="grid grid-2 mc-section-gap">
+    {% call panel("SPARK TIMELINE", id="spark-timeline-panel",
+                  hx_get="/spark/timeline",
+                  hx_trigger="load, every 10s") %}
+      <div class="spark-timeline-scroll">
+        <p class="chat-history-placeholder">Loading timeline...</p>
+      </div>
+    {% endcall %}
+    {% call panel("SPARK INSIGHTS", id="spark-insights-panel",
+                  hx_get="/spark/insights",
+                  hx_trigger="load, every 30s") %}
+      <p class="chat-history-placeholder">Loading insights...</p>
+    {% endcall %}
+  </div>
+</div>
+
 <!-- Chat History -->
 <div class="card mc-card-spaced">
     <div class="card-header">
@@ -428,7 +469,34 @@ async function loadGrokStats() {
     }
 }
 
+// Load Spark status
+async function loadSparkStatus() {
+    try {
+        var response = await fetch('/spark');
+        var data = await response.json();
+        var st = data.status || {};
+
+        document.getElementById('spark-events').textContent = st.total_events || 0;
+        document.getElementById('spark-memories').textContent = st.total_memories || 0;
+        document.getElementById('spark-predictions').textContent = st.total_predictions || 0;
+
+        var badge = document.getElementById('spark-status-badge');
+        if (st.total_events > 0) {
+            badge.textContent = 'Active';
+            badge.className = 'badge badge-success';
+        } else {
+            badge.textContent = 'Idle';
+            badge.className = 'badge badge-warning';
+        }
+    } catch (error) {
+        var badge = document.getElementById('spark-status-badge');
+        badge.textContent = 'Offline';
+        badge.className = 'badge badge-danger';
+    }
+}
+
 // Initial load
+loadSparkStatus();
 loadSovereignty();
 loadHealth();
 loadSwarmStats();
@@ -442,5 +510,6 @@ setInterval(loadHealth, 10000);
 setInterval(loadSwarmStats, 5000);
 setInterval(updateHeartbeat, 5000);
 setInterval(loadGrokStats, 10000);
+setInterval(loadSparkStatus, 15000);
 </script>
 {% endblock %}

src/dashboard/templates/partials/daily_run_panel.html

@@ -0,0 +1,54 @@
+<div class="card-header mc-panel-header">// DAILY RUN METRICS</div>
+<div class="card-body p-3">
+  {% if not gitea_available %}
+  <div class="mc-muted" style="font-size: 0.85rem; padding: 8px 0;">
+    <span style="color: var(--amber);">⚠</span> Gitea API unavailable
+  </div>
+  {% else %}
+  {% set m = metrics %}
+
+  <!-- Sessions summary -->
+  <div class="dr-section" style="margin-bottom: 16px;">
+    <div class="dr-row" style="display: flex; justify-content: space-between; align-items: center; margin-bottom: 8px;">
+      <span class="dr-label" style="font-size: 0.85rem; color: var(--text-dim);">Sessions ({{ m.lookback_days }}d)</span>
+      <a href="{{ logbook_url }}" target="_blank" class="dr-link" style="font-size: 0.75rem; color: var(--green); text-decoration: none;">
+        Logbook →
+      </a>
+    </div>
+    <div class="dr-stat" style="display: flex; align-items: baseline; gap: 8px;">
+      <span class="dr-value" style="font-size: 1.5rem; font-weight: 600; color: var(--text-bright);">{{ m.sessions_completed }}</span>
+      <span class="dr-trend" style="font-size: 0.9rem; color: {{ m.sessions_trend_color }};">{{ m.sessions_trend }}</span>
+      <span class="dr-prev" style="font-size: 0.75rem; color: var(--text-dim);">vs {{ m.sessions_previous }} prev</span>
+    </div>
+  </div>
+
+  <!-- Layer breakdown -->
+  <div class="dr-section">
+    <div class="dr-label" style="font-size: 0.85rem; color: var(--text-dim); margin-bottom: 8px;">Issues by Layer</div>
+    <div class="dr-layers" style="display: flex; flex-direction: column; gap: 6px;">
+      {% for layer in m.layers %}
+      <div class="dr-layer-row" style="display: flex; justify-content: space-between; align-items: center;">
+        <a href="{{ layer_urls[layer.name] }}" target="_blank" class="dr-layer-name" style="font-size: 0.8rem; color: var(--text); text-decoration: none; text-transform: capitalize;">
+          {{ layer.name.replace('-', ' ') }}
+        </a>
+        <div class="dr-layer-stat" style="display: flex; align-items: center; gap: 6px;">
+          <span class="dr-layer-value" style="font-size: 0.9rem; font-weight: 500; color: var(--text-bright);">{{ layer.current_count }}</span>
+          <span class="dr-layer-trend" style="font-size: 0.75rem; color: {{ layer.trend_color }}; width: 18px; text-align: center;">{{ layer.trend }}</span>
+        </div>
+      </div>
+      {% endfor %}
+    </div>
+  </div>
+
+  <!-- Total touched -->
+  <div class="dr-section" style="margin-top: 12px; padding-top: 12px; border-top: 1px solid var(--border);">
+    <div class="dr-row" style="display: flex; justify-content: space-between; align-items: center;">
+      <span class="dr-label" style="font-size: 0.8rem; color: var(--text-dim);">Total Issues Touched</span>
+      <div class="dr-total-stat" style="display: flex; align-items: center; gap: 6px;">
+        <span class="dr-total-value" style="font-size: 1rem; font-weight: 600; color: var(--text-bright);">{{ m.total_touched_current }}</span>
+        <span class="dr-total-prev" style="font-size: 0.7rem; color: var(--text-dim);">/ {{ m.total_touched_previous }} prev</span>
+      </div>
+    </div>
+  </div>
+  {% endif %}
+</div>

src/dashboard/templates/partials/quests_panel.html

@@ -0,0 +1,80 @@
+{% from "macros.html" import panel %}
+
+<div class="quests-summary mb-4">
+    <div class="row">
+        <div class="col-md-4">
+            <div class="stat-card">
+                <div class="stat-value">{{ total_tokens }}</div>
+                <div class="stat-label">Tokens Earned</div>
+            </div>
+        </div>
+        <div class="col-md-4">
+            <div class="stat-card">
+                <div class="stat-value">{{ completed_count }}</div>
+                <div class="stat-label">Quests Completed</div>
+            </div>
+        </div>
+        <div class="col-md-4">
+            <div class="stat-card">
+                <div class="stat-value">{{ quests|selectattr('enabled', 'equalto', true)|list|length }}</div>
+                <div class="stat-label">Active Quests</div>
+            </div>
+        </div>
+    </div>
+</div>
+
+<div class="quests-list">
+    {% for quest in quests %}
+    {% if quest.enabled %}
+    <div class="quest-card quest-status-{{ quest.status }}">
+        <div class="quest-header">
+            <h5 class="quest-name">{{ quest.name }}</h5>
+            <span class="quest-reward">+{{ quest.reward_tokens }} ⚡</span>
+        </div>
+        <p class="quest-description">{{ quest.description }}</p>
+
+        <div class="quest-progress">
+            {% if quest.status == 'completed' %}
+            <div class="progress">
+                <div class="progress-bar bg-success" style="width: 100%"></div>
+            </div>
+            <span class="quest-status-badge completed">Completed</span>
+            {% elif quest.status == 'claimed' %}
+            <div class="progress">
+                <div class="progress-bar bg-success" style="width: 100%"></div>
+            </div>
+            <span class="quest-status-badge claimed">Reward Claimed</span>
+            {% elif quest.on_cooldown %}
+            <div class="progress">
+                <div class="progress-bar bg-secondary" style="width: 100%"></div>
+            </div>
+            <span class="quest-status-badge cooldown">
+                Cooldown: {{ quest.cooldown_hours_remaining }}h remaining
+            </span>
+            {% else %}
+            <div class="progress">
+                <div class="progress-bar" style="width: {{ (quest.current_value / quest.target_value * 100)|int }}%"></div>
+            </div>
+            <span class="quest-progress-text">{{ quest.current_value }} / {{ quest.target_value }}</span>
+            {% endif %}
+        </div>
+
+        <div class="quest-meta">
+            <span class="quest-type">{{ quest.type }}</span>
+            {% if quest.repeatable %}
+            <span class="quest-repeatable">↻ Repeatable</span>
+            {% endif %}
+            {% if quest.completion_count > 0 %}
+            <span class="quest-completions">Completed {{ quest.completion_count }} time{% if quest.completion_count != 1 %}s{% endif %}</span>
+            {% endif %}
+        </div>
+    </div>
+    {% endif %}
+    {% endfor %}
+</div>
+
+{% if not quests|selectattr('enabled', 'equalto', true)|list|length %}
+<div class="alert alert-info">
+    No active quests available. Check back later or contact an administrator.
+</div>
+{% endif %}

src/dashboard/templates/quests.html

@@ -0,0 +1,50 @@
+{% extends "base.html" %}
+
+{% block title %}Quests — Mission Control{% endblock %}
+
+{% block content %}
+<div class="container-fluid">
+    <div class="row">
+        <div class="col-12">
+            <h1 class="mc-title">Token Quests</h1>
+            <p class="mc-subtitle">Complete quests to earn bonus tokens</p>
+        </div>
+    </div>
+
+    <div class="row mt-4">
+        <div class="col-md-8">
+            <div id="quests-panel" hx-get="/quests/panel/{{ agent_id }}" hx-trigger="load, every 30s">
+                <div class="mc-loading">Loading quests...</div>
+            </div>
+        </div>
+
+        <div class="col-md-4">
+            <div class="card mc-panel">
+                <div class="card-header">
+                    <h5 class="mb-0">Leaderboard</h5>
+                </div>
+                <div class="card-body">
+                    <div id="leaderboard" hx-get="/quests/api/leaderboard" hx-trigger="load, every 60s">
+                        <div class="mc-loading">Loading leaderboard...</div>
+                    </div>
+                </div>
+            </div>
+
+            <div class="card mc-panel mt-4">
+                <div class="card-header">
+                    <h5 class="mb-0">About Quests</h5>
+                </div>
+                <div class="card-body">
+                    <p class="mb-2">Quests are special objectives that reward tokens upon completion.</p>
+                    <ul class="mc-list mb-0">
+                        <li>Complete Daily Run sessions</li>
+                        <li>Close flaky-test issues</li>
+                        <li>Reduce P1 issue backlog</li>
+                        <li>Improve documentation</li>
+                    </ul>
+                </div>
+            </div>
+        </div>
+    </div>
+</div>
+{% endblock %}

src/dashboard/templates/tower.html

@@ -0,0 +1,180 @@
+{% extends "base.html" %}
+
+{% block title %}Timmy Time — Tower{% endblock %}
+
+{% block extra_styles %}{% endblock %}
+
+{% block content %}
+<div class="container-fluid tower-container py-3">
+
+  <div class="tower-header">
+    <div class="tower-title">TOWER</div>
+    <div class="tower-subtitle">
+      Real-time Spark visualization &mdash;
+      <span id="tower-conn" class="tower-conn-badge tower-conn-connecting">CONNECTING</span>
+    </div>
+  </div>
+
+  <div class="row g-3">
+
+    <!-- Left: THINKING (events) -->
+    <div class="col-12 col-lg-4 d-flex flex-column gap-3">
+      <div class="card mc-panel tower-phase-card">
+        <div class="card-header mc-panel-header tower-phase-thinking">// THINKING</div>
+        <div class="card-body p-3 tower-scroll" id="tower-events">
+          <div class="tower-empty">Waiting for Spark data&hellip;</div>
+        </div>
+      </div>
+    </div>
+
+    <!-- Middle: PREDICTING (EIDOS) -->
+    <div class="col-12 col-lg-4 d-flex flex-column gap-3">
+      <div class="card mc-panel tower-phase-card">
+        <div class="card-header mc-panel-header tower-phase-predicting">// PREDICTING</div>
+        <div class="card-body p-3" id="tower-predictions">
+          <div class="tower-empty">Waiting for Spark data&hellip;</div>
+        </div>
+      </div>
+      <div class="card mc-panel">
+        <div class="card-header mc-panel-header">// EIDOS STATS</div>
+        <div class="card-body p-3">
+          <div class="tower-stat-grid" id="tower-stats">
+            <div class="tower-stat"><span class="tower-stat-label">EVENTS</span><span class="tower-stat-value" id="ts-events">0</span></div>
+            <div class="tower-stat"><span class="tower-stat-label">MEMORIES</span><span class="tower-stat-value" id="ts-memories">0</span></div>
+            <div class="tower-stat"><span class="tower-stat-label">PREDICTIONS</span><span class="tower-stat-value" id="ts-preds">0</span></div>
+            <div class="tower-stat"><span class="tower-stat-label">ACCURACY</span><span class="tower-stat-value" id="ts-accuracy">—</span></div>
+          </div>
+        </div>
+      </div>
+    </div>
+
+    <!-- Right: ADVISING -->
+    <div class="col-12 col-lg-4 d-flex flex-column gap-3">
+      <div class="card mc-panel tower-phase-card">
+        <div class="card-header mc-panel-header tower-phase-advising">// ADVISING</div>
+        <div class="card-body p-3 tower-scroll" id="tower-advisories">
+          <div class="tower-empty">Waiting for Spark data&hellip;</div>
+        </div>
+      </div>
+    </div>
+
+  </div>
+</div>
+
+<script>
+(function() {
+  var ws = null;
+  var badge = document.getElementById('tower-conn');
+
+  function setConn(state) {
+    badge.textContent = state.toUpperCase();
+    badge.className = 'tower-conn-badge tower-conn-' + state;
+  }
+
+  function esc(s) { var d = document.createElement('div'); d.textContent = s; return d.innerHTML; }
+
+  function renderEvents(events) {
+    var el = document.getElementById('tower-events');
+    if (!events || !events.length) { el.innerHTML = '<div class="tower-empty">No events captured yet.</div>'; return; }
+    var html = '';
+    for (var i = 0; i < events.length; i++) {
+      var ev = events[i];
+      var dots = ev.importance >= 0.8 ? '\u25cf\u25cf\u25cf' : ev.importance >= 0.5 ? '\u25cf\u25cf' : '\u25cf';
+      html += '<div class="tower-event tower-etype-' + esc(ev.event_type) + '">'
+        + '<div class="tower-ev-head">'
+        + '<span class="tower-ev-badge">' + esc(ev.event_type.replace(/_/g, ' ').toUpperCase()) + '</span>'
+        + '<span class="tower-ev-dots">' + dots + '</span>'
+        + '</div>'
+        + '<div class="tower-ev-desc">' + esc(ev.description) + '</div>'
+        + '<div class="tower-ev-time">' + esc((ev.created_at || '').slice(0, 19)) + '</div>'
+        + '</div>';
+    }
+    el.innerHTML = html;
+  }
+
+  function renderPredictions(preds) {
+    var el = document.getElementById('tower-predictions');
+    if (!preds || !preds.length) { el.innerHTML = '<div class="tower-empty">No predictions yet.</div>'; return; }
+    var html = '';
+    for (var i = 0; i < preds.length; i++) {
+      var p = preds[i];
+      var cls = p.evaluated ? 'tower-pred-done' : 'tower-pred-pending';
+      var accTxt = p.accuracy != null ? Math.round(p.accuracy * 100) + '%' : 'PENDING';
+      var accCls = p.accuracy != null ? (p.accuracy >= 0.7 ? 'text-success' : p.accuracy < 0.4 ? 'text-danger' : 'text-warning') : '';
+      html += '<div class="tower-pred ' + cls + '">'
+        + '<div class="tower-pred-head">'
+        + '<span class="tower-pred-task">' + esc(p.task_id) + '</span>'
+        + '<span class="tower-pred-acc ' + accCls + '">' + accTxt + '</span>'
+        + '</div>';
+      if (p.predicted) {
+        var pr = p.predicted;
+        html += '<div class="tower-pred-detail">';
+        if (pr.likely_winner) html += '<span>Winner: ' + esc(pr.likely_winner.slice(0, 8)) + '</span> ';
+        if (pr.success_probability != null) html += '<span>Success: ' + Math.round(pr.success_probability * 100) + '%</span> ';
+        html += '</div>';
+      }
+      html += '<div class="tower-ev-time">' + esc((p.created_at || '').slice(0, 19)) + '</div>'
+        + '</div>';
+    }
+    el.innerHTML = html;
+  }
+
+  function renderAdvisories(advs) {
+    var el = document.getElementById('tower-advisories');
+    if (!advs || !advs.length) { el.innerHTML = '<div class="tower-empty">No advisories yet.</div>'; return; }
+    var html = '';
+    for (var i = 0; i < advs.length; i++) {
+      var a = advs[i];
+      var prio = a.priority >= 0.7 ? 'high' : a.priority >= 0.4 ? 'medium' : 'low';
+      html += '<div class="tower-advisory tower-adv-' + prio + '">'
+        + '<div class="tower-adv-head">'
+        + '<span class="tower-adv-cat">' + esc(a.category.replace(/_/g, ' ').toUpperCase()) + '</span>'
+        + '<span class="tower-adv-prio">' + Math.round(a.priority * 100) + '%</span>'
+        + '</div>'
+        + '<div class="tower-adv-title">' + esc(a.title) + '</div>'
+        + '<div class="tower-adv-detail">' + esc(a.detail) + '</div>'
+        + '<div class="tower-adv-action">' + esc(a.suggested_action) + '</div>'
+        + '</div>';
+    }
+    el.innerHTML = html;
+  }
+
+  function renderStats(status) {
+    if (!status) return;
+    document.getElementById('ts-events').textContent = status.events_captured || 0;
+    document.getElementById('ts-memories').textContent = status.memories_stored || 0;
+    var p = status.predictions || {};
+    document.getElementById('ts-preds').textContent = p.total_predictions || 0;
+    var acc = p.avg_accuracy;
+    var accEl = document.getElementById('ts-accuracy');
+    if (acc != null) {
+      accEl.textContent = Math.round(acc * 100) + '%';
+      accEl.className = 'tower-stat-value ' + (acc >= 0.7 ? 'text-success' : acc < 0.4 ? 'text-danger' : 'text-warning');
+    } else {
+      accEl.textContent = '\u2014';
+    }
+  }
+
+  function handleMsg(data) {
+    if (data.type !== 'spark_state') return;
+    renderEvents(data.events);
+    renderPredictions(data.predictions);
+    renderAdvisories(data.advisories);
+    renderStats(data.status);
+  }
+
+  function connect() {
+    var proto = location.protocol === 'https:' ? 'wss:' : 'ws:';
+    ws = new WebSocket(proto + '//' + location.host + '/tower/ws');
+    ws.onopen = function() { setConn('live'); };
+    ws.onclose = function() { setConn('offline'); setTimeout(connect, 3000); };
+    ws.onerror = function() { setConn('offline'); };
+    ws.onmessage = function(e) {
+      try { handleMsg(JSON.parse(e.data)); } catch(err) { console.error('Tower WS parse error', err); }
+    };
+  }
+
+  connect();
+})();
+</script>
+{% endblock %}

src/infrastructure/db_pool.py

@@ -0,0 +1,84 @@
+"""Thread-local SQLite connection pool.
+
+Provides a ConnectionPool class that manages SQLite connections per thread,
+with support for context managers and automatic cleanup.
+"""
+
+import sqlite3
+import threading
+from collections.abc import Generator
+from contextlib import contextmanager
+from pathlib import Path
+
+
+class ConnectionPool:
+    """Thread-local SQLite connection pool.
+
+    Each thread gets its own connection, which is reused for subsequent
+    requests from the same thread. Connections are automatically cleaned
+    up when close_connection() is called or the context manager exits.
+    """
+
+    def __init__(self, db_path: Path | str) -> None:
+        """Initialize the connection pool.
+
+        Args:
+            db_path: Path to the SQLite database file.
+        """
+        self._db_path = Path(db_path)
+        self._local = threading.local()
+
+    def _ensure_db_exists(self) -> None:
+        """Ensure the database directory exists."""
+        self._db_path.parent.mkdir(parents=True, exist_ok=True)
+
+    def get_connection(self) -> sqlite3.Connection:
+        """Get a connection for the current thread.
+
+        Creates a new connection if one doesn't exist for this thread,
+        otherwise returns the existing connection.
+
+        Returns:
+            A sqlite3 Connection object.
+        """
+        if not hasattr(self._local, "conn") or self._local.conn is None:
+            self._ensure_db_exists()
+            self._local.conn = sqlite3.connect(str(self._db_path), check_same_thread=False)
+            self._local.conn.row_factory = sqlite3.Row
+        return self._local.conn
+
+    def close_connection(self) -> None:
+        """Close the connection for the current thread.
+
+        Cleans up the thread-local storage. Safe to call even if
+        no connection exists for this thread.
+        """
+        if hasattr(self._local, "conn") and self._local.conn is not None:
+            self._local.conn.close()
+            self._local.conn = None
+
+    @contextmanager
+    def connection(self) -> Generator[sqlite3.Connection, None, None]:
+        """Context manager for getting and automatically closing a connection.
+
+        Yields:
+            A sqlite3 Connection object.
+
+        Example:
+            with pool.connection() as conn:
+                cursor = conn.execute("SELECT 1")
+                result = cursor.fetchone()
+        """
+        conn = self.get_connection()
+        try:
+            yield conn
+        finally:
+            self.close_connection()
+
+    def close_all(self) -> None:
+        """Close all connections (useful for testing).
+
+        Note: This only closes the connection for the current thread.
+        In a multi-threaded environment, each thread must close its own.
+        """
+        self.close_connection()

src/infrastructure/error_capture.py

@@ -100,6 +100,172 @@ def _get_git_context() -> dict:
         return {"branch": "unknown", "commit": "unknown"}
 
 
+def _extract_traceback_info(exc: Exception) -> tuple[str, str, int]:
+    """Extract formatted traceback, affected file, and line number.
+
+    Returns:
+        Tuple of (traceback_string, affected_file, affected_line).
+    """
+    tb_str = "".join(traceback.format_exception(type(exc), exc, exc.__traceback__))
+
+    tb_obj = exc.__traceback__
+    affected_file = "unknown"
+    affected_line = 0
+    while tb_obj and tb_obj.tb_next:
+        tb_obj = tb_obj.tb_next
+    if tb_obj:
+        affected_file = tb_obj.tb_frame.f_code.co_filename
+        affected_line = tb_obj.tb_lineno
+
+    return tb_str, affected_file, affected_line
+
+
+def _log_error_event(
+    exc: Exception,
+    source: str,
+    error_hash: str,
+    affected_file: str,
+    affected_line: int,
+    git_ctx: dict,
+) -> None:
+    """Log the captured error to the event log."""
+    try:
+        from swarm.event_log import EventType, log_event
+
+        log_event(
+            EventType.ERROR_CAPTURED,
+            source=source,
+            data={
+                "error_type": type(exc).__name__,
+                "message": str(exc)[:500],
+                "hash": error_hash,
+                "file": affected_file,
+                "line": affected_line,
+                "git_branch": git_ctx.get("branch", ""),
+                "git_commit": git_ctx.get("commit", ""),
+            },
+        )
+    except Exception as log_exc:
+        logger.debug("Failed to log error event: %s", log_exc)
+
+
+def _build_report_description(
+    exc: Exception,
+    source: str,
+    context: dict | None,
+    error_hash: str,
+    tb_str: str,
+    affected_file: str,
+    affected_line: int,
+    git_ctx: dict,
+) -> str:
+    """Build the markdown description for a bug report task."""
+    parts = [
+        f"**Error:** {type(exc).__name__}: {str(exc)}",
+        f"**Source:** {source}",
+        f"**File:** {affected_file}:{affected_line}",
+        f"**Git:** {git_ctx.get('branch', '?')} @ {git_ctx.get('commit', '?')}",
+        f"**Time:** {datetime.now(UTC).isoformat()}",
+        f"**Hash:** {error_hash}",
+    ]
+
+    if context:
+        ctx_str = ", ".join(f"{k}={v}" for k, v in context.items())
+        parts.append(f"**Context:** {ctx_str}")
+
+    parts.append(f"\n**Stack Trace:**\n```\n{tb_str[:2000]}\n```")
+    return "\n".join(parts)
+
+
+def _log_bug_report_created(source: str, task_id: str, error_hash: str, title: str) -> None:
+    """Log a BUG_REPORT_CREATED event (best-effort)."""
+    try:
+        from swarm.event_log import EventType, log_event
+
+        log_event(
+            EventType.BUG_REPORT_CREATED,
+            source=source,
+            task_id=task_id,
+            data={
+                "error_hash": error_hash,
+                "title": title[:100],
+            },
+        )
+    except Exception as exc:
+        logger.warning("Bug report event log error: %s", exc)
+
+
+def _create_bug_report(
+    exc: Exception,
+    source: str,
+    context: dict | None,
+    error_hash: str,
+    tb_str: str,
+    affected_file: str,
+    affected_line: int,
+    git_ctx: dict,
+) -> str | None:
+    """Create a bug report task and return the task ID (or None on failure)."""
+    try:
+        from swarm.task_queue.models import create_task
+
+        title = f"[BUG] {type(exc).__name__}: {str(exc)[:80]}"
+        description = _build_report_description(
+            exc,
+            source,
+            context,
+            error_hash,
+            tb_str,
+            affected_file,
+            affected_line,
+            git_ctx,
+        )
+
+        task = create_task(
+            title=title,
+            description=description,
+            assigned_to="default",
+            created_by="system",
+            priority="normal",
+            requires_approval=False,
+            auto_approve=True,
+            task_type="bug_report",
+        )
+
+        _log_bug_report_created(source, task.id, error_hash, title)
+        return task.id
+
+    except Exception as task_exc:
+        logger.debug("Failed to create bug report task: %s", task_exc)
+        return None
+
+
+def _notify_bug_report(exc: Exception, source: str) -> None:
+    """Send a push notification about the captured error."""
+    try:
+        from infrastructure.notifications.push import notifier
+
+        notifier.notify(
+            title="Bug Report Filed",
+            message=f"{type(exc).__name__} in {source}: {str(exc)[:80]}",
+            category="system",
+        )
+    except Exception as notify_exc:
+        logger.warning("Bug report notification error: %s", notify_exc)
+
+
+def _record_to_session(exc: Exception, source: str) -> None:
+    """Record the error via the registered session callback."""
+    if _error_recorder is not None:
+        try:
+            _error_recorder(
+                error=f"{type(exc).__name__}: {str(exc)}",
+                context=source,
+            )
+        except Exception as log_exc:
+            logger.warning("Bug report session logging error: %s", log_exc)
+
+
 def capture_error(
     exc: Exception,
     source: str = "unknown",
@@ -126,116 +292,23 @@ def capture_error(
         logger.debug("Duplicate error suppressed: %s (hash=%s)", exc, error_hash)
         return None
 
-    # Format the stack trace
-    tb_str = "".join(traceback.format_exception(type(exc), exc, exc.__traceback__))
-
-    # Extract file/line from traceback
-    tb_obj = exc.__traceback__
-    affected_file = "unknown"
-    affected_line = 0
-    while tb_obj and tb_obj.tb_next:
-        tb_obj = tb_obj.tb_next
-    if tb_obj:
-        affected_file = tb_obj.tb_frame.f_code.co_filename
-        affected_line = tb_obj.tb_lineno
-
+    tb_str, affected_file, affected_line = _extract_traceback_info(exc)
     git_ctx = _get_git_context()
 
-    # 1. Log to event_log
-    try:
-        from swarm.event_log import EventType, log_event
+    _log_error_event(exc, source, error_hash, affected_file, affected_line, git_ctx)
 
-        log_event(
-            EventType.ERROR_CAPTURED,
-            source=source,
-            data={
-                "error_type": type(exc).__name__,
-                "message": str(exc)[:500],
-                "hash": error_hash,
-                "file": affected_file,
-                "line": affected_line,
-                "git_branch": git_ctx.get("branch", ""),
-                "git_commit": git_ctx.get("commit", ""),
-            },
-        )
-    except Exception as log_exc:
-        logger.debug("Failed to log error event: %s", log_exc)
+    task_id = _create_bug_report(
+        exc,
+        source,
+        context,
+        error_hash,
+        tb_str,
+        affected_file,
+        affected_line,
+        git_ctx,
+    )
 
-    # 2. Create bug report task
-    task_id = None
-    try:
-        from swarm.task_queue.models import create_task
-
-        title = f"[BUG] {type(exc).__name__}: {str(exc)[:80]}"
-
-        description_parts = [
-            f"**Error:** {type(exc).__name__}: {str(exc)}",
-            f"**Source:** {source}",
-            f"**File:** {affected_file}:{affected_line}",
-            f"**Git:** {git_ctx.get('branch', '?')} @ {git_ctx.get('commit', '?')}",
-            f"**Time:** {datetime.now(UTC).isoformat()}",
-            f"**Hash:** {error_hash}",
-        ]
-
-        if context:
-            ctx_str = ", ".join(f"{k}={v}" for k, v in context.items())
-            description_parts.append(f"**Context:** {ctx_str}")
-
-        description_parts.append(f"\n**Stack Trace:**\n```\n{tb_str[:2000]}\n```")
-
-        task = create_task(
-            title=title,
-            description="\n".join(description_parts),
-            assigned_to="default",
-            created_by="system",
-            priority="normal",
-            requires_approval=False,
-            auto_approve=True,
-            task_type="bug_report",
-        )
-        task_id = task.id
-
-        # Log the creation event
-        try:
-            from swarm.event_log import EventType, log_event
-
-            log_event(
-                EventType.BUG_REPORT_CREATED,
-                source=source,
-                task_id=task_id,
-                data={
-                    "error_hash": error_hash,
-                    "title": title[:100],
-                },
-            )
-        except Exception as exc:
-            logger.warning("Bug report screenshot error: %s", exc)
-            pass
-
-    except Exception as task_exc:
-        logger.debug("Failed to create bug report task: %s", task_exc)
-
-    # 3. Send notification
-    try:
-        from infrastructure.notifications.push import notifier
-
-        notifier.notify(
-            title="Bug Report Filed",
-            message=f"{type(exc).__name__} in {source}: {str(exc)[:80]}",
-            category="system",
-        )
-    except Exception as exc:
-        logger.warning("Bug report notification error: %s", exc)
-        pass
-
-    # 4. Record in session logger (via registered callback)
-    if _error_recorder is not None:
-        try:
-            _error_recorder(
-                error=f"{type(exc).__name__}: {str(exc)}",
-                context=source,
-            )
-        except Exception as log_exc:
-            logger.warning("Bug report session logging error: %s", log_exc)
+    _notify_bug_report(exc, source)
+    _record_to_session(exc, source)
 
     return task_id

src/infrastructure/events/bus.py

@@ -64,7 +64,7 @@ class EventBus:
 
         @bus.subscribe("agent.task.*")
         async def handle_task(event: Event):
-            logger.debug(f"Task event: {event.data}")
+            logger.debug("Task event: %s", event.data)
 
         await bus.publish(Event(
             type="agent.task.assigned",

src/infrastructure/hands/shell.py

@@ -144,6 +144,65 @@ class ShellHand:
 
         return None
 
+    @staticmethod
+    def _build_run_env(env: dict | None) -> dict:
+        """Merge *env* overrides into a copy of the current environment."""
+        import os
+
+        run_env = os.environ.copy()
+        if env:
+            run_env.update(env)
+        return run_env
+
+    async def _execute_subprocess(
+        self,
+        command: str,
+        effective_timeout: int,
+        cwd: str | None,
+        run_env: dict,
+        start: float,
+    ) -> ShellResult:
+        """Run *command* as a subprocess with timeout enforcement."""
+        proc = await asyncio.create_subprocess_shell(
+            command,
+            stdout=asyncio.subprocess.PIPE,
+            stderr=asyncio.subprocess.PIPE,
+            cwd=cwd,
+            env=run_env,
+        )
+
+        try:
+            stdout_bytes, stderr_bytes = await asyncio.wait_for(
+                proc.communicate(), timeout=effective_timeout
+            )
+        except TimeoutError:
+            proc.kill()
+            await proc.wait()
+            latency = (time.time() - start) * 1000
+            logger.warning("Shell command timed out after %ds: %s", effective_timeout, command)
+            return ShellResult(
+                command=command,
+                success=False,
+                exit_code=-1,
+                error=f"Command timed out after {effective_timeout}s",
+                latency_ms=latency,
+                timed_out=True,
+            )
+
+        latency = (time.time() - start) * 1000
+        exit_code = proc.returncode if proc.returncode is not None else -1
+        stdout = stdout_bytes.decode("utf-8", errors="replace").strip()
+        stderr = stderr_bytes.decode("utf-8", errors="replace").strip()
+
+        return ShellResult(
+            command=command,
+            success=exit_code == 0,
+            exit_code=exit_code,
+            stdout=stdout,
+            stderr=stderr,
+            latency_ms=latency,
+        )
+
     async def run(
         self,
         command: str,
@@ -164,7 +223,6 @@ class ShellHand:
         """
         start = time.time()
 
-        # Validate
         validation_error = self._validate_command(command)
         if validation_error:
             return ShellResult(
@@ -178,52 +236,8 @@ class ShellHand:
         cwd = working_dir or self._working_dir
 
         try:
-            import os
-
-            run_env = os.environ.copy()
-            if env:
-                run_env.update(env)
-
-            proc = await asyncio.create_subprocess_shell(
-                command,
-                stdout=asyncio.subprocess.PIPE,
-                stderr=asyncio.subprocess.PIPE,
-                cwd=cwd,
-                env=run_env,
-            )
-
-            try:
-                stdout_bytes, stderr_bytes = await asyncio.wait_for(
-                    proc.communicate(), timeout=effective_timeout
-                )
-            except TimeoutError:
-                proc.kill()
-                await proc.wait()
-                latency = (time.time() - start) * 1000
-                logger.warning("Shell command timed out after %ds: %s", effective_timeout, command)
-                return ShellResult(
-                    command=command,
-                    success=False,
-                    exit_code=-1,
-                    error=f"Command timed out after {effective_timeout}s",
-                    latency_ms=latency,
-                    timed_out=True,
-                )
-
-            latency = (time.time() - start) * 1000
-            exit_code = proc.returncode if proc.returncode is not None else -1
-            stdout = stdout_bytes.decode("utf-8", errors="replace").strip()
-            stderr = stderr_bytes.decode("utf-8", errors="replace").strip()
-
-            return ShellResult(
-                command=command,
-                success=exit_code == 0,
-                exit_code=exit_code,
-                stdout=stdout,
-                stderr=stderr,
-                latency_ms=latency,
-            )
-
+            run_env = self._build_run_env(env)
+            return await self._execute_subprocess(command, effective_timeout, cwd, run_env, start)
         except Exception as exc:
             latency = (time.time() - start) * 1000
             logger.warning("Shell command failed: %s — %s", command, exc)

src/infrastructure/matrix_config.py

@@ -0,0 +1,266 @@
+"""Matrix configuration loader utility.
+
+Provides a typed dataclass for Matrix world configuration and a loader
+that fetches settings from YAML with sensible defaults.
+"""
+
+import logging
+from dataclasses import dataclass, field
+from pathlib import Path
+from typing import Any
+
+import yaml
+
+logger = logging.getLogger(__name__)
+
+
+@dataclass
+class PointLight:
+    """A single point light in the Matrix world."""
+
+    color: str = "#FFFFFF"
+    intensity: float = 1.0
+    position: dict[str, float] = field(default_factory=lambda: {"x": 0, "y": 0, "z": 0})
+
+    @classmethod
+    def from_dict(cls, data: dict[str, Any]) -> "PointLight":
+        """Create a PointLight from a dictionary with defaults."""
+        return cls(
+            color=data.get("color", "#FFFFFF"),
+            intensity=data.get("intensity", 1.0),
+            position=data.get("position", {"x": 0, "y": 0, "z": 0}),
+        )
+
+
+def _default_point_lights_factory() -> list[PointLight]:
+    """Factory function for default point lights."""
+    return [
+        PointLight(
+            color="#FFAA55",  # Warm amber (Workshop)
+            intensity=1.2,
+            position={"x": 0, "y": 5, "z": 0},
+        ),
+        PointLight(
+            color="#3B82F6",  # Cool blue (Matrix)
+            intensity=0.8,
+            position={"x": -5, "y": 3, "z": -5},
+        ),
+        PointLight(
+            color="#A855F7",  # Purple accent
+            intensity=0.6,
+            position={"x": 5, "y": 3, "z": 5},
+        ),
+    ]
+
+
+@dataclass
+class LightingConfig:
+    """Lighting configuration for the Matrix world."""
+
+    ambient_color: str = "#FFAA55"  # Warm amber (Workshop warmth)
+    ambient_intensity: float = 0.5
+    point_lights: list[PointLight] = field(default_factory=_default_point_lights_factory)
+
+    @classmethod
+    def from_dict(cls, data: dict[str, Any] | None) -> "LightingConfig":
+        """Create a LightingConfig from a dictionary with defaults."""
+        if data is None:
+            data = {}
+
+        point_lights_data = data.get("point_lights", [])
+        point_lights = (
+            [PointLight.from_dict(pl) for pl in point_lights_data]
+            if point_lights_data
+            else _default_point_lights_factory()
+        )
+
+        return cls(
+            ambient_color=data.get("ambient_color", "#FFAA55"),
+            ambient_intensity=data.get("ambient_intensity", 0.5),
+            point_lights=point_lights,
+        )
+
+
+@dataclass
+class EnvironmentConfig:
+    """Environment settings for the Matrix world."""
+
+    rain_enabled: bool = False
+    starfield_enabled: bool = True
+    fog_color: str = "#0f0f23"
+    fog_density: float = 0.02
+
+    @classmethod
+    def from_dict(cls, data: dict[str, Any] | None) -> "EnvironmentConfig":
+        """Create an EnvironmentConfig from a dictionary with defaults."""
+        if data is None:
+            data = {}
+        return cls(
+            rain_enabled=data.get("rain_enabled", False),
+            starfield_enabled=data.get("starfield_enabled", True),
+            fog_color=data.get("fog_color", "#0f0f23"),
+            fog_density=data.get("fog_density", 0.02),
+        )
+
+
+@dataclass
+class FeaturesConfig:
+    """Feature toggles for the Matrix world."""
+
+    chat_enabled: bool = True
+    visitor_avatars: bool = True
+    pip_familiar: bool = True
+    workshop_portal: bool = True
+
+    @classmethod
+    def from_dict(cls, data: dict[str, Any] | None) -> "FeaturesConfig":
+        """Create a FeaturesConfig from a dictionary with defaults."""
+        if data is None:
+            data = {}
+        return cls(
+            chat_enabled=data.get("chat_enabled", True),
+            visitor_avatars=data.get("visitor_avatars", True),
+            pip_familiar=data.get("pip_familiar", True),
+            workshop_portal=data.get("workshop_portal", True),
+        )
+
+
+@dataclass
+class AgentConfig:
+    """Configuration for a single Matrix agent."""
+
+    name: str = ""
+    role: str = ""
+    enabled: bool = True
+
+    @classmethod
+    def from_dict(cls, data: dict[str, Any]) -> "AgentConfig":
+        """Create an AgentConfig from a dictionary with defaults."""
+        return cls(
+            name=data.get("name", ""),
+            role=data.get("role", ""),
+            enabled=data.get("enabled", True),
+        )
+
+
+@dataclass
+class AgentsConfig:
+    """Agent registry configuration."""
+
+    default_count: int = 5
+    max_count: int = 20
+    agents: list[AgentConfig] = field(default_factory=list)
+
+    @classmethod
+    def from_dict(cls, data: dict[str, Any] | None) -> "AgentsConfig":
+        """Create an AgentsConfig from a dictionary with defaults."""
+        if data is None:
+            data = {}
+
+        agents_data = data.get("agents", [])
+        agents = [AgentConfig.from_dict(a) for a in agents_data] if agents_data else []
+
+        return cls(
+            default_count=data.get("default_count", 5),
+            max_count=data.get("max_count", 20),
+            agents=agents,
+        )
+
+
+@dataclass
+class MatrixConfig:
+    """Complete Matrix world configuration.
+
+    Combines lighting, environment, features, and agent settings
+    into a single configuration object.
+    """
+
+    lighting: LightingConfig = field(default_factory=LightingConfig)
+    environment: EnvironmentConfig = field(default_factory=EnvironmentConfig)
+    features: FeaturesConfig = field(default_factory=FeaturesConfig)
+    agents: AgentsConfig = field(default_factory=AgentsConfig)
+
+    @classmethod
+    def from_dict(cls, data: dict[str, Any] | None) -> "MatrixConfig":
+        """Create a MatrixConfig from a dictionary with defaults for missing sections."""
+        if data is None:
+            data = {}
+        return cls(
+            lighting=LightingConfig.from_dict(data.get("lighting")),
+            environment=EnvironmentConfig.from_dict(data.get("environment")),
+            features=FeaturesConfig.from_dict(data.get("features")),
+            agents=AgentsConfig.from_dict(data.get("agents")),
+        )
+
+    def to_dict(self) -> dict[str, Any]:
+        """Convert the configuration to a plain dictionary."""
+        return {
+            "lighting": {
+                "ambient_color": self.lighting.ambient_color,
+                "ambient_intensity": self.lighting.ambient_intensity,
+                "point_lights": [
+                    {
+                        "color": pl.color,
+                        "intensity": pl.intensity,
+                        "position": pl.position,
+                    }
+                    for pl in self.lighting.point_lights
+                ],
+            },
+            "environment": {
+                "rain_enabled": self.environment.rain_enabled,
+                "starfield_enabled": self.environment.starfield_enabled,
+                "fog_color": self.environment.fog_color,
+                "fog_density": self.environment.fog_density,
+            },
+            "features": {
+                "chat_enabled": self.features.chat_enabled,
+                "visitor_avatars": self.features.visitor_avatars,
+                "pip_familiar": self.features.pip_familiar,
+                "workshop_portal": self.features.workshop_portal,
+            },
+            "agents": {
+                "default_count": self.agents.default_count,
+                "max_count": self.agents.max_count,
+                "agents": [
+                    {"name": a.name, "role": a.role, "enabled": a.enabled}
+                    for a in self.agents.agents
+                ],
+            },
+        }
+
+
+def load_from_yaml(path: str | Path) -> MatrixConfig:
+    """Load Matrix configuration from a YAML file.
+
+    Missing keys are filled with sensible defaults. If the file
+    cannot be read or parsed, returns a fully default configuration.
+
+    Args:
+        path: Path to the YAML configuration file.
+
+    Returns:
+        A MatrixConfig instance with loaded or default values.
+    """
+    path = Path(path)
+
+    if not path.exists():
+        logger.warning("Matrix config file not found: %s, using defaults", path)
+        return MatrixConfig()
+
+    try:
+        with open(path, encoding="utf-8") as f:
+            raw_data = yaml.safe_load(f)
+
+        if not isinstance(raw_data, dict):
+            logger.warning("Matrix config invalid format, using defaults")
+            return MatrixConfig()
+
+        return MatrixConfig.from_dict(raw_data)
+
+    except yaml.YAMLError as exc:
+        logger.warning("Matrix config YAML parse error: %s, using defaults", exc)
+        return MatrixConfig()
+    except OSError as exc:
+        logger.warning("Matrix config read error: %s, using defaults", exc)
+        return MatrixConfig()

src/infrastructure/models/multimodal.py

@@ -13,7 +13,7 @@ import logging
 from dataclasses import dataclass, field
 from enum import Enum, auto
 
-from config import settings
+from config import normalize_ollama_url, settings
 
 logger = logging.getLogger(__name__)
 
@@ -307,7 +307,7 @@ class MultiModalManager:
             import json
             import urllib.request
 
-            url = self.ollama_url.replace("localhost", "127.0.0.1")
+            url = normalize_ollama_url(self.ollama_url)
             req = urllib.request.Request(
                 f"{url}/api/tags",
                 method="GET",
@@ -462,7 +462,7 @@ class MultiModalManager:
 
             logger.info("Pulling model: %s", model_name)
 
-            url = self.ollama_url.replace("localhost", "127.0.0.1")
+            url = normalize_ollama_url(self.ollama_url)
             req = urllib.request.Request(
                 f"{url}/api/pull",
                 method="POST",

src/infrastructure/presence.py

@@ -0,0 +1,333 @@
+"""Presence state serializer — transforms ADR-023 presence dicts for consumers.
+
+Converts the raw presence schema (version, liveness, mood, energy, etc.)
+into the camelCase world-state payload consumed by the Workshop 3D renderer
+and WebSocket gateway.
+"""
+
+import logging
+import time
+from datetime import UTC, datetime
+
+logger = logging.getLogger(__name__)
+
+# Default Pip familiar state (used when familiar module unavailable)
+DEFAULT_PIP_STATE = {
+    "name": "Pip",
+    "mood": "sleepy",
+    "energy": 0.5,
+    "color": "0x00b450",  # emerald green
+    "trail_color": "0xdaa520",  # gold
+}
+
+
+def _get_familiar_state() -> dict:
+    """Get Pip familiar state from familiar module, with graceful fallback.
+
+    Returns a dict with name, mood, energy, color, and trail_color.
+    Falls back to default state if familiar module unavailable or raises.
+    """
+    try:
+        from timmy.familiar import pip_familiar
+
+        snapshot = pip_familiar.snapshot()
+        # Map PipSnapshot fields to the expected agent_state format
+        return {
+            "name": snapshot.name,
+            "mood": snapshot.state,
+            "energy": DEFAULT_PIP_STATE["energy"],  # Pip doesn't track energy yet
+            "color": DEFAULT_PIP_STATE["color"],
+            "trail_color": DEFAULT_PIP_STATE["trail_color"],
+        }
+    except Exception as exc:
+        logger.warning("Familiar state unavailable, using default: %s", exc)
+        return DEFAULT_PIP_STATE.copy()
+
+
+# Valid bark styles for Matrix protocol
+BARK_STYLES = {"speech", "thought", "whisper", "shout"}
+
+
+def produce_bark(agent_id: str, text: str, reply_to: str = None, style: str = "speech") -> dict:
+    """Format a chat response as a Matrix bark message.
+
+    Barks appear as floating text above agents in the Matrix 3D world with
+    typing animation. This function formats the text for the Matrix protocol.
+
+    Parameters
+    ----------
+    agent_id:
+        Unique identifier for the agent (e.g. ``"timmy"``).
+    text:
+        The chat response text to display as a bark.
+    reply_to:
+        Optional message ID or reference this bark is replying to.
+    style:
+        Visual style of the bark. One of: "speech" (default), "thought",
+        "whisper", "shout". Invalid styles fall back to "speech".
+
+    Returns
+    -------
+    dict
+        Bark message with keys ``type``, ``agent_id``, ``data`` (containing
+        ``text``, ``reply_to``, ``style``), and ``ts``.
+
+    Examples
+    --------
+    >>> produce_bark("timmy", "Hello world!")
+    {
+        "type": "bark",
+        "agent_id": "timmy",
+        "data": {"text": "Hello world!", "reply_to": None, "style": "speech"},
+        "ts": 1742529600,
+    }
+    """
+    # Validate and normalize style
+    if style not in BARK_STYLES:
+        style = "speech"
+
+    # Truncate text to 280 characters (bark, not essay)
+    truncated_text = text[:280] if text else ""
+
+    return {
+        "type": "bark",
+        "agent_id": agent_id,
+        "data": {
+            "text": truncated_text,
+            "reply_to": reply_to,
+            "style": style,
+        },
+        "ts": int(time.time()),
+    }
+
+
+def produce_thought(
+    agent_id: str, thought_text: str, thought_id: int, chain_id: str = None
+) -> dict:
+    """Format a thinking engine thought as a Matrix thought message.
+
+    Thoughts appear as subtle floating text in the 3D world, streaming from
+    Timmy's thinking engine (/thinking/api). This function wraps thoughts in
+    Matrix protocol format.
+
+    Parameters
+    ----------
+    agent_id:
+        Unique identifier for the agent (e.g. ``"timmy"``).
+    thought_text:
+        The thought text to display. Truncated to 500 characters.
+    thought_id:
+        Unique identifier for this thought (sequence number).
+    chain_id:
+        Optional chain identifier grouping related thoughts.
+
+    Returns
+    -------
+    dict
+        Thought message with keys ``type``, ``agent_id``, ``data`` (containing
+        ``text``, ``thought_id``, ``chain_id``), and ``ts``.
+
+    Examples
+    --------
+    >>> produce_thought("timmy", "Considering the options...", 42, "chain-123")
+    {
+        "type": "thought",
+        "agent_id": "timmy",
+        "data": {"text": "Considering the options...", "thought_id": 42, "chain_id": "chain-123"},
+        "ts": 1742529600,
+    }
+    """
+    # Truncate text to 500 characters (thoughts can be longer than barks)
+    truncated_text = thought_text[:500] if thought_text else ""
+
+    return {
+        "type": "thought",
+        "agent_id": agent_id,
+        "data": {
+            "text": truncated_text,
+            "thought_id": thought_id,
+            "chain_id": chain_id,
+        },
+        "ts": int(time.time()),
+    }
+
+
+def serialize_presence(presence: dict) -> dict:
+    """Transform an ADR-023 presence dict into the world-state API shape.
+
+    Parameters
+    ----------
+    presence:
+        Raw presence dict as written by
+        :func:`~timmy.workshop_state.get_state_dict` or read from
+        ``~/.timmy/presence.json``.
+
+    Returns
+    -------
+    dict
+        CamelCase world-state payload with ``timmyState``, ``familiar``,
+        ``activeThreads``, ``recentEvents``, ``concerns``, ``visitorPresent``,
+        ``updatedAt``, and ``version`` keys.
+    """
+    return {
+        "timmyState": {
+            "mood": presence.get("mood", "calm"),
+            "activity": presence.get("current_focus", "idle"),
+            "energy": presence.get("energy", 0.5),
+            "confidence": presence.get("confidence", 0.7),
+        },
+        "familiar": presence.get("familiar"),
+        "activeThreads": presence.get("active_threads", []),
+        "recentEvents": presence.get("recent_events", []),
+        "concerns": presence.get("concerns", []),
+        "visitorPresent": False,
+        "updatedAt": presence.get("liveness", datetime.now(UTC).strftime("%Y-%m-%dT%H:%M:%SZ")),
+        "version": presence.get("version", 1),
+    }
+
+
+# ---------------------------------------------------------------------------
+# Status mapping: ADR-023 current_focus → Matrix agent status
+# ---------------------------------------------------------------------------
+_STATUS_KEYWORDS: dict[str, str] = {
+    "thinking": "thinking",
+    "speaking": "speaking",
+    "talking": "speaking",
+    "idle": "idle",
+}
+
+
+def _derive_status(current_focus: str) -> str:
+    """Map a free-text current_focus value to a Matrix status enum.
+
+    Returns one of: online, idle, thinking, speaking.
+    """
+    focus_lower = current_focus.lower()
+    for keyword, status in _STATUS_KEYWORDS.items():
+        if keyword in focus_lower:
+            return status
+    if current_focus and current_focus != "idle":
+        return "online"
+    return "idle"
+
+
+def produce_agent_state(agent_id: str, presence: dict) -> dict:
+    """Build a Matrix-compatible ``agent_state`` message from presence data.
+
+    Parameters
+    ----------
+    agent_id:
+        Unique identifier for the agent (e.g. ``"timmy"``).
+    presence:
+        Raw ADR-023 presence dict.
+
+    Returns
+    -------
+    dict
+        Message with keys ``type``, ``agent_id``, ``data``, and ``ts``.
+    """
+    return {
+        "type": "agent_state",
+        "agent_id": agent_id,
+        "data": {
+            "display_name": presence.get("display_name", agent_id.title()),
+            "role": presence.get("role", "assistant"),
+            "status": _derive_status(presence.get("current_focus", "idle")),
+            "mood": presence.get("mood", "calm"),
+            "energy": presence.get("energy", 0.5),
+            "bark": presence.get("bark", ""),
+            "familiar": _get_familiar_state(),
+        },
+        "ts": int(time.time()),
+    }
+
+
+def produce_system_status() -> dict:
+    """Generate a system_status message for the Matrix.
+
+    Returns a dict with system health metrics including agent count,
+    visitor count, uptime, thinking engine status, and memory count.
+
+    Returns
+    -------
+    dict
+        Message with keys ``type``, ``data`` (containing ``agents_online``,
+        ``visitors``, ``uptime_seconds``, ``thinking_active``, ``memory_count``),
+        and ``ts``.
+
+    Examples
+    --------
+    >>> produce_system_status()
+    {
+        "type": "system_status",
+        "data": {
+            "agents_online": 5,
+            "visitors": 2,
+            "uptime_seconds": 3600,
+            "thinking_active": True,
+            "memory_count": 150,
+        },
+        "ts": 1742529600,
+    }
+    """
+    # Count agents with status != offline
+    agents_online = 0
+    try:
+        from timmy.agents.loader import list_agents
+
+        agents = list_agents()
+        agents_online = sum(1 for a in agents if a.get("status", "") not in ("offline", ""))
+    except Exception as exc:
+        logger.debug("Failed to count agents: %s", exc)
+
+    # Count visitors from WebSocket clients
+    visitors = 0
+    try:
+        from dashboard.routes.world import _ws_clients
+
+        visitors = len(_ws_clients)
+    except Exception as exc:
+        logger.debug("Failed to count visitors: %s", exc)
+
+    # Calculate uptime
+    uptime_seconds = 0
+    try:
+        from datetime import UTC
+
+        from config import APP_START_TIME
+
+        uptime_seconds = int((datetime.now(UTC) - APP_START_TIME).total_seconds())
+    except Exception as exc:
+        logger.debug("Failed to calculate uptime: %s", exc)
+
+    # Check thinking engine status
+    thinking_active = False
+    try:
+        from config import settings
+        from timmy.thinking import thinking_engine
+
+        thinking_active = settings.thinking_enabled and thinking_engine is not None
+    except Exception as exc:
+        logger.debug("Failed to check thinking status: %s", exc)
+
+    # Count memories in vector store
+    memory_count = 0
+    try:
+        from timmy.memory_system import get_memory_stats
+
+        stats = get_memory_stats()
+        memory_count = stats.get("total_entries", 0)
+    except Exception as exc:
+        logger.debug("Failed to count memories: %s", exc)
+
+    return {
+        "type": "system_status",
+        "data": {
+            "agents_online": agents_online,
+            "visitors": visitors,
+            "uptime_seconds": uptime_seconds,
+            "thinking_active": thinking_active,
+            "memory_count": memory_count,
+        },
+        "ts": int(time.time()),
+    }

src/infrastructure/protocol.py

@@ -0,0 +1,261 @@
+"""Shared WebSocket message protocol for the Matrix frontend.
+
+Defines all WebSocket message types as an enum and typed dataclasses
+with ``to_json()`` / ``from_json()`` helpers so every producer and the
+gateway speak the same language.
+
+Message wire format
+-------------------
+.. code-block:: json
+
+   {"type": "agent_state", "agent_id": "timmy", "data": {...}, "ts": 1234567890}
+"""
+
+import json
+import logging
+import time
+from dataclasses import asdict, dataclass, field
+from enum import StrEnum
+from typing import Any
+
+logger = logging.getLogger(__name__)
+
+
+class MessageType(StrEnum):
+    """All WebSocket message types defined by the Matrix PROTOCOL.md."""
+
+    AGENT_STATE = "agent_state"
+    VISITOR_STATE = "visitor_state"
+    BARK = "bark"
+    THOUGHT = "thought"
+    SYSTEM_STATUS = "system_status"
+    CONNECTION_ACK = "connection_ack"
+    ERROR = "error"
+    TASK_UPDATE = "task_update"
+    MEMORY_FLASH = "memory_flash"
+
+
+# ---------------------------------------------------------------------------
+# Base message
+# ---------------------------------------------------------------------------
+
+
+@dataclass
+class WSMessage:
+    """Base WebSocket message with common envelope fields."""
+
+    type: str
+    ts: float = field(default_factory=time.time)
+
+    def to_json(self) -> str:
+        """Serialise the message to a JSON string."""
+        return json.dumps(asdict(self))
+
+    @classmethod
+    def from_json(cls, raw: str) -> "WSMessage":
+        """Deserialise a JSON string into the correct message subclass.
+
+        Falls back to the base ``WSMessage`` when the ``type`` field is
+        unrecognised.
+        """
+        data = json.loads(raw)
+        msg_type = data.get("type")
+        sub = _REGISTRY.get(msg_type)
+        if sub is not None:
+            return sub.from_json(raw)
+        return cls(**data)
+
+
+# ---------------------------------------------------------------------------
+# Concrete message types
+# ---------------------------------------------------------------------------
+
+
+@dataclass
+class AgentStateMessage(WSMessage):
+    """State update for a single agent."""
+
+    type: str = field(default=MessageType.AGENT_STATE)
+    agent_id: str = ""
+    data: dict[str, Any] = field(default_factory=dict)
+
+    @classmethod
+    def from_json(cls, raw: str) -> "AgentStateMessage":
+        payload = json.loads(raw)
+        return cls(
+            type=payload.get("type", MessageType.AGENT_STATE),
+            ts=payload.get("ts", time.time()),
+            agent_id=payload.get("agent_id", ""),
+            data=payload.get("data", {}),
+        )
+
+
+@dataclass
+class VisitorStateMessage(WSMessage):
+    """State update for a visitor / user session."""
+
+    type: str = field(default=MessageType.VISITOR_STATE)
+    visitor_id: str = ""
+    data: dict[str, Any] = field(default_factory=dict)
+
+    @classmethod
+    def from_json(cls, raw: str) -> "VisitorStateMessage":
+        payload = json.loads(raw)
+        return cls(
+            type=payload.get("type", MessageType.VISITOR_STATE),
+            ts=payload.get("ts", time.time()),
+            visitor_id=payload.get("visitor_id", ""),
+            data=payload.get("data", {}),
+        )
+
+
+@dataclass
+class BarkMessage(WSMessage):
+    """A bark (chat-like utterance) from an agent."""
+
+    type: str = field(default=MessageType.BARK)
+    agent_id: str = ""
+    content: str = ""
+
+    @classmethod
+    def from_json(cls, raw: str) -> "BarkMessage":
+        payload = json.loads(raw)
+        return cls(
+            type=payload.get("type", MessageType.BARK),
+            ts=payload.get("ts", time.time()),
+            agent_id=payload.get("agent_id", ""),
+            content=payload.get("content", ""),
+        )
+
+
+@dataclass
+class ThoughtMessage(WSMessage):
+    """An inner thought from an agent."""
+
+    type: str = field(default=MessageType.THOUGHT)
+    agent_id: str = ""
+    content: str = ""
+
+    @classmethod
+    def from_json(cls, raw: str) -> "ThoughtMessage":
+        payload = json.loads(raw)
+        return cls(
+            type=payload.get("type", MessageType.THOUGHT),
+            ts=payload.get("ts", time.time()),
+            agent_id=payload.get("agent_id", ""),
+            content=payload.get("content", ""),
+        )
+
+
+@dataclass
+class SystemStatusMessage(WSMessage):
+    """System-wide status broadcast."""
+
+    type: str = field(default=MessageType.SYSTEM_STATUS)
+    status: str = ""
+    data: dict[str, Any] = field(default_factory=dict)
+
+    @classmethod
+    def from_json(cls, raw: str) -> "SystemStatusMessage":
+        payload = json.loads(raw)
+        return cls(
+            type=payload.get("type", MessageType.SYSTEM_STATUS),
+            ts=payload.get("ts", time.time()),
+            status=payload.get("status", ""),
+            data=payload.get("data", {}),
+        )
+
+
+@dataclass
+class ConnectionAckMessage(WSMessage):
+    """Acknowledgement sent when a client connects."""
+
+    type: str = field(default=MessageType.CONNECTION_ACK)
+    client_id: str = ""
+
+    @classmethod
+    def from_json(cls, raw: str) -> "ConnectionAckMessage":
+        payload = json.loads(raw)
+        return cls(
+            type=payload.get("type", MessageType.CONNECTION_ACK),
+            ts=payload.get("ts", time.time()),
+            client_id=payload.get("client_id", ""),
+        )
+
+
+@dataclass
+class ErrorMessage(WSMessage):
+    """Error message sent to a client."""
+
+    type: str = field(default=MessageType.ERROR)
+    code: str = ""
+    message: str = ""
+
+    @classmethod
+    def from_json(cls, raw: str) -> "ErrorMessage":
+        payload = json.loads(raw)
+        return cls(
+            type=payload.get("type", MessageType.ERROR),
+            ts=payload.get("ts", time.time()),
+            code=payload.get("code", ""),
+            message=payload.get("message", ""),
+        )
+
+
+@dataclass
+class TaskUpdateMessage(WSMessage):
+    """Update about a task (created, assigned, completed, etc.)."""
+
+    type: str = field(default=MessageType.TASK_UPDATE)
+    task_id: str = ""
+    status: str = ""
+    data: dict[str, Any] = field(default_factory=dict)
+
+    @classmethod
+    def from_json(cls, raw: str) -> "TaskUpdateMessage":
+        payload = json.loads(raw)
+        return cls(
+            type=payload.get("type", MessageType.TASK_UPDATE),
+            ts=payload.get("ts", time.time()),
+            task_id=payload.get("task_id", ""),
+            status=payload.get("status", ""),
+            data=payload.get("data", {}),
+        )
+
+
+@dataclass
+class MemoryFlashMessage(WSMessage):
+    """A flash of memory — a recalled or stored memory event."""
+
+    type: str = field(default=MessageType.MEMORY_FLASH)
+    agent_id: str = ""
+    memory_key: str = ""
+    content: str = ""
+
+    @classmethod
+    def from_json(cls, raw: str) -> "MemoryFlashMessage":
+        payload = json.loads(raw)
+        return cls(
+            type=payload.get("type", MessageType.MEMORY_FLASH),
+            ts=payload.get("ts", time.time()),
+            agent_id=payload.get("agent_id", ""),
+            memory_key=payload.get("memory_key", ""),
+            content=payload.get("content", ""),
+        )
+
+
+# ---------------------------------------------------------------------------
+# Registry for from_json dispatch
+# ---------------------------------------------------------------------------
+
+_REGISTRY: dict[str, type[WSMessage]] = {
+    MessageType.AGENT_STATE: AgentStateMessage,
+    MessageType.VISITOR_STATE: VisitorStateMessage,
+    MessageType.BARK: BarkMessage,
+    MessageType.THOUGHT: ThoughtMessage,
+    MessageType.SYSTEM_STATUS: SystemStatusMessage,
+    MessageType.CONNECTION_ACK: ConnectionAckMessage,
+    MessageType.ERROR: ErrorMessage,
+    MessageType.TASK_UPDATE: TaskUpdateMessage,
+    MessageType.MEMORY_FLASH: MemoryFlashMessage,
+}

src/infrastructure/router/__init__.py

@@ -2,6 +2,7 @@
 
 from .api import router
 from .cascade import CascadeRouter, Provider, ProviderStatus, get_router
+from .history import HealthHistoryStore, get_history_store
 
 __all__ = [
     "CascadeRouter",
@@ -9,4 +10,6 @@ __all__ = [
     "ProviderStatus",
     "get_router",
     "router",
+    "HealthHistoryStore",
+    "get_history_store",
 ]

src/infrastructure/router/api.py

@@ -8,6 +8,7 @@ from fastapi import APIRouter, Depends, HTTPException
 from pydantic import BaseModel
 
 from .cascade import CascadeRouter, get_router
+from .history import HealthHistoryStore, get_history_store
 
 logger = logging.getLogger(__name__)
 router = APIRouter(prefix="/api/v1/router", tags=["router"])
@@ -183,6 +184,33 @@ async def run_health_check(
     }
 
 
+@router.post("/reload")
+async def reload_config(
+    cascade: Annotated[CascadeRouter, Depends(get_cascade_router)],
+) -> dict[str, Any]:
+    """Hot-reload providers.yaml without restart.
+
+    Preserves circuit breaker state and metrics for existing providers.
+    """
+    try:
+        result = cascade.reload_config()
+        return {"status": "ok", **result}
+    except Exception as exc:
+        logger.error("Config reload failed: %s", exc)
+        raise HTTPException(status_code=500, detail=f"Reload failed: {exc}") from exc
+
+
+@router.get("/history")
+async def get_history(
+    hours: int = 24,
+    store: Annotated[HealthHistoryStore, Depends(get_history_store)] = None,
+) -> list[dict[str, Any]]:
+    """Get provider health history for the last N hours."""
+    if store is None:
+        store = get_history_store()
+    return store.get_history(hours=hours)
+
+
 @router.get("/config")
 async def get_config(
     cascade: Annotated[CascadeRouter, Depends(get_cascade_router)],

src/infrastructure/router/cascade.py

@@ -18,6 +18,8 @@ from enum import Enum
 from pathlib import Path
 from typing import Any
 
+from config import settings
+
 try:
     import yaml
 except ImportError:
@@ -100,7 +102,7 @@ class Provider:
     """LLM provider configuration and state."""
 
     name: str
-    type: str  # ollama, openai, anthropic, airllm
+    type: str  # ollama, openai, anthropic
     enabled: bool
     priority: int
     url: str | None = None
@@ -219,65 +221,56 @@ class CascadeRouter:
                 raise RuntimeError("PyYAML not installed")
 
             content = self.config_path.read_text()
-            # Expand environment variables
             content = self._expand_env_vars(content)
             data = yaml.safe_load(content)
 
-            # Load cascade settings
-            cascade = data.get("cascade", {})
-
-            # Load fallback chains
-            fallback_chains = data.get("fallback_chains", {})
-
-            # Load multi-modal settings
-            multimodal = data.get("multimodal", {})
-
-            self.config = RouterConfig(
-                timeout_seconds=cascade.get("timeout_seconds", 30),
-                max_retries_per_provider=cascade.get("max_retries_per_provider", 2),
-                retry_delay_seconds=cascade.get("retry_delay_seconds", 1),
-                circuit_breaker_failure_threshold=cascade.get("circuit_breaker", {}).get(
-                    "failure_threshold", 5
-                ),
-                circuit_breaker_recovery_timeout=cascade.get("circuit_breaker", {}).get(
-                    "recovery_timeout", 60
-                ),
-                circuit_breaker_half_open_max_calls=cascade.get("circuit_breaker", {}).get(
-                    "half_open_max_calls", 2
-                ),
-                auto_pull_models=multimodal.get("auto_pull", True),
-                fallback_chains=fallback_chains,
-            )
-
-            # Load providers
-            for p_data in data.get("providers", []):
-                # Skip disabled providers
-                if not p_data.get("enabled", False):
-                    continue
-
-                provider = Provider(
-                    name=p_data["name"],
-                    type=p_data["type"],
-                    enabled=p_data.get("enabled", True),
-                    priority=p_data.get("priority", 99),
-                    url=p_data.get("url"),
-                    api_key=p_data.get("api_key"),
-                    base_url=p_data.get("base_url"),
-                    models=p_data.get("models", []),
-                )
-
-                # Check if provider is actually available
-                if self._check_provider_available(provider):
-                    self.providers.append(provider)
-                else:
-                    logger.warning("Provider %s not available, skipping", provider.name)
-
-            # Sort by priority
-            self.providers.sort(key=lambda p: p.priority)
+            self.config = self._parse_router_config(data)
+            self._load_providers(data)
 
         except Exception as exc:
             logger.error("Failed to load config: %s", exc)
 
+    def _parse_router_config(self, data: dict) -> RouterConfig:
+        """Build a RouterConfig from parsed YAML data."""
+        cascade = data.get("cascade", {})
+        cb = cascade.get("circuit_breaker", {})
+        multimodal = data.get("multimodal", {})
+
+        return RouterConfig(
+            timeout_seconds=cascade.get("timeout_seconds", 30),
+            max_retries_per_provider=cascade.get("max_retries_per_provider", 2),
+            retry_delay_seconds=cascade.get("retry_delay_seconds", 1),
+            circuit_breaker_failure_threshold=cb.get("failure_threshold", 5),
+            circuit_breaker_recovery_timeout=cb.get("recovery_timeout", 60),
+            circuit_breaker_half_open_max_calls=cb.get("half_open_max_calls", 2),
+            auto_pull_models=multimodal.get("auto_pull", True),
+            fallback_chains=data.get("fallback_chains", {}),
+        )
+
+    def _load_providers(self, data: dict) -> None:
+        """Load, filter, and sort providers from parsed YAML data."""
+        for p_data in data.get("providers", []):
+            if not p_data.get("enabled", False):
+                continue
+
+            provider = Provider(
+                name=p_data["name"],
+                type=p_data["type"],
+                enabled=p_data.get("enabled", True),
+                priority=p_data.get("priority", 99),
+                url=p_data.get("url"),
+                api_key=p_data.get("api_key"),
+                base_url=p_data.get("base_url"),
+                models=p_data.get("models", []),
+            )
+
+            if self._check_provider_available(provider):
+                self.providers.append(provider)
+            else:
+                logger.warning("Provider %s not available, skipping", provider.name)
+
+        self.providers.sort(key=lambda p: p.priority)
+
     def _expand_env_vars(self, content: str) -> str:
         """Expand ${VAR} syntax in YAML content.
 
@@ -301,22 +294,13 @@ class CascadeRouter:
                 # Can't check without requests, assume available
                 return True
             try:
-                url = provider.url or "http://localhost:11434"
+                url = provider.url or settings.ollama_url
                 response = requests.get(f"{url}/api/tags", timeout=5)
                 return response.status_code == 200
             except Exception as exc:
                 logger.debug("Ollama provider check error: %s", exc)
                 return False
 
-        elif provider.type == "airllm":
-            # Check if airllm is installed
-            try:
-                import importlib.util
-
-                return importlib.util.find_spec("airllm") is not None
-            except (ImportError, ModuleNotFoundError):
-                return False
-
         elif provider.type in ("openai", "anthropic", "grok"):
             # Check if API key is set
             return provider.api_key is not None and provider.api_key != ""
@@ -395,6 +379,101 @@ class CascadeRouter:
 
         return None
 
+    def _select_model(
+        self, provider: Provider, model: str | None, content_type: ContentType
+    ) -> tuple[str | None, bool]:
+        """Select the best model for the request, with vision fallback.
+
+        Returns:
+            Tuple of (selected_model, is_fallback_model).
+        """
+        selected_model = model or provider.get_default_model()
+        is_fallback = False
+
+        if content_type != ContentType.TEXT and selected_model:
+            if provider.type == "ollama" and self._mm_manager:
+                from infrastructure.models.multimodal import ModelCapability
+
+                if content_type == ContentType.VISION:
+                    supports = self._mm_manager.model_supports(
+                        selected_model, ModelCapability.VISION
+                    )
+                    if not supports:
+                        fallback = self._get_fallback_model(provider, selected_model, content_type)
+                        if fallback:
+                            logger.info(
+                                "Model %s doesn't support vision, falling back to %s",
+                                selected_model,
+                                fallback,
+                            )
+                            selected_model = fallback
+                            is_fallback = True
+                        else:
+                            logger.warning(
+                                "No vision-capable model found on %s, trying anyway",
+                                provider.name,
+                            )
+
+        return selected_model, is_fallback
+
+    async def _attempt_with_retry(
+        self,
+        provider: Provider,
+        messages: list[dict],
+        model: str | None,
+        temperature: float,
+        max_tokens: int | None,
+        content_type: ContentType,
+    ) -> dict:
+        """Try a provider with retries, returning the result dict.
+
+        Raises:
+            RuntimeError: If all retry attempts fail.
+            Returns error strings collected during retries via the exception message.
+        """
+        errors: list[str] = []
+        for attempt in range(self.config.max_retries_per_provider):
+            try:
+                return await self._try_provider(
+                    provider=provider,
+                    messages=messages,
+                    model=model,
+                    temperature=temperature,
+                    max_tokens=max_tokens,
+                    content_type=content_type,
+                )
+            except Exception as exc:
+                error_msg = str(exc)
+                logger.warning(
+                    "Provider %s attempt %d failed: %s",
+                    provider.name,
+                    attempt + 1,
+                    error_msg,
+                )
+                errors.append(f"{provider.name}: {error_msg}")
+
+                if attempt < self.config.max_retries_per_provider - 1:
+                    await asyncio.sleep(self.config.retry_delay_seconds)
+
+        raise RuntimeError("; ".join(errors))
+
+    def _is_provider_available(self, provider: Provider) -> bool:
+        """Check if a provider should be tried (enabled + circuit breaker)."""
+        if not provider.enabled:
+            logger.debug("Skipping %s (disabled)", provider.name)
+            return False
+
+        if provider.status == ProviderStatus.UNHEALTHY:
+            if self._can_close_circuit(provider):
+                provider.circuit_state = CircuitState.HALF_OPEN
+                provider.half_open_calls = 0
+                logger.info("Circuit breaker half-open for %s", provider.name)
+            else:
+                logger.debug("Skipping %s (circuit open)", provider.name)
+                return False
+
+        return True
+
     async def complete(
         self,
         messages: list[dict],
@@ -421,7 +500,6 @@ class CascadeRouter:
         Raises:
             RuntimeError: If all providers fail
         """
-        # Detect content type for multi-modal routing
         content_type = self._detect_content_type(messages)
         if content_type != ContentType.TEXT:
             logger.debug("Detected %s content, selecting appropriate model", content_type.value)
@@ -429,93 +507,34 @@ class CascadeRouter:
         errors = []
 
         for provider in self.providers:
-            # Skip disabled providers
-            if not provider.enabled:
-                logger.debug("Skipping %s (disabled)", provider.name)
+            if not self._is_provider_available(provider):
                 continue
 
-            # Skip unhealthy providers (circuit breaker)
-            if provider.status == ProviderStatus.UNHEALTHY:
-                # Check if circuit breaker can close
-                if self._can_close_circuit(provider):
-                    provider.circuit_state = CircuitState.HALF_OPEN
-                    provider.half_open_calls = 0
-                    logger.info("Circuit breaker half-open for %s", provider.name)
-                else:
-                    logger.debug("Skipping %s (circuit open)", provider.name)
-                    continue
+            selected_model, is_fallback_model = self._select_model(provider, model, content_type)
 
-            # Determine which model to use
-            selected_model = model or provider.get_default_model()
-            is_fallback_model = False
+            try:
+                result = await self._attempt_with_retry(
+                    provider,
+                    messages,
+                    selected_model,
+                    temperature,
+                    max_tokens,
+                    content_type,
+                )
+            except RuntimeError as exc:
+                errors.append(str(exc))
+                self._record_failure(provider)
+                continue
 
-            # For non-text content, check if model supports it
-            if content_type != ContentType.TEXT and selected_model:
-                if provider.type == "ollama" and self._mm_manager:
-                    from infrastructure.models.multimodal import ModelCapability
+            self._record_success(provider, result.get("latency_ms", 0))
+            return {
+                "content": result["content"],
+                "provider": provider.name,
+                "model": result.get("model", selected_model or provider.get_default_model()),
+                "latency_ms": result.get("latency_ms", 0),
+                "is_fallback_model": is_fallback_model,
+            }
 
-                    # Check if selected model supports the required capability
-                    if content_type == ContentType.VISION:
-                        supports = self._mm_manager.model_supports(
-                            selected_model, ModelCapability.VISION
-                        )
-                        if not supports:
-                            # Find fallback model
-                            fallback = self._get_fallback_model(
-                                provider, selected_model, content_type
-                            )
-                            if fallback:
-                                logger.info(
-                                    "Model %s doesn't support vision, falling back to %s",
-                                    selected_model,
-                                    fallback,
-                                )
-                                selected_model = fallback
-                                is_fallback_model = True
-                            else:
-                                logger.warning(
-                                    "No vision-capable model found on %s, trying anyway",
-                                    provider.name,
-                                )
-
-            # Try this provider
-            for attempt in range(self.config.max_retries_per_provider):
-                try:
-                    result = await self._try_provider(
-                        provider=provider,
-                        messages=messages,
-                        model=selected_model,
-                        temperature=temperature,
-                        max_tokens=max_tokens,
-                        content_type=content_type,
-                    )
-
-                    # Success! Update metrics and return
-                    self._record_success(provider, result.get("latency_ms", 0))
-                    return {
-                        "content": result["content"],
-                        "provider": provider.name,
-                        "model": result.get(
-                            "model", selected_model or provider.get_default_model()
-                        ),
-                        "latency_ms": result.get("latency_ms", 0),
-                        "is_fallback_model": is_fallback_model,
-                    }
-
-                except Exception as exc:
-                    error_msg = str(exc)
-                    logger.warning(
-                        "Provider %s attempt %d failed: %s", provider.name, attempt + 1, error_msg
-                    )
-                    errors.append(f"{provider.name}: {error_msg}")
-
-                    if attempt < self.config.max_retries_per_provider - 1:
-                        await asyncio.sleep(self.config.retry_delay_seconds)
-
-            # All retries failed for this provider
-            self._record_failure(provider)
-
-        # All providers failed
         raise RuntimeError(f"All providers failed: {'; '.join(errors)}")
 
     async def _try_provider(
@@ -536,6 +555,7 @@ class CascadeRouter:
                 messages=messages,
                 model=model or provider.get_default_model(),
                 temperature=temperature,
+                max_tokens=max_tokens,
                 content_type=content_type,
             )
         elif provider.type == "openai":
@@ -576,23 +596,26 @@ class CascadeRouter:
         messages: list[dict],
         model: str,
         temperature: float,
+        max_tokens: int | None = None,
         content_type: ContentType = ContentType.TEXT,
     ) -> dict:
         """Call Ollama API with multi-modal support."""
         import aiohttp
 
-        url = f"{provider.url}/api/chat"
+        url = f"{provider.url or settings.ollama_url}/api/chat"
 
         # Transform messages for Ollama format (including images)
         transformed_messages = self._transform_messages_for_ollama(messages)
 
+        options = {"temperature": temperature}
+        if max_tokens:
+            options["num_predict"] = max_tokens
+
         payload = {
             "model": model,
             "messages": transformed_messages,
             "stream": False,
-            "options": {
-                "temperature": temperature,
-            },
+            "options": options,
         }
 
         timeout = aiohttp.ClientTimeout(total=self.config.timeout_seconds)
@@ -736,7 +759,7 @@ class CascadeRouter:
 
         client = openai.AsyncOpenAI(
             api_key=provider.api_key,
-            base_url=provider.base_url or "https://api.x.ai/v1",
+            base_url=provider.base_url or settings.xai_base_url,
             timeout=httpx.Timeout(300.0),
         )
 
@@ -815,6 +838,66 @@ class CascadeRouter:
         provider.status = ProviderStatus.HEALTHY
         logger.info("Circuit breaker CLOSED for %s", provider.name)
 
+    def reload_config(self) -> dict:
+        """Hot-reload providers.yaml, preserving runtime state.
+
+        Re-reads the config file, rebuilds the provider list, and
+        preserves circuit breaker state and metrics for providers
+        that still exist after reload.
+
+        Returns:
+            Summary dict with added/removed/preserved counts.
+        """
+        # Snapshot current runtime state keyed by provider name
+        old_state: dict[
+            str, tuple[ProviderMetrics, CircuitState, float | None, int, ProviderStatus]
+        ] = {}
+        for p in self.providers:
+            old_state[p.name] = (
+                p.metrics,
+                p.circuit_state,
+                p.circuit_opened_at,
+                p.half_open_calls,
+                p.status,
+            )
+
+        old_names = set(old_state.keys())
+
+        # Reload from disk
+        self.providers = []
+        self._load_config()
+
+        # Restore preserved state
+        new_names = {p.name for p in self.providers}
+        preserved = 0
+        for p in self.providers:
+            if p.name in old_state:
+                metrics, circuit, opened_at, half_open, status = old_state[p.name]
+                p.metrics = metrics
+                p.circuit_state = circuit
+                p.circuit_opened_at = opened_at
+                p.half_open_calls = half_open
+                p.status = status
+                preserved += 1
+
+        added = new_names - old_names
+        removed = old_names - new_names
+
+        logger.info(
+            "Config reloaded: %d providers (%d preserved, %d added, %d removed)",
+            len(self.providers),
+            preserved,
+            len(added),
+            len(removed),
+        )
+
+        return {
+            "total_providers": len(self.providers),
+            "preserved": preserved,
+            "added": sorted(added),
+            "removed": sorted(removed),
+        }
+
     def get_metrics(self) -> dict:
         """Get metrics for all providers."""
         return {

src/infrastructure/router/history.py

@@ -0,0 +1,152 @@
+"""Provider health history — time-series snapshots for dashboard visualization."""
+
+import asyncio
+import logging
+import sqlite3
+from datetime import UTC, datetime, timedelta
+from pathlib import Path
+
+logger = logging.getLogger(__name__)
+
+_store: "HealthHistoryStore | None" = None
+
+
+class HealthHistoryStore:
+    """Stores timestamped provider health snapshots in SQLite."""
+
+    def __init__(self, db_path: str = "data/router_history.db") -> None:
+        self.db_path = db_path
+        if db_path != ":memory:":
+            Path(db_path).parent.mkdir(parents=True, exist_ok=True)
+        self._conn = sqlite3.connect(db_path, check_same_thread=False)
+        self._conn.row_factory = sqlite3.Row
+        self._init_schema()
+        self._bg_task: asyncio.Task | None = None
+
+    def _init_schema(self) -> None:
+        self._conn.execute("""
+            CREATE TABLE IF NOT EXISTS snapshots (
+                id INTEGER PRIMARY KEY AUTOINCREMENT,
+                timestamp TEXT NOT NULL,
+                provider_name TEXT NOT NULL,
+                status TEXT NOT NULL,
+                error_rate REAL NOT NULL,
+                avg_latency_ms REAL NOT NULL,
+                circuit_state TEXT NOT NULL,
+                total_requests INTEGER NOT NULL
+            )
+        """)
+        self._conn.execute("""
+            CREATE INDEX IF NOT EXISTS idx_snapshots_ts
+            ON snapshots(timestamp)
+        """)
+        self._conn.commit()
+
+    def record_snapshot(self, providers: list[dict]) -> None:
+        """Record a health snapshot for all providers."""
+        ts = datetime.now(UTC).isoformat()
+        rows = [
+            (
+                ts,
+                p["name"],
+                p["status"],
+                p["error_rate"],
+                p["avg_latency_ms"],
+                p["circuit_state"],
+                p["total_requests"],
+            )
+            for p in providers
+        ]
+        self._conn.executemany(
+            """INSERT INTO snapshots
+               (timestamp, provider_name, status, error_rate,
+                avg_latency_ms, circuit_state, total_requests)
+               VALUES (?, ?, ?, ?, ?, ?, ?)""",
+            rows,
+        )
+        self._conn.commit()
+
+    def get_history(self, hours: int = 24) -> list[dict]:
+        """Return snapshots from the last N hours, grouped by timestamp."""
+        cutoff = (datetime.now(UTC) - timedelta(hours=hours)).isoformat()
+        rows = self._conn.execute(
+            """SELECT timestamp, provider_name, status, error_rate,
+                      avg_latency_ms, circuit_state, total_requests
+               FROM snapshots WHERE timestamp >= ? ORDER BY timestamp""",
+            (cutoff,),
+        ).fetchall()
+
+        # Group by timestamp
+        snapshots: dict[str, list[dict]] = {}
+        for row in rows:
+            ts = row["timestamp"]
+            if ts not in snapshots:
+                snapshots[ts] = []
+            snapshots[ts].append(
+                {
+                    "name": row["provider_name"],
+                    "status": row["status"],
+                    "error_rate": row["error_rate"],
+                    "avg_latency_ms": row["avg_latency_ms"],
+                    "circuit_state": row["circuit_state"],
+                    "total_requests": row["total_requests"],
+                }
+            )
+
+        return [{"timestamp": ts, "providers": providers} for ts, providers in snapshots.items()]
+
+    def prune(self, keep_hours: int = 168) -> int:
+        """Remove snapshots older than keep_hours. Returns rows deleted."""
+        cutoff = (datetime.now(UTC) - timedelta(hours=keep_hours)).isoformat()
+        cursor = self._conn.execute("DELETE FROM snapshots WHERE timestamp < ?", (cutoff,))
+        self._conn.commit()
+        return cursor.rowcount
+
+    def close(self) -> None:
+        """Close the database connection."""
+        if self._bg_task and not self._bg_task.done():
+            self._bg_task.cancel()
+        self._conn.close()
+
+    def _capture_snapshot(self, cascade_router) -> None:  # noqa: ANN001
+        """Capture current provider state as a snapshot."""
+        providers = []
+        for p in cascade_router.providers:
+            providers.append(
+                {
+                    "name": p.name,
+                    "status": p.status.value,
+                    "error_rate": round(p.metrics.error_rate, 4),
+                    "avg_latency_ms": round(p.metrics.avg_latency_ms, 2),
+                    "circuit_state": p.circuit_state.value,
+                    "total_requests": p.metrics.total_requests,
+                }
+            )
+        self.record_snapshot(providers)
+
+    async def start_background_task(
+        self,
+        cascade_router,
+        interval_seconds: int = 60,  # noqa: ANN001
+    ) -> None:
+        """Start periodic snapshot capture."""
+
+        async def _loop() -> None:
+            while True:
+                try:
+                    self._capture_snapshot(cascade_router)
+                    logger.debug("Recorded health snapshot")
+                except Exception:
+                    logger.exception("Failed to record health snapshot")
+                await asyncio.sleep(interval_seconds)
+
+        self._bg_task = asyncio.create_task(_loop())
+        logger.info("Health history background task started (interval=%ds)", interval_seconds)
+
+
+def get_history_store() -> HealthHistoryStore:
+    """Get or create the singleton history store."""
+    global _store  # noqa: PLW0603
+    if _store is None:
+        _store = HealthHistoryStore()
+    return _store

src/infrastructure/visitor.py

@@ -0,0 +1,166 @@
+"""Visitor state tracking for the Matrix frontend.
+
+Tracks active visitors as they connect and move around the 3D world,
+and provides serialization for Matrix protocol broadcast messages.
+"""
+
+import time
+from dataclasses import dataclass, field
+from datetime import UTC, datetime
+
+
+@dataclass
+class VisitorState:
+    """State for a single visitor in the Matrix.
+
+    Attributes
+    ----------
+    visitor_id: Unique identifier for the visitor (client ID).
+    display_name: Human-readable name shown above the visitor.
+    position: 3D coordinates (x, y, z) in the world.
+    rotation: Rotation angle in degrees (0-360).
+    connected_at: ISO timestamp when the visitor connected.
+    """
+
+    visitor_id: str
+    display_name: str = ""
+    position: dict[str, float] = field(default_factory=lambda: {"x": 0.0, "y": 0.0, "z": 0.0})
+    rotation: float = 0.0
+    connected_at: str = field(
+        default_factory=lambda: datetime.now(UTC).strftime("%Y-%m-%dT%H:%M:%SZ")
+    )
+
+    def __post_init__(self):
+        """Set display_name to visitor_id if not provided; copy position dict."""
+        if not self.display_name:
+            self.display_name = self.visitor_id
+        # Copy position to avoid shared mutable state
+        self.position = dict(self.position)
+
+
+class VisitorRegistry:
+    """Registry of active visitors in the Matrix.
+
+    Thread-safe singleton pattern (Python GIL protects dict operations).
+    Used by the WebSocket layer to track and broadcast visitor positions.
+    """
+
+    _instance: "VisitorRegistry | None" = None
+
+    def __new__(cls) -> "VisitorRegistry":
+        """Singleton constructor."""
+        if cls._instance is None:
+            cls._instance = super().__new__(cls)
+            cls._instance._visitors: dict[str, VisitorState] = {}
+        return cls._instance
+
+    def add(
+        self, visitor_id: str, display_name: str = "", position: dict | None = None
+    ) -> VisitorState:
+        """Add a new visitor to the registry.
+
+        Parameters
+        ----------
+        visitor_id: Unique identifier for the visitor.
+        display_name: Optional display name (defaults to visitor_id).
+        position: Optional initial position (defaults to origin).
+
+        Returns
+        -------
+        The newly created VisitorState.
+        """
+        visitor = VisitorState(
+            visitor_id=visitor_id,
+            display_name=display_name,
+            position=position if position else {"x": 0.0, "y": 0.0, "z": 0.0},
+        )
+        self._visitors[visitor_id] = visitor
+        return visitor
+
+    def remove(self, visitor_id: str) -> bool:
+        """Remove a visitor from the registry.
+
+        Parameters
+        ----------
+        visitor_id: The visitor to remove.
+
+        Returns
+        -------
+        True if the visitor was found and removed, False otherwise.
+        """
+        if visitor_id in self._visitors:
+            del self._visitors[visitor_id]
+            return True
+        return False
+
+    def update_position(
+        self,
+        visitor_id: str,
+        position: dict[str, float],
+        rotation: float | None = None,
+    ) -> bool:
+        """Update a visitor's position and rotation.
+
+        Parameters
+        ----------
+        visitor_id: The visitor to update.
+        position: New 3D coordinates (x, y, z).
+        rotation: Optional new rotation angle.
+
+        Returns
+        -------
+        True if the visitor was found and updated, False otherwise.
+        """
+        if visitor_id not in self._visitors:
+            return False
+
+        self._visitors[visitor_id].position = position
+        if rotation is not None:
+            self._visitors[visitor_id].rotation = rotation
+        return True
+
+    def get(self, visitor_id: str) -> VisitorState | None:
+        """Get a single visitor's state.
+
+        Parameters
+        ----------
+        visitor_id: The visitor to retrieve.
+
+        Returns
+        -------
+        The VisitorState if found, None otherwise.
+        """
+        return self._visitors.get(visitor_id)
+
+    def get_all(self) -> list[dict]:
+        """Get all active visitors as Matrix protocol message dicts.
+
+        Returns
+        -------
+        List of visitor_state dicts ready for WebSocket broadcast.
+        Each dict has: type, visitor_id, data (with display_name,
+        position, rotation, connected_at), and ts.
+        """
+        now = int(time.time())
+        return [
+            {
+                "type": "visitor_state",
+                "visitor_id": v.visitor_id,
+                "data": {
+                    "display_name": v.display_name,
+                    "position": v.position,
+                    "rotation": v.rotation,
+                    "connected_at": v.connected_at,
+                },
+                "ts": now,
+            }
+            for v in self._visitors.values()
+        ]
+
+    def clear(self) -> None:
+        """Remove all visitors (useful for testing)."""
+        self._visitors.clear()
+
+    def __len__(self) -> int:
+        """Return the number of active visitors."""
+        return len(self._visitors)

src/integrations/chat_bridge/vendors/discord.py

@@ -515,25 +515,36 @@ class DiscordVendor(ChatPlatform):
 
     async def _handle_message(self, message) -> None:
         """Process an incoming message and respond via a thread."""
-        # Strip the bot mention from the message content
-        content = message.content
-        if self._client.user:
-            content = content.replace(f"<@{self._client.user.id}>", "").strip()
-
+        content = self._extract_content(message)
         if not content:
             return
 
-        # Create or reuse a thread for this conversation
         thread = await self._get_or_create_thread(message)
         target = thread or message.channel
+        session_id = f"discord_{thread.id}" if thread else f"discord_{message.channel.id}"
 
-        # Derive session_id for per-conversation history via Agno's SQLite
-        if thread:
-            session_id = f"discord_{thread.id}"
-        else:
-            session_id = f"discord_{message.channel.id}"
+        run_output, response = await self._invoke_agent(content, session_id, target)
 
-        # Run Timmy agent with typing indicator and timeout
+        if run_output is not None:
+            await self._handle_paused_run(run_output, target, session_id)
+            raw_content = run_output.content if hasattr(run_output, "content") else ""
+            response = _clean_response(raw_content or "")
+
+        await self._send_response(response, target)
+
+    def _extract_content(self, message) -> str:
+        """Strip the bot mention and return clean message text."""
+        content = message.content
+        if self._client.user:
+            content = content.replace(f"<@{self._client.user.id}>", "").strip()
+        return content
+
+    async def _invoke_agent(self, content: str, session_id: str, target):
+        """Run chat_with_tools with a typing indicator and timeout.
+
+        Returns a (run_output, error_response) tuple.  On success the
+        error_response is ``None``; on failure run_output is ``None``.
+        """
         run_output = None
         response = None
         try:
@@ -547,54 +558,58 @@ class DiscordVendor(ChatPlatform):
             response = "Sorry, that took too long. Please try a simpler request."
         except Exception as exc:
             logger.error("Discord: chat_with_tools() failed: %s", exc)
-            response = (
-                "I'm having trouble reaching my language model right now. Please try again shortly."
+            response = "I'm having trouble reaching my inference backend right now. Please try again shortly."
+        return run_output, response
+
+    async def _handle_paused_run(self, run_output, target, session_id: str) -> None:
+        """If Agno paused the run for tool confirmation, enqueue approvals."""
+        status = getattr(run_output, "status", None)
+        is_paused = status == "PAUSED" or str(status) == "RunStatus.paused"
+
+        if not (is_paused and getattr(run_output, "active_requirements", None)):
+            return
+
+        from config import settings
+
+        if not settings.discord_confirm_actions:
+            return
+
+        for req in run_output.active_requirements:
+            if not getattr(req, "needs_confirmation", False):
+                continue
+            te = req.tool_execution
+            tool_name = getattr(te, "tool_name", "unknown")
+            tool_args = getattr(te, "tool_args", {}) or {}
+
+            from timmy.approvals import create_item
+
+            item = create_item(
+                title=f"Discord: {tool_name}",
+                description=_format_action_description(tool_name, tool_args),
+                proposed_action=json.dumps({"tool": tool_name, "args": tool_args}),
+                impact=_get_impact_level(tool_name),
             )
+            self._pending_actions[item.id] = {
+                "run_output": run_output,
+                "requirement": req,
+                "tool_name": tool_name,
+                "tool_args": tool_args,
+                "target": target,
+                "session_id": session_id,
+            }
+            await self._send_confirmation(target, tool_name, tool_args, item.id)
 
-        # Check if Agno paused the run for tool confirmation
-        if run_output is not None:
-            status = getattr(run_output, "status", None)
-            is_paused = status == "PAUSED" or str(status) == "RunStatus.paused"
-
-            if is_paused and getattr(run_output, "active_requirements", None):
-                from config import settings
-
-                if settings.discord_confirm_actions:
-                    for req in run_output.active_requirements:
-                        if getattr(req, "needs_confirmation", False):
-                            te = req.tool_execution
-                            tool_name = getattr(te, "tool_name", "unknown")
-                            tool_args = getattr(te, "tool_args", {}) or {}
-
-                            from timmy.approvals import create_item
-
-                            item = create_item(
-                                title=f"Discord: {tool_name}",
-                                description=_format_action_description(tool_name, tool_args),
-                                proposed_action=json.dumps({"tool": tool_name, "args": tool_args}),
-                                impact=_get_impact_level(tool_name),
-                            )
-                            self._pending_actions[item.id] = {
-                                "run_output": run_output,
-                                "requirement": req,
-                                "tool_name": tool_name,
-                                "tool_args": tool_args,
-                                "target": target,
-                                "session_id": session_id,
-                            }
-                            await self._send_confirmation(target, tool_name, tool_args, item.id)
-
-            raw_content = run_output.content if hasattr(run_output, "content") else ""
-            response = _clean_response(raw_content or "")
-
-        # Discord has a 2000 character limit — send with error handling
-        if response and response.strip():
-            for chunk in _chunk_message(response, 2000):
-                try:
-                    await target.send(chunk)
-                except Exception as exc:
-                    logger.error("Discord: failed to send message chunk: %s", exc)
-                    break
+    @staticmethod
+    async def _send_response(response: str | None, target) -> None:
+        """Send a response to Discord, chunked to the 2000-char limit."""
+        if not response or not response.strip():
+            return
+        for chunk in _chunk_message(response, 2000):
+            try:
+                await target.send(chunk)
+            except Exception as exc:
+                logger.error("Discord: failed to send message chunk: %s", exc)
+                break
 
     async def _get_or_create_thread(self, message):
         """Get the active thread for a channel, or create one.

src/lightning/__init__.py

@@ -0,0 +1 @@
+"""Lightning Network integration for tool-usage micro-payments."""

src/lightning/factory.py

@@ -0,0 +1,69 @@
+"""Lightning backend factory.
+
+Returns a mock or real LND backend based on ``settings.lightning_backend``.
+"""
+
+from __future__ import annotations
+
+import hashlib
+import logging
+import secrets
+from dataclasses import dataclass
+
+from config import settings
+
+logger = logging.getLogger(__name__)
+
+
+@dataclass
+class Invoice:
+    """Minimal Lightning invoice representation."""
+
+    payment_hash: str
+    payment_request: str
+    amount_sats: int
+    memo: str
+
+
+class MockBackend:
+    """In-memory mock Lightning backend for development and testing."""
+
+    def create_invoice(self, amount_sats: int, memo: str = "") -> Invoice:
+        """Create a fake invoice with a random payment hash."""
+        raw = secrets.token_bytes(32)
+        payment_hash = hashlib.sha256(raw).hexdigest()
+        payment_request = f"lnbc{amount_sats}mock{payment_hash[:20]}"
+        logger.debug("Mock invoice: %s sats — %s", amount_sats, payment_hash[:12])
+        return Invoice(
+            payment_hash=payment_hash,
+            payment_request=payment_request,
+            amount_sats=amount_sats,
+            memo=memo,
+        )
+
+
+# Singleton — lazily created
+_backend: MockBackend | None = None
+
+
+def get_backend() -> MockBackend:
+    """Return the configured Lightning backend (currently mock-only).
+
+    Raises ``ValueError`` if an unsupported backend is requested.
+    """
+    global _backend  # noqa: PLW0603
+    if _backend is not None:
+        return _backend
+
+    kind = settings.lightning_backend
+    if kind == "mock":
+        _backend = MockBackend()
+    elif kind == "lnd":
+        # LND gRPC integration is on the roadmap — for now fall back to mock.
+        logger.warning("LND backend not yet implemented — using mock")
+        _backend = MockBackend()
+    else:
+        raise ValueError(f"Unknown lightning_backend: {kind!r}")
+
+    logger.info("Lightning backend: %s", kind)
+    return _backend

src/lightning/ledger.py

@@ -0,0 +1,146 @@
+"""In-memory Lightning transaction ledger.
+
+Tracks invoices, settlements, and balances per the schema in
+``docs/adr/018-lightning-ledger.md``.  Uses a simple in-memory list so the
+dashboard can display real (ephemeral) data without requiring SQLite yet.
+"""
+
+from __future__ import annotations
+
+import logging
+import uuid
+from dataclasses import dataclass
+from datetime import UTC, datetime
+from enum import StrEnum
+
+logger = logging.getLogger(__name__)
+
+
+class TxType(StrEnum):
+    incoming = "incoming"
+    outgoing = "outgoing"
+
+
+class TxStatus(StrEnum):
+    pending = "pending"
+    settled = "settled"
+    failed = "failed"
+    expired = "expired"
+
+
+@dataclass
+class LedgerEntry:
+    """Single ledger row matching the ADR-018 schema."""
+
+    id: str
+    tx_type: TxType
+    status: TxStatus
+    payment_hash: str
+    amount_sats: int
+    memo: str
+    source: str
+    created_at: str
+    invoice: str = ""
+    preimage: str = ""
+    task_id: str = ""
+    agent_id: str = ""
+    settled_at: str = ""
+    fee_sats: int = 0
+
+
+# ── In-memory store ──────────────────────────────────────────────────
+_entries: list[LedgerEntry] = []
+
+
+def create_invoice_entry(
+    payment_hash: str,
+    amount_sats: int,
+    memo: str = "",
+    source: str = "tool_usage",
+    task_id: str = "",
+    agent_id: str = "",
+    invoice: str = "",
+) -> LedgerEntry:
+    """Record a new incoming invoice in the ledger."""
+    entry = LedgerEntry(
+        id=uuid.uuid4().hex[:16],
+        tx_type=TxType.incoming,
+        status=TxStatus.pending,
+        payment_hash=payment_hash,
+        amount_sats=amount_sats,
+        memo=memo,
+        source=source,
+        task_id=task_id,
+        agent_id=agent_id,
+        invoice=invoice,
+        created_at=datetime.now(UTC).isoformat(),
+    )
+    _entries.append(entry)
+    logger.debug("Ledger entry created: %s (%s sats)", entry.id, amount_sats)
+    return entry
+
+
+def mark_settled(payment_hash: str, preimage: str = "") -> LedgerEntry | None:
+    """Mark a pending entry as settled by payment hash."""
+    for entry in _entries:
+        if entry.payment_hash == payment_hash and entry.status == TxStatus.pending:
+            entry.status = TxStatus.settled
+            entry.preimage = preimage
+            entry.settled_at = datetime.now(UTC).isoformat()
+            logger.debug("Ledger settled: %s", payment_hash[:12])
+            return entry
+    return None
+
+
+def get_balance() -> dict:
+    """Compute the current balance from settled and pending entries."""
+    incoming_total = sum(
+        e.amount_sats
+        for e in _entries
+        if e.tx_type == TxType.incoming and e.status == TxStatus.settled
+    )
+    outgoing_total = sum(
+        e.amount_sats
+        for e in _entries
+        if e.tx_type == TxType.outgoing and e.status == TxStatus.settled
+    )
+    fees = sum(e.fee_sats for e in _entries if e.status == TxStatus.settled)
+    pending_in = sum(
+        e.amount_sats
+        for e in _entries
+        if e.tx_type == TxType.incoming and e.status == TxStatus.pending
+    )
+    pending_out = sum(
+        e.amount_sats
+        for e in _entries
+        if e.tx_type == TxType.outgoing and e.status == TxStatus.pending
+    )
+    net = incoming_total - outgoing_total - fees
+    return {
+        "incoming_total_sats": incoming_total,
+        "outgoing_total_sats": outgoing_total,
+        "fees_paid_sats": fees,
+        "net_sats": net,
+        "pending_incoming_sats": pending_in,
+        "pending_outgoing_sats": pending_out,
+        "available_sats": net - pending_out,
+    }
+
+
+def get_transactions(
+    tx_type: str | None = None,
+    status: str | None = None,
+    limit: int = 50,
+) -> list[LedgerEntry]:
+    """Return ledger entries, optionally filtered."""
+    result = _entries
+    if tx_type:
+        result = [e for e in result if e.tx_type.value == tx_type]
+    if status:
+        result = [e for e in result if e.status.value == status]
+    return list(reversed(result))[:limit]
+
+
+def clear() -> None:
+    """Reset the ledger (for testing)."""
+    _entries.clear()

src/loop/__init__.py

@@ -0,0 +1 @@
+"""Three-phase agent loop: Gather → Reason → Act."""

src/loop/phase1_gather.py

@@ -0,0 +1,37 @@
+"""Phase 1 — Gather: accept raw input, produce structured context.
+
+This is the sensory phase. It receives a raw ContextPayload and enriches
+it with whatever context Timmy needs before reasoning. In the stub form,
+it simply passes the payload through with a phase marker.
+"""
+
+from __future__ import annotations
+
+import logging
+
+from loop.schema import ContextPayload
+
+logger = logging.getLogger(__name__)
+
+
+def gather(payload: ContextPayload) -> ContextPayload:
+    """Accept raw input and return structured context for reasoning.
+
+    Stub: tags the payload with phase=gather and logs transit.
+    Timmy will flesh this out with context selection, memory lookup,
+    adapter polling, and attention-residual weighting.
+    """
+    logger.info(
+        "Phase 1 (Gather) received: source=%s content_len=%d tokens=%d",
+        payload.source,
+        len(payload.content),
+        payload.token_count,
+    )
+
+    result = payload.with_metadata(phase="gather", gathered=True)
+
+    logger.info(
+        "Phase 1 (Gather) produced: metadata_keys=%s",
+        sorted(result.metadata.keys()),
+    )
+    return result

src/loop/phase2_reason.py

@@ -0,0 +1,36 @@
+"""Phase 2 — Reason: accept gathered context, produce reasoning output.
+
+This is the deliberation phase. It receives enriched context from Phase 1
+and decides what to do. In the stub form, it passes the payload through
+with a phase marker.
+"""
+
+from __future__ import annotations
+
+import logging
+
+from loop.schema import ContextPayload
+
+logger = logging.getLogger(__name__)
+
+
+def reason(payload: ContextPayload) -> ContextPayload:
+    """Accept gathered context and return a reasoning result.
+
+    Stub: tags the payload with phase=reason and logs transit.
+    Timmy will flesh this out with LLM calls, confidence scoring,
+    plan generation, and judgment logic.
+    """
+    logger.info(
+        "Phase 2 (Reason) received: source=%s gathered=%s",
+        payload.source,
+        payload.metadata.get("gathered", False),
+    )
+
+    result = payload.with_metadata(phase="reason", reasoned=True)
+
+    logger.info(
+        "Phase 2 (Reason) produced: metadata_keys=%s",
+        sorted(result.metadata.keys()),
+    )
+    return result

src/loop/phase3_act.py

@@ -0,0 +1,36 @@
+"""Phase 3 — Act: accept reasoning output, execute and produce feedback.
+
+This is the command phase. It receives the reasoning result from Phase 2
+and takes action. In the stub form, it passes the payload through with a
+phase marker and produces feedback for the next cycle.
+"""
+
+from __future__ import annotations
+
+import logging
+
+from loop.schema import ContextPayload
+
+logger = logging.getLogger(__name__)
+
+
+def act(payload: ContextPayload) -> ContextPayload:
+    """Accept reasoning result and return action output + feedback.
+
+    Stub: tags the payload with phase=act and logs transit.
+    Timmy will flesh this out with tool execution, delegation,
+    response generation, and feedback construction.
+    """
+    logger.info(
+        "Phase 3 (Act) received: source=%s reasoned=%s",
+        payload.source,
+        payload.metadata.get("reasoned", False),
+    )
+
+    result = payload.with_metadata(phase="act", acted=True)
+
+    logger.info(
+        "Phase 3 (Act) produced: metadata_keys=%s",
+        sorted(result.metadata.keys()),
+    )
+    return result

src/loop/runner.py

@@ -0,0 +1,40 @@
+"""Loop runner — orchestrates the three phases in sequence.
+
+Runs Gather → Reason → Act as a single cycle, passing output from each
+phase as input to the next. The Act output feeds back as input to the
+next Gather call.
+"""
+
+from __future__ import annotations
+
+import logging
+
+from loop.phase1_gather import gather
+from loop.phase2_reason import reason
+from loop.phase3_act import act
+from loop.schema import ContextPayload
+
+logger = logging.getLogger(__name__)
+
+
+def run_cycle(payload: ContextPayload) -> ContextPayload:
+    """Execute one full Gather → Reason → Act cycle.
+
+    Returns the Act phase output, which can be fed back as input
+    to the next cycle.
+    """
+    logger.info("=== Loop cycle start: source=%s ===", payload.source)
+
+    gathered = gather(payload)
+    reasoned = reason(gathered)
+    acted = act(reasoned)
+
+    logger.info(
+        "=== Loop cycle complete: phases=%s ===",
+        [
+            gathered.metadata.get("phase"),
+            reasoned.metadata.get("phase"),
+            acted.metadata.get("phase"),
+        ],
+    )
+    return acted

src/loop/schema.py

@@ -0,0 +1,43 @@
+"""Data schema for the three-phase loop.
+
+Each phase passes a ContextPayload forward. The schema is intentionally
+minimal — Timmy decides what fields matter as the loop matures.
+"""
+
+from __future__ import annotations
+
+import logging
+from dataclasses import dataclass, field
+from datetime import UTC, datetime
+
+logger = logging.getLogger(__name__)
+
+
+@dataclass
+class ContextPayload:
+    """Immutable context packet passed between loop phases.
+
+    Attributes:
+        source: Where this payload originated (e.g. "user", "timer", "event").
+        content: The raw content string to process.
+        timestamp: When the payload was created.
+        token_count: Estimated token count for budget tracking. -1 = unknown.
+        metadata: Arbitrary key-value pairs for phase-specific data.
+    """
+
+    source: str
+    content: str
+    timestamp: datetime = field(default_factory=lambda: datetime.now(UTC))
+    token_count: int = -1
+    metadata: dict = field(default_factory=dict)
+
+    def with_metadata(self, **kwargs: object) -> ContextPayload:
+        """Return a new payload with additional metadata merged in."""
+        merged = {**self.metadata, **kwargs}
+        return ContextPayload(
+            source=self.source,
+            content=self.content,
+            timestamp=self.timestamp,
+            token_count=self.token_count,
+            metadata=merged,
+        )

src/timmy/__init__.py

@@ -1 +1 @@
-"""Timmy — Core AI agent (Ollama/AirLLM backends, CLI, prompts)."""
+"""Timmy — Core AI agent (Ollama/Grok/Claude backends, CLI, prompts)."""

src/timmy/adapters/__init__.py

@@ -0,0 +1 @@
+"""Adapters — normalize external data streams into sensory events."""

src/timmy/adapters/gitea_adapter.py

@@ -0,0 +1,136 @@
+"""Gitea webhook adapter — normalize webhook payloads to event bus events.
+
+Receives raw Gitea webhook payloads and emits typed events via the
+infrastructure event bus.  Bot-only activity is filtered unless it
+represents a PR merge (which is always noteworthy).
+"""
+
+import logging
+from typing import Any
+
+from infrastructure.events.bus import emit
+
+logger = logging.getLogger(__name__)
+
+# Gitea usernames considered "bot" accounts
+BOT_USERNAMES = frozenset({"hermes", "kimi", "manus"})
+
+# Owner username — activity from this user is always emitted
+OWNER_USERNAME = "rockachopa"
+
+# Mapping from Gitea webhook event type to our bus event type
+_EVENT_TYPE_MAP = {
+    "push": "gitea.push",
+    "issues": "gitea.issue.opened",
+    "issue_comment": "gitea.issue.comment",
+    "pull_request": "gitea.pull_request",
+}
+
+
+def _extract_actor(payload: dict[str, Any]) -> str:
+    """Extract the actor username from a webhook payload."""
+    # Gitea puts actor in sender.login for most events
+    sender = payload.get("sender", {})
+    return sender.get("login", "unknown")
+
+
+def _is_bot(username: str) -> bool:
+    return username.lower() in BOT_USERNAMES
+
+
+def _is_pr_merge(event_type: str, payload: dict[str, Any]) -> bool:
+    """Check if this is a pull_request merge event."""
+    if event_type != "pull_request":
+        return False
+    action = payload.get("action", "")
+    pr = payload.get("pull_request", {})
+    return action == "closed" and pr.get("merged", False)
+
+
+def _normalize_push(payload: dict[str, Any], actor: str) -> dict[str, Any]:
+    """Normalize a push event payload."""
+    commits = payload.get("commits", [])
+    return {
+        "actor": actor,
+        "ref": payload.get("ref", ""),
+        "repo": payload.get("repository", {}).get("full_name", ""),
+        "num_commits": len(commits),
+        "head_message": commits[0].get("message", "").split("\n", 1)[0].strip() if commits else "",
+    }
+
+
+def _normalize_issue_opened(payload: dict[str, Any], actor: str) -> dict[str, Any]:
+    """Normalize an issue-opened event payload."""
+    issue = payload.get("issue", {})
+    return {
+        "actor": actor,
+        "action": payload.get("action", "opened"),
+        "repo": payload.get("repository", {}).get("full_name", ""),
+        "issue_number": issue.get("number", 0),
+        "title": issue.get("title", ""),
+    }
+
+
+def _normalize_issue_comment(payload: dict[str, Any], actor: str) -> dict[str, Any]:
+    """Normalize an issue-comment event payload."""
+    issue = payload.get("issue", {})
+    comment = payload.get("comment", {})
+    return {
+        "actor": actor,
+        "action": payload.get("action", "created"),
+        "repo": payload.get("repository", {}).get("full_name", ""),
+        "issue_number": issue.get("number", 0),
+        "issue_title": issue.get("title", ""),
+        "comment_body": (comment.get("body", "")[:200]),
+    }
+
+
+def _normalize_pull_request(payload: dict[str, Any], actor: str) -> dict[str, Any]:
+    """Normalize a pull-request event payload."""
+    pr = payload.get("pull_request", {})
+    return {
+        "actor": actor,
+        "action": payload.get("action", ""),
+        "repo": payload.get("repository", {}).get("full_name", ""),
+        "pr_number": pr.get("number", 0),
+        "title": pr.get("title", ""),
+        "merged": pr.get("merged", False),
+    }
+
+
+_NORMALIZERS = {
+    "push": _normalize_push,
+    "issues": _normalize_issue_opened,
+    "issue_comment": _normalize_issue_comment,
+    "pull_request": _normalize_pull_request,
+}
+
+
+async def handle_webhook(event_type: str, payload: dict[str, Any]) -> bool:
+    """Normalize a Gitea webhook payload and emit it to the event bus.
+
+    Args:
+        event_type: The Gitea event type header (e.g. "push", "issues").
+        payload: The raw JSON payload from the webhook.
+
+    Returns:
+        True if an event was emitted, False if filtered or unsupported.
+    """
+    bus_event_type = _EVENT_TYPE_MAP.get(event_type)
+    if bus_event_type is None:
+        logger.debug("Unsupported Gitea event type: %s", event_type)
+        return False
+
+    actor = _extract_actor(payload)
+
+    # Filter bot-only activity — except PR merges
+    if _is_bot(actor) and not _is_pr_merge(event_type, payload):
+        logger.debug("Filtered bot activity from %s on %s", actor, event_type)
+        return False
+
+    normalizer = _NORMALIZERS[event_type]
+    data = normalizer(payload, actor)
+
+    await emit(bus_event_type, source="gitea", data=data)
+    logger.info("Emitted %s from %s", bus_event_type, actor)
+    return True

src/timmy/adapters/time_adapter.py

@@ -0,0 +1,82 @@
+"""Time adapter — circadian awareness for Timmy.
+
+Emits time-of-day events so Timmy knows the current period
+and tracks how long since the last user interaction.
+"""
+
+import logging
+from datetime import UTC, datetime
+
+from infrastructure.events.bus import emit
+
+logger = logging.getLogger(__name__)
+
+# Time-of-day periods: (event_name, start_hour, end_hour)
+_PERIODS = [
+    ("morning", 6, 9),
+    ("afternoon", 12, 14),
+    ("evening", 18, 20),
+    ("late_night", 23, 24),
+    ("late_night", 0, 3),
+]
+
+
+def classify_period(hour: int) -> str | None:
+    """Return the circadian period name for a given hour, or None."""
+    for name, start, end in _PERIODS:
+        if start <= hour < end:
+            return name
+    return None
+
+
+class TimeAdapter:
+    """Emits circadian and interaction-tracking events."""
+
+    def __init__(self) -> None:
+        self._last_interaction: datetime | None = None
+        self._last_period: str | None = None
+        self._last_date: str | None = None
+
+    def record_interaction(self, now: datetime | None = None) -> None:
+        """Record a user interaction timestamp."""
+        self._last_interaction = now or datetime.now(UTC)
+
+    def time_since_last_interaction(
+        self,
+        now: datetime | None = None,
+    ) -> float | None:
+        """Seconds since last user interaction, or None if no interaction."""
+        if self._last_interaction is None:
+            return None
+        current = now or datetime.now(UTC)
+        return (current - self._last_interaction).total_seconds()
+
+    async def tick(self, now: datetime | None = None) -> list[str]:
+        """Check current time and emit relevant events.
+
+        Returns list of event types emitted (useful for testing).
+        """
+        current = now or datetime.now(UTC)
+        emitted: list[str] = []
+
+        # --- new_day ---
+        date_str = current.strftime("%Y-%m-%d")
+        if self._last_date is not None and date_str != self._last_date:
+            event_type = "time.new_day"
+            await emit(event_type, source="time_adapter", data={"date": date_str})
+            emitted.append(event_type)
+        self._last_date = date_str
+
+        # --- circadian period ---
+        period = classify_period(current.hour)
+        if period is not None and period != self._last_period:
+            event_type = f"time.{period}"
+            await emit(
+                event_type,
+                source="time_adapter",
+                data={"hour": current.hour, "period": period},
+            )
+            emitted.append(event_type)
+            self._last_period = period
+
+        return emitted

src/timmy/agent.py

@@ -26,12 +26,12 @@ from timmy.prompts import get_system_prompt
 from timmy.tools import create_full_toolkit
 
 if TYPE_CHECKING:
-    from timmy.backends import ClaudeBackend, GrokBackend, TimmyAirLLMAgent
+    from timmy.backends import ClaudeBackend, GrokBackend
 
 logger = logging.getLogger(__name__)
 
 # Union type for callers that want to hint the return type.
-TimmyAgent = Union[Agent, "TimmyAirLLMAgent", "GrokBackend", "ClaudeBackend"]
+TimmyAgent = Union[Agent, "GrokBackend", "ClaudeBackend"]
 
 # Models known to be too small for reliable tool calling.
 # These hallucinate tool calls as text, invoke tools randomly,
@@ -63,7 +63,7 @@ def _pull_model(model_name: str) -> bool:
 
         logger.info("Pulling model: %s", model_name)
 
-        url = settings.ollama_url.replace("localhost", "127.0.0.1")
+        url = settings.normalized_ollama_url
         req = urllib.request.Request(
             f"{url}/api/pull",
             method="POST",
@@ -172,107 +172,34 @@ def _warmup_model(model_name: str) -> bool:
 
 
 def _resolve_backend(requested: str | None) -> str:
-    """Return the backend name to use, resolving 'auto' and explicit overrides.
+    """Return the backend name to use.
 
-    Priority (highest → lowest):
+    Priority (highest -> lowest):
       1. CLI flag passed directly to create_timmy()
       2. TIMMY_MODEL_BACKEND env var / .env setting
-      3. 'ollama' (safe default — no surprises)
-
-    'auto' triggers Apple Silicon detection: uses AirLLM if both
-    is_apple_silicon() and airllm_available() return True.
+      3. 'ollama' (safe default -- no surprises)
     """
     if requested is not None:
         return requested
 
-    configured = settings.timmy_model_backend  # "ollama" | "airllm" | "grok" | "claude" | "auto"
-    if configured != "auto":
-        return configured
-
-    # "auto" path — lazy import to keep startup fast and tests clean.
-    from timmy.backends import airllm_available, is_apple_silicon
-
-    if is_apple_silicon() and airllm_available():
-        return "airllm"
-    return "ollama"
+    return settings.timmy_model_backend  # "ollama" | "grok" | "claude"
 
 
-def create_timmy(
-    db_file: str = "timmy.db",
-    backend: str | None = None,
-    model_size: str | None = None,
-    *,
-    skip_mcp: bool = False,
-    session_id: str = "unknown",
-) -> TimmyAgent:
-    """Instantiate the agent — Ollama or AirLLM, same public interface.
+def _build_tools_list(use_tools: bool, skip_mcp: bool, model_name: str) -> list:
+    """Assemble the tools list based on model capability and MCP flags.
 
-    Args:
-        db_file:    SQLite file for Agno conversation memory (Ollama path only).
-        backend:    "ollama" | "airllm" | "auto" | None (reads config/env).
-        model_size: AirLLM size — "8b" | "70b" | "405b" | None (reads config).
-        skip_mcp:   If True, omit MCP tool servers (Gitea, filesystem).
-                    Use for background tasks (thinking, QA) where MCP's
-                    stdio cancel-scope lifecycle conflicts with asyncio
-                    task cancellation.
-
-    Returns an Agno Agent or backend-specific agent — all expose
-    print_response(message, stream).
+    Returns a list of Toolkit / MCPTools objects, or an empty list.
     """
-    resolved = _resolve_backend(backend)
-    size = model_size or settings.airllm_model_size
-
-    if resolved == "claude":
-        from timmy.backends import ClaudeBackend
-
-        return ClaudeBackend()
-
-    if resolved == "grok":
-        from timmy.backends import GrokBackend
-
-        return GrokBackend()
-
-    if resolved == "airllm":
-        from timmy.backends import TimmyAirLLMAgent
-
-        return TimmyAirLLMAgent(model_size=size)
-
-    # Default: Ollama via Agno.
-    # Resolve model with automatic pulling and fallback
-    model_name, is_fallback = _resolve_model_with_fallback(
-        requested_model=None,
-        require_vision=False,
-        auto_pull=True,
-    )
-
-    # If Ollama is completely unreachable, fail loudly.
-    # Sovereignty: never silently send data to a cloud API.
-    # Use --backend claude explicitly if you want cloud inference.
-    if not _check_model_available(model_name):
-        logger.error(
-            "Ollama unreachable and no local models available. "
-            "Start Ollama with 'ollama serve' or use --backend claude explicitly."
-        )
-
-    if is_fallback:
-        logger.info("Using fallback model %s (requested was unavailable)", model_name)
-
-    use_tools = _model_supports_tools(model_name)
-
-    # Conditionally include tools — small models get none
-    toolkit = create_full_toolkit() if use_tools else None
     if not use_tools:
         logger.info("Tools disabled for model %s (too small for reliable tool calling)", model_name)
+        return []
 
-    # Build the tools list — Agno accepts a list of Toolkit / MCPTools
-    tools_list: list = []
-    if toolkit:
-        tools_list.append(toolkit)
+    tools_list: list = [create_full_toolkit()]
 
     # Add MCP tool servers (lazy-connected on first arun()).
     # Skipped when skip_mcp=True — MCP's stdio transport uses anyio cancel
     # scopes that conflict with asyncio background task cancellation (#72).
-    if use_tools and not skip_mcp:
+    if not skip_mcp:
         try:
             from timmy.mcp_tools import create_filesystem_mcp_tools, create_gitea_mcp_tools
 
@@ -286,30 +213,46 @@ def create_timmy(
         except Exception as exc:
             logger.debug("MCP tools unavailable: %s", exc)
 
-    # Select prompt tier based on tool capability
+    return tools_list
+
+
+def _build_prompt(use_tools: bool, session_id: str) -> str:
+    """Build the full system prompt with optional memory context."""
     base_prompt = get_system_prompt(tools_enabled=use_tools, session_id=session_id)
 
-    # Try to load memory context
     try:
         from timmy.memory_system import memory_system
 
         memory_context = memory_system.get_system_context()
         if memory_context:
-            # Truncate if too long — smaller budget for small models
-            # since the expanded prompt (roster, guardrails) uses more tokens
+            # Smaller budget for small models — expanded prompt uses more tokens
             max_context = 2000 if not use_tools else 8000
             if len(memory_context) > max_context:
                 memory_context = memory_context[:max_context] + "\n... [truncated]"
-            full_prompt = f"{base_prompt}\n\n## Memory Context\n\n{memory_context}"
-        else:
-            full_prompt = base_prompt
+            return (
+                f"{base_prompt}\n\n"
+                f"## GROUNDED CONTEXT (verified sources — cite when using)\n\n"
+                f"{memory_context}"
+            )
     except Exception as exc:
         logger.warning("Failed to load memory context: %s", exc)
-        full_prompt = base_prompt
 
+    return base_prompt
+
+
+def _create_ollama_agent(
+    *,
+    db_file: str,
+    model_name: str,
+    tools_list: list,
+    full_prompt: str,
+    use_tools: bool,
+) -> Agent:
+    """Construct the Agno Agent with Ollama backend and warm up the model."""
     model_kwargs = {}
     if settings.ollama_num_ctx > 0:
         model_kwargs["options"] = {"num_ctx": settings.ollama_num_ctx}
+
     agent = Agent(
         name="Agent",
         model=Ollama(id=model_name, host=settings.ollama_url, timeout=300, **model_kwargs),
@@ -326,6 +269,67 @@ def create_timmy(
     return agent
 
 
+def create_timmy(
+    db_file: str = "timmy.db",
+    backend: str | None = None,
+    *,
+    skip_mcp: bool = False,
+    session_id: str = "unknown",
+) -> TimmyAgent:
+    """Instantiate the agent — Ollama, Grok, or Claude.
+
+    Args:
+        db_file:    SQLite file for Agno conversation memory (Ollama path only).
+        backend:    "ollama" | "grok" | "claude" | None (reads config/env).
+        skip_mcp:   If True, omit MCP tool servers (Gitea, filesystem).
+                    Use for background tasks (thinking, QA) where MCP's
+                    stdio cancel-scope lifecycle conflicts with asyncio
+                    task cancellation.
+
+    Returns an Agno Agent or backend-specific agent — all expose
+    print_response(message, stream).
+    """
+    resolved = _resolve_backend(backend)
+
+    if resolved == "claude":
+        from timmy.backends import ClaudeBackend
+
+        return ClaudeBackend()
+
+    if resolved == "grok":
+        from timmy.backends import GrokBackend
+
+        return GrokBackend()
+
+    # Default: Ollama via Agno.
+    model_name, is_fallback = _resolve_model_with_fallback(
+        requested_model=None,
+        require_vision=False,
+        auto_pull=True,
+    )
+
+    if not _check_model_available(model_name):
+        logger.error(
+            "Ollama unreachable and no local models available. "
+            "Start Ollama with 'ollama serve' or use --backend claude explicitly."
+        )
+
+    if is_fallback:
+        logger.info("Using fallback model %s (requested was unavailable)", model_name)
+
+    use_tools = _model_supports_tools(model_name)
+    tools_list = _build_tools_list(use_tools, skip_mcp, model_name)
+    full_prompt = _build_prompt(use_tools, session_id)
+
+    return _create_ollama_agent(
+        db_file=db_file,
+        model_name=model_name,
+        tools_list=tools_list,
+        full_prompt=full_prompt,
+        use_tools=use_tools,
+    )
+
+
 class TimmyWithMemory:
     """Agent wrapper with explicit three-tier memory management."""
 

src/timmy/agentic_loop.py

@@ -18,6 +18,7 @@ from __future__ import annotations
 import asyncio
 import logging
 import re
+import threading
 import time
 import uuid
 from collections.abc import Callable
@@ -59,6 +60,7 @@ class AgenticResult:
 # ---------------------------------------------------------------------------
 
 _loop_agent = None
+_loop_agent_lock = threading.Lock()
 
 
 def _get_loop_agent():
@@ -69,9 +71,11 @@ def _get_loop_agent():
     """
     global _loop_agent
     if _loop_agent is None:
-        from timmy.agent import create_timmy
+        with _loop_agent_lock:
+            if _loop_agent is None:
+                from timmy.agent import create_timmy
 
-        _loop_agent = create_timmy()
+                _loop_agent = create_timmy()
     return _loop_agent
 
 
@@ -91,6 +95,126 @@ def _parse_steps(plan_text: str) -> list[str]:
     return [line.strip() for line in plan_text.strip().splitlines() if line.strip()]
 
 
+# ---------------------------------------------------------------------------
+# Extracted helpers
+# ---------------------------------------------------------------------------
+
+
+def _extract_content(run_result) -> str:
+    """Extract text content from an agent run result."""
+    return run_result.content if hasattr(run_result, "content") else str(run_result)
+
+
+def _clean(text: str) -> str:
+    """Clean a model response using session's response cleaner."""
+    from timmy.session import _clean_response
+
+    return _clean_response(text)
+
+
+async def _plan_task(
+    agent, task: str, session_id: str, max_steps: int
+) -> tuple[list[str], bool] | str:
+    """Run the planning phase — returns (steps, was_truncated) or error string."""
+    plan_prompt = (
+        f"Break this task into numbered steps (max {max_steps}). "
+        f"Return ONLY a numbered list, nothing else.\n\n"
+        f"Task: {task}"
+    )
+    try:
+        plan_run = await asyncio.to_thread(
+            agent.run, plan_prompt, stream=False, session_id=f"{session_id}_plan"
+        )
+        plan_text = _extract_content(plan_run)
+    except Exception as exc:  # broad catch intentional: agent.run can raise any error
+        logger.error("Agentic loop: planning failed: %s", exc)
+        return f"Planning failed: {exc}"
+
+    steps = _parse_steps(plan_text)
+    if not steps:
+        return "Planning produced no steps."
+
+    planned_count = len(steps)
+    steps = steps[:max_steps]
+    return steps, planned_count > len(steps)
+
+
+async def _execute_step(
+    agent,
+    task: str,
+    step_desc: str,
+    step_num: int,
+    total_steps: int,
+    recent_results: list[str],
+    session_id: str,
+) -> AgenticStep:
+    """Execute a single step, returning an AgenticStep."""
+    step_start = time.monotonic()
+    context = (
+        f"Task: {task}\n"
+        f"Step {step_num}/{total_steps}: {step_desc}\n"
+        f"Recent progress: {recent_results[-2:] if recent_results else []}\n\n"
+        f"Execute this step and report what you did."
+    )
+    step_run = await asyncio.to_thread(
+        agent.run, context, stream=False, session_id=f"{session_id}_step{step_num}"
+    )
+    step_result = _clean(_extract_content(step_run))
+    return AgenticStep(
+        step_num=step_num,
+        description=step_desc,
+        result=step_result,
+        status="completed",
+        duration_ms=int((time.monotonic() - step_start) * 1000),
+    )
+
+
+async def _adapt_step(
+    agent,
+    step_desc: str,
+    step_num: int,
+    error: Exception,
+    step_start: float,
+    session_id: str,
+) -> AgenticStep:
+    """Attempt adaptation after a step failure."""
+    adapt_prompt = (
+        f"Step {step_num} failed with error: {error}\n"
+        f"Original step was: {step_desc}\n"
+        f"Adapt the plan and try an alternative approach for this step."
+    )
+    adapt_run = await asyncio.to_thread(
+        agent.run, adapt_prompt, stream=False, session_id=f"{session_id}_adapt{step_num}"
+    )
+    adapt_result = _clean(_extract_content(adapt_run))
+    return AgenticStep(
+        step_num=step_num,
+        description=f"[Adapted] {step_desc}",
+        result=adapt_result,
+        status="adapted",
+        duration_ms=int((time.monotonic() - step_start) * 1000),
+    )
+
+
+def _summarize(result: AgenticResult, total_steps: int, was_truncated: bool) -> None:
+    """Fill in summary and final status on the result object (mutates in place)."""
+    completed = sum(1 for s in result.steps if s.status == "completed")
+    adapted = sum(1 for s in result.steps if s.status == "adapted")
+    failed = sum(1 for s in result.steps if s.status == "failed")
+
+    parts = [f"Completed {completed}/{total_steps} steps"]
+    if adapted:
+        parts.append(f"{adapted} adapted")
+    if failed:
+        parts.append(f"{failed} failed")
+    result.summary = f"{result.task}: {', '.join(parts)}."
+
+    if was_truncated or len(result.steps) < total_steps or failed:
+        result.status = "partial"
+    else:
+        result.status = "completed"
+
+
 # ---------------------------------------------------------------------------
 # Core loop
 # ---------------------------------------------------------------------------
@@ -121,88 +245,41 @@ async def run_agentic_loop(
 
     task_id = str(uuid.uuid4())[:8]
     start_time = time.monotonic()
-
     agent = _get_loop_agent()
     result = AgenticResult(task_id=task_id, task=task, summary="")
 
-    # ── Phase 1: Planning ──────────────────────────────────────────────────
-    plan_prompt = (
-        f"Break this task into numbered steps (max {max_steps}). "
-        f"Return ONLY a numbered list, nothing else.\n\n"
-        f"Task: {task}"
-    )
-    try:
-        plan_run = await asyncio.to_thread(
-            agent.run, plan_prompt, stream=False, session_id=f"{session_id}_plan"
-        )
-        plan_text = plan_run.content if hasattr(plan_run, "content") else str(plan_run)
-    except Exception as exc:  # broad catch intentional: agent.run can raise any error
-        logger.error("Agentic loop: planning failed: %s", exc)
+    # Phase 1: Planning
+    plan = await _plan_task(agent, task, session_id, max_steps)
+    if isinstance(plan, str):
         result.status = "failed"
-        result.summary = f"Planning failed: {exc}"
+        result.summary = plan
         result.total_duration_ms = int((time.monotonic() - start_time) * 1000)
         return result
 
-    steps = _parse_steps(plan_text)
-    if not steps:
-        result.status = "failed"
-        result.summary = "Planning produced no steps."
-        result.total_duration_ms = int((time.monotonic() - start_time) * 1000)
-        return result
-
-    # Enforce max_steps — track if we truncated
-    planned_steps = len(steps)
-    steps = steps[:max_steps]
+    steps, was_truncated = plan
     total_steps = len(steps)
-    was_truncated = planned_steps > total_steps
 
-    # Broadcast plan
     await _broadcast_progress(
         "agentic.plan_ready",
-        {
-            "task_id": task_id,
-            "task": task,
-            "steps": steps,
-            "total": total_steps,
-        },
+        {"task_id": task_id, "task": task, "steps": steps, "total": total_steps},
     )
 
-    # ── Phase 2: Execution ─────────────────────────────────────────────────
+    # Phase 2: Execution
     completed_results: list[str] = []
-
     for i, step_desc in enumerate(steps, 1):
         step_start = time.monotonic()
-
-        recent = completed_results[-2:] if completed_results else []
-        context = (
-            f"Task: {task}\n"
-            f"Step {i}/{total_steps}: {step_desc}\n"
-            f"Recent progress: {recent}\n\n"
-            f"Execute this step and report what you did."
-        )
-
         try:
-            step_run = await asyncio.to_thread(
-                agent.run, context, stream=False, session_id=f"{session_id}_step{i}"
-            )
-            step_result = step_run.content if hasattr(step_run, "content") else str(step_run)
-
-            # Clean the response
-            from timmy.session import _clean_response
-
-            step_result = _clean_response(step_result)
-
-            step = AgenticStep(
-                step_num=i,
-                description=step_desc,
-                result=step_result,
-                status="completed",
-                duration_ms=int((time.monotonic() - step_start) * 1000),
+            step = await _execute_step(
+                agent,
+                task,
+                step_desc,
+                i,
+                total_steps,
+                completed_results,
+                session_id,
             )
             result.steps.append(step)
-            completed_results.append(f"Step {i}: {step_result[:200]}")
-
-            # Broadcast progress
+            completed_results.append(f"Step {i}: {step.result[:200]}")
             await _broadcast_progress(
                 "agentic.step_complete",
                 {
@@ -210,46 +287,18 @@ async def run_agentic_loop(
                     "step": i,
                     "total": total_steps,
                     "description": step_desc,
-                    "result": step_result[:200],
+                    "result": step.result[:200],
                 },
             )
-
             if on_progress:
                 await on_progress(step_desc, i, total_steps)
 
         except Exception as exc:  # broad catch intentional: agent.run can raise any error
             logger.warning("Agentic loop step %d failed: %s", i, exc)
-
-            # ── Adaptation: ask model to adapt ─────────────────────────────
-            adapt_prompt = (
-                f"Step {i} failed with error: {exc}\n"
-                f"Original step was: {step_desc}\n"
-                f"Adapt the plan and try an alternative approach for this step."
-            )
             try:
-                adapt_run = await asyncio.to_thread(
-                    agent.run,
-                    adapt_prompt,
-                    stream=False,
-                    session_id=f"{session_id}_adapt{i}",
-                )
-                adapt_result = (
-                    adapt_run.content if hasattr(adapt_run, "content") else str(adapt_run)
-                )
-                from timmy.session import _clean_response
-
-                adapt_result = _clean_response(adapt_result)
-
-                step = AgenticStep(
-                    step_num=i,
-                    description=f"[Adapted] {step_desc}",
-                    result=adapt_result,
-                    status="adapted",
-                    duration_ms=int((time.monotonic() - step_start) * 1000),
-                )
+                step = await _adapt_step(agent, step_desc, i, exc, step_start, session_id)
                 result.steps.append(step)
-                completed_results.append(f"Step {i} (adapted): {adapt_result[:200]}")
-
+                completed_results.append(f"Step {i} (adapted): {step.result[:200]}")
                 await _broadcast_progress(
                     "agentic.step_adapted",
                     {
@@ -258,46 +307,26 @@ async def run_agentic_loop(
                         "total": total_steps,
                         "description": step_desc,
                         "error": str(exc),
-                        "adaptation": adapt_result[:200],
+                        "adaptation": step.result[:200],
                     },
                 )
-
                 if on_progress:
                     await on_progress(f"[Adapted] {step_desc}", i, total_steps)
-
-            except Exception as adapt_exc:  # broad catch intentional: agent.run can raise any error
+            except Exception as adapt_exc:  # broad catch intentional
                 logger.error("Agentic loop adaptation also failed: %s", adapt_exc)
-                step = AgenticStep(
-                    step_num=i,
-                    description=step_desc,
-                    result=f"Failed: {exc}; Adaptation also failed: {adapt_exc}",
-                    status="failed",
-                    duration_ms=int((time.monotonic() - step_start) * 1000),
+                result.steps.append(
+                    AgenticStep(
+                        step_num=i,
+                        description=step_desc,
+                        result=f"Failed: {exc}; Adaptation also failed: {adapt_exc}",
+                        status="failed",
+                        duration_ms=int((time.monotonic() - step_start) * 1000),
+                    )
                 )
-                result.steps.append(step)
                 completed_results.append(f"Step {i}: FAILED")
 
-    # ── Phase 3: Summary ───────────────────────────────────────────────────
-    completed_count = sum(1 for s in result.steps if s.status == "completed")
-    adapted_count = sum(1 for s in result.steps if s.status == "adapted")
-    failed_count = sum(1 for s in result.steps if s.status == "failed")
-    parts = [f"Completed {completed_count}/{total_steps} steps"]
-    if adapted_count:
-        parts.append(f"{adapted_count} adapted")
-    if failed_count:
-        parts.append(f"{failed_count} failed")
-    result.summary = f"{task}: {', '.join(parts)}."
-
-    # Determine final status
-    if was_truncated:
-        result.status = "partial"
-    elif len(result.steps) < total_steps:
-        result.status = "partial"
-    elif any(s.status == "failed" for s in result.steps):
-        result.status = "partial"
-    else:
-        result.status = "completed"
-
+    # Phase 3: Summary
+    _summarize(result, total_steps, was_truncated)
     result.total_duration_ms = int((time.monotonic() - start_time) * 1000)
 
     await _broadcast_progress(

src/timmy/agents/base.py

@@ -119,75 +119,84 @@ class BaseAgent(ABC):
         """
         pass
 
-    async def run(self, message: str) -> str:
-        """Run the agent with a message.
+    # Transient errors that indicate Ollama contention or temporary
+    # unavailability — these deserve a retry with backoff.
+    _TRANSIENT = (
+        httpx.ConnectError,
+        httpx.ReadError,
+        httpx.ReadTimeout,
+        httpx.ConnectTimeout,
+        ConnectionError,
+        TimeoutError,
+    )
 
-        Retries on transient failures (connection errors, timeouts) with
-        exponential backoff.  GPU contention from concurrent Ollama
-        requests causes ReadError / ReadTimeout — these are transient
-        and should be retried, not raised immediately (#70).
+    async def run(self, message: str, *, max_retries: int = 3) -> str:
+        """Run the agent with a message, retrying on transient failures.
 
-        Returns:
-            Agent response
+        GPU contention from concurrent Ollama requests causes ReadError /
+        ReadTimeout — these are transient and retried with exponential
+        backoff (#70).
         """
-        max_retries = 3
-        last_exception = None
-        # Transient errors that indicate Ollama contention or temporary
-        # unavailability — these deserve a retry with backoff.
-        _transient = (
-            httpx.ConnectError,
-            httpx.ReadError,
-            httpx.ReadTimeout,
-            httpx.ConnectTimeout,
-            ConnectionError,
-            TimeoutError,
-        )
+        response = await self._run_with_retries(message, max_retries)
+        await self._emit_response_event(message, response)
+        return response
 
+    async def _run_with_retries(self, message: str, max_retries: int) -> str:
+        """Execute agent.run() with retry logic for transient errors."""
         for attempt in range(1, max_retries + 1):
             try:
                 result = self.agent.run(message, stream=False)
-                response = result.content if hasattr(result, "content") else str(result)
-                break  # Success, exit the retry loop
-            except _transient as exc:
-                last_exception = exc
-                if attempt < max_retries:
-                    # Contention backoff — longer waits because the GPU
-                    # needs time to finish the other request.
-                    wait = min(2**attempt, 16)
-                    logger.warning(
-                        "Ollama contention on attempt %d/%d: %s. Waiting %ds before retry...",
-                        attempt,
-                        max_retries,
-                        type(exc).__name__,
-                        wait,
-                    )
-                    await asyncio.sleep(wait)
-                else:
-                    logger.error(
-                        "Ollama unreachable after %d attempts: %s",
-                        max_retries,
-                        exc,
-                    )
-                    raise last_exception from exc
+                return result.content if hasattr(result, "content") else str(result)
+            except self._TRANSIENT as exc:
+                self._handle_retry_or_raise(
+                    exc,
+                    attempt,
+                    max_retries,
+                    transient=True,
+                )
+                await asyncio.sleep(min(2**attempt, 16))
             except Exception as exc:
-                last_exception = exc
-                if attempt < max_retries:
-                    logger.warning(
-                        "Agent run failed on attempt %d/%d: %s. Retrying...",
-                        attempt,
-                        max_retries,
-                        exc,
-                    )
-                    await asyncio.sleep(min(2 ** (attempt - 1), 8))
-                else:
-                    logger.error(
-                        "Agent run failed after %d attempts: %s",
-                        max_retries,
-                        exc,
-                    )
-                    raise last_exception from exc
+                self._handle_retry_or_raise(
+                    exc,
+                    attempt,
+                    max_retries,
+                    transient=False,
+                )
+                await asyncio.sleep(min(2 ** (attempt - 1), 8))
+        # Unreachable — _handle_retry_or_raise raises on last attempt.
+        raise RuntimeError("retry loop exited unexpectedly")  # pragma: no cover
 
-        # Emit completion event
+    @staticmethod
+    def _handle_retry_or_raise(
+        exc: Exception,
+        attempt: int,
+        max_retries: int,
+        *,
+        transient: bool,
+    ) -> None:
+        """Log a retry warning or raise after exhausting attempts."""
+        if attempt < max_retries:
+            if transient:
+                logger.warning(
+                    "Ollama contention on attempt %d/%d: %s. Waiting before retry...",
+                    attempt,
+                    max_retries,
+                    type(exc).__name__,
+                )
+            else:
+                logger.warning(
+                    "Agent run failed on attempt %d/%d: %s. Retrying...",
+                    attempt,
+                    max_retries,
+                    exc,
+                )
+        else:
+            label = "Ollama unreachable" if transient else "Agent run failed"
+            logger.error("%s after %d attempts: %s", label, max_retries, exc)
+            raise exc
+
+    async def _emit_response_event(self, message: str, response: str) -> None:
+        """Publish a completion event to the event bus if connected."""
         if self.event_bus:
             await self.event_bus.publish(
                 Event(
@@ -197,8 +206,6 @@ class BaseAgent(ABC):
                 )
             )
 
-        return response
-
     def get_capabilities(self) -> list[str]:
         """Get list of capabilities this agent provides."""
         return self.tools

src/timmy/backends.py

@@ -1,11 +1,10 @@
-"""LLM backends — AirLLM (local big models), Grok (xAI), and Claude (Anthropic).
+"""LLM backends — Grok (xAI) and Claude (Anthropic).
 
 Provides drop-in replacements for the Agno Agent that expose the same
 run(message, stream) → RunResult interface used by the dashboard and the
 print_response(message, stream) interface used by the CLI.
 
 Backends:
-  - TimmyAirLLMAgent: Local 8B/70B/405B via AirLLM (Apple Silicon or PyTorch)
   - GrokBackend: xAI Grok API via OpenAI-compatible SDK (opt-in premium)
   - ClaudeBackend: Anthropic Claude API — lightweight cloud fallback
 
@@ -16,21 +15,11 @@ import logging
 import platform
 import time
 from dataclasses import dataclass
-from typing import Literal
 
 from timmy.prompts import get_system_prompt
 
 logger = logging.getLogger(__name__)
 
-# HuggingFace model IDs for each supported size.
-_AIRLLM_MODELS: dict[str, str] = {
-    "8b": "meta-llama/Meta-Llama-3.1-8B-Instruct",
-    "70b": "meta-llama/Meta-Llama-3.1-70B-Instruct",
-    "405b": "meta-llama/Meta-Llama-3.1-405B-Instruct",
-}
-
-ModelSize = Literal["8b", "70b", "405b"]
-
 
 @dataclass
 class RunResult:
@@ -45,108 +34,6 @@ def is_apple_silicon() -> bool:
     return platform.system() == "Darwin" and platform.machine() == "arm64"
 
 
-def airllm_available() -> bool:
-    """Return True when the airllm package is importable."""
-    try:
-        import airllm  # noqa: F401
-
-        return True
-    except ImportError:
-        return False
-
-
-class TimmyAirLLMAgent:
-    """Thin AirLLM wrapper compatible with both dashboard and CLI call sites.
-
-    Exposes:
-      run(message, stream)           → RunResult(content=...)  [dashboard]
-      print_response(message, stream) → None                   [CLI]
-
-    Maintains a rolling 10-turn in-memory history so Timmy remembers the
-    conversation within a session — no SQLite needed at this layer.
-    """
-
-    def __init__(self, model_size: str = "70b") -> None:
-        model_id = _AIRLLM_MODELS.get(model_size)
-        if model_id is None:
-            raise ValueError(
-                f"Unknown model size {model_size!r}. Choose from: {list(_AIRLLM_MODELS)}"
-            )
-
-        if is_apple_silicon():
-            from airllm import AirLLMMLX  # type: ignore[import]
-
-            self._model = AirLLMMLX(model_id)
-        else:
-            from airllm import AutoModel  # type: ignore[import]
-
-            self._model = AutoModel.from_pretrained(model_id)
-
-        self._history: list[str] = []
-        self._model_size = model_size
-
-    # ── public interface (mirrors Agno Agent) ────────────────────────────────
-
-    def run(self, message: str, *, stream: bool = False) -> RunResult:
-        """Run inference and return a structured result (matches Agno Agent.run()).
-
-        `stream` is accepted for API compatibility; AirLLM always generates
-        the full output in one pass.
-        """
-        prompt = self._build_prompt(message)
-
-        input_tokens = self._model.tokenizer(
-            [prompt],
-            return_tensors="pt",
-            padding=True,
-            truncation=True,
-            max_length=2048,
-        )
-        output = self._model.generate(
-            **input_tokens,
-            max_new_tokens=512,
-            use_cache=True,
-            do_sample=True,
-            temperature=0.7,
-        )
-
-        # Decode only the newly generated tokens, not the prompt.
-        input_len = input_tokens["input_ids"].shape[1]
-        response = self._model.tokenizer.decode(
-            output[0][input_len:], skip_special_tokens=True
-        ).strip()
-
-        self._history.append(f"User: {message}")
-        self._history.append(f"Timmy: {response}")
-
-        return RunResult(content=response)
-
-    def print_response(self, message: str, *, stream: bool = True) -> None:
-        """Run inference and render the response to stdout (CLI interface)."""
-        result = self.run(message, stream=stream)
-        self._render(result.content)
-
-    # ── private helpers ──────────────────────────────────────────────────────
-
-    def _build_prompt(self, message: str) -> str:
-        context = get_system_prompt(tools_enabled=False, session_id="airllm") + "\n\n"
-        # Include the last 10 turns (5 exchanges) for continuity.
-        if self._history:
-            context += "\n".join(self._history[-10:]) + "\n\n"
-        return context + f"User: {message}\nTimmy:"
-
-    @staticmethod
-    def _render(text: str) -> None:
-        """Print response with rich markdown when available, plain text otherwise."""
-        try:
-            from rich.console import Console
-            from rich.markdown import Markdown
-
-            Console().print(Markdown(text))
-        except ImportError:
-            print(text)
-
-
 # ── Grok (xAI) Backend ─────────────────────────────────────────────────────
 # Premium cloud augmentation — opt-in only, never the default path.
 
@@ -187,7 +74,7 @@ class GrokBackend:
     Uses the OpenAI-compatible SDK to connect to xAI's API.
     Only activated when GROK_ENABLED=true and XAI_API_KEY is set.
 
-    Exposes the same interface as TimmyAirLLMAgent and Agno Agent:
+    Exposes the same interface as Agno Agent:
       run(message, stream)           → RunResult  [dashboard]
       print_response(message, stream) → None       [CLI]
       health_check()                 → dict        [monitoring]
@@ -215,9 +102,11 @@ class GrokBackend:
         import httpx
         from openai import OpenAI
 
+        from config import settings
+
         return OpenAI(
             api_key=self._api_key,
-            base_url="https://api.x.ai/v1",
+            base_url=settings.xai_base_url,
             timeout=httpx.Timeout(300.0),
         )
 
@@ -226,9 +115,11 @@ class GrokBackend:
         import httpx
         from openai import AsyncOpenAI
 
+        from config import settings
+
         return AsyncOpenAI(
             api_key=self._api_key,
-            base_url="https://api.x.ai/v1",
+            base_url=settings.xai_base_url,
             timeout=httpx.Timeout(300.0),
         )
 
@@ -373,6 +264,7 @@ class GrokBackend:
                 },
             }
         except Exception as exc:
+            logger.exception("Grok health check failed")
             return {
                 "ok": False,
                 "error": str(exc),
@@ -437,8 +329,7 @@ CLAUDE_MODELS: dict[str, str] = {
 class ClaudeBackend:
     """Anthropic Claude backend — cloud fallback when local models are offline.
 
-    Uses the official Anthropic SDK.  Same interface as GrokBackend and
-    TimmyAirLLMAgent:
+    Uses the official Anthropic SDK.  Same interface as GrokBackend:
       run(message, stream)           → RunResult  [dashboard]
       print_response(message, stream) → None       [CLI]
       health_check()                 → dict        [monitoring]
@@ -540,6 +431,7 @@ class ClaudeBackend:
             )
             return {"ok": True, "error": None, "backend": "claude", "model": self._model}
         except Exception as exc:
+            logger.exception("Claude health check failed")
             return {"ok": False, "error": str(exc), "backend": "claude", "model": self._model}
 
     # ── Private helpers ───────────────────────────────────────────────────

src/timmy/cli.py

@@ -22,13 +22,13 @@ _BACKEND_OPTION = typer.Option(
     None,
     "--backend",
     "-b",
-    help="Inference backend: 'ollama' (default) | 'airllm' | 'auto'",
+    help="Inference backend: 'ollama' (default) | 'grok' | 'claude'",
 )
 _MODEL_SIZE_OPTION = typer.Option(
     None,
     "--model-size",
     "-s",
-    help="AirLLM model size when --backend airllm: '8b' | '70b' | '405b'",
+    help="Model size (reserved for future use).",
 )
 
 
@@ -37,6 +37,68 @@ def _is_interactive() -> bool:
     return hasattr(sys.stdin, "isatty") and sys.stdin.isatty()
 
 
+def _read_message_input(message: list[str]) -> str:
+    """Join CLI args into a message, reading from stdin when requested.
+
+    Returns the final message string.  Raises ``typer.Exit(1)`` when
+    stdin is explicitly requested (``-``) but empty.
+    """
+    message_str = " ".join(message)
+
+    if message_str == "-" or not _is_interactive():
+        try:
+            stdin_content = sys.stdin.read().strip()
+        except (KeyboardInterrupt, EOFError):
+            stdin_content = ""
+        if stdin_content:
+            message_str = stdin_content
+        elif message_str == "-":
+            typer.echo("No input provided via stdin.", err=True)
+            raise typer.Exit(1)
+
+    return message_str
+
+
+def _resolve_session_id(session_id: str | None, new_session: bool) -> str:
+    """Return the effective session ID for a chat invocation."""
+    import uuid
+
+    if session_id is not None:
+        return session_id
+    if new_session:
+        return str(uuid.uuid4())
+    return _CLI_SESSION_ID
+
+
+def _prompt_interactive(req, tool_name: str, tool_args: dict) -> None:
+    """Display tool details and prompt the human for approval."""
+    description = format_action_description(tool_name, tool_args)
+    impact = get_impact_level(tool_name)
+
+    typer.echo()
+    typer.echo(typer.style("Tool confirmation required", bold=True))
+    typer.echo(f"  Impact: {impact.upper()}")
+    typer.echo(f"  {description}")
+    typer.echo()
+
+    if typer.confirm("Allow this action?", default=False):
+        req.confirm()
+        logger.info("CLI: approved %s", tool_name)
+    else:
+        req.reject(note="User rejected from CLI")
+        logger.info("CLI: rejected %s", tool_name)
+
+
+def _decide_autonomous(req, tool_name: str, tool_args: dict) -> None:
+    """Auto-approve allowlisted tools; reject everything else."""
+    if is_allowlisted(tool_name, tool_args):
+        req.confirm()
+        logger.info("AUTO-APPROVED (allowlist): %s", tool_name)
+    else:
+        req.reject(note="Auto-rejected: not in allowlist")
+        logger.info("AUTO-REJECTED (not allowlisted): %s %s", tool_name, str(tool_args)[:100])
+
+
 def _handle_tool_confirmation(agent, run_output, session_id: str, *, autonomous: bool = False):
     """Prompt user to approve/reject dangerous tool calls.
 
@@ -51,6 +113,7 @@ def _handle_tool_confirmation(agent, run_output, session_id: str, *, autonomous:
     Returns the final RunOutput after all confirmations are resolved.
     """
     interactive = _is_interactive() and not autonomous
+    decide = _prompt_interactive if interactive else _decide_autonomous
 
     max_rounds = 10  # safety limit
     for _ in range(max_rounds):
@@ -66,39 +129,10 @@ def _handle_tool_confirmation(agent, run_output, session_id: str, *, autonomous:
         for req in reqs:
             if not getattr(req, "needs_confirmation", False):
                 continue
-
             te = req.tool_execution
             tool_name = getattr(te, "tool_name", "unknown")
             tool_args = getattr(te, "tool_args", {}) or {}
-
-            if interactive:
-                # Human present — prompt for approval
-                description = format_action_description(tool_name, tool_args)
-                impact = get_impact_level(tool_name)
-
-                typer.echo()
-                typer.echo(typer.style("Tool confirmation required", bold=True))
-                typer.echo(f"  Impact: {impact.upper()}")
-                typer.echo(f"  {description}")
-                typer.echo()
-
-                approved = typer.confirm("Allow this action?", default=False)
-                if approved:
-                    req.confirm()
-                    logger.info("CLI: approved %s", tool_name)
-                else:
-                    req.reject(note="User rejected from CLI")
-                    logger.info("CLI: rejected %s", tool_name)
-            else:
-                # Autonomous mode — check allowlist
-                if is_allowlisted(tool_name, tool_args):
-                    req.confirm()
-                    logger.info("AUTO-APPROVED (allowlist): %s", tool_name)
-                else:
-                    req.reject(note="Auto-rejected: not in allowlist")
-                    logger.info(
-                        "AUTO-REJECTED (not allowlisted): %s %s", tool_name, str(tool_args)[:100]
-                    )
+            decide(req, tool_name, tool_args)
 
         # Resume the run so the agent sees the confirmation result
         try:
@@ -138,10 +172,39 @@ def think(
     model_size: str | None = _MODEL_SIZE_OPTION,
 ):
     """Ask Timmy to think carefully about a topic."""
-    timmy = create_timmy(backend=backend, model_size=model_size, session_id=_CLI_SESSION_ID)
+    timmy = create_timmy(backend=backend, session_id=_CLI_SESSION_ID)
     timmy.print_response(f"Think carefully about: {topic}", stream=True, session_id=_CLI_SESSION_ID)
 
 
+def _read_message_input(message: list[str]) -> str:
+    """Join CLI arguments and read from stdin when appropriate."""
+    message_str = " ".join(message)
+
+    if message_str == "-" or not _is_interactive():
+        try:
+            stdin_content = sys.stdin.read().strip()
+        except (KeyboardInterrupt, EOFError):
+            stdin_content = ""
+        if stdin_content:
+            message_str = stdin_content
+        elif message_str == "-":
+            typer.echo("No input provided via stdin.", err=True)
+            raise typer.Exit(1)
+
+    return message_str
+
+
+def _resolve_session_id(session_id: str | None, new_session: bool) -> str:
+    """Return the effective session ID based on CLI flags."""
+    import uuid
+
+    if session_id is not None:
+        return session_id
+    if new_session:
+        return str(uuid.uuid4())
+    return _CLI_SESSION_ID
+
+
 @app.command()
 def chat(
     message: list[str] = typer.Argument(
@@ -178,38 +241,13 @@ def chat(
 
     Read from stdin by passing "-" as the message or piping input.
     """
-    import uuid
+    message_str = _read_message_input(message)
+    session_id = _resolve_session_id(session_id, new_session)
+    timmy = create_timmy(backend=backend, session_id=session_id)
 
-    # Join multiple arguments into a single message string
-    message_str = " ".join(message)
-
-    # Handle stdin input if "-" is passed or stdin is not a tty
-    if message_str == "-" or not _is_interactive():
-        try:
-            stdin_content = sys.stdin.read().strip()
-        except (KeyboardInterrupt, EOFError):
-            stdin_content = ""
-        if stdin_content:
-            message_str = stdin_content
-        elif message_str == "-":
-            typer.echo("No input provided via stdin.", err=True)
-            raise typer.Exit(1)
-
-    if session_id is not None:
-        pass  # use the provided value
-    elif new_session:
-        session_id = str(uuid.uuid4())
-    else:
-        session_id = _CLI_SESSION_ID
-    timmy = create_timmy(backend=backend, model_size=model_size, session_id=session_id)
-
-    # Use agent.run() so we can intercept paused runs for tool confirmation.
     run_output = timmy.run(message_str, stream=False, session_id=session_id)
-
-    # Handle paused runs — dangerous tools need user approval
     run_output = _handle_tool_confirmation(timmy, run_output, session_id, autonomous=autonomous)
 
-    # Print the final response
     content = run_output.content if hasattr(run_output, "content") else str(run_output)
     if content:
         from timmy.session import _clean_response
@@ -278,7 +316,7 @@ def status(
     model_size: str | None = _MODEL_SIZE_OPTION,
 ):
     """Print Timmy's operational status."""
-    timmy = create_timmy(backend=backend, model_size=model_size, session_id=_CLI_SESSION_ID)
+    timmy = create_timmy(backend=backend, session_id=_CLI_SESSION_ID)
     timmy.print_response(STATUS_PROMPT, stream=False, session_id=_CLI_SESSION_ID)
 
 
@@ -416,5 +454,78 @@ def route(
         typer.echo("→ orchestrator (no pattern match)")
 
 
+@app.command()
+def focus(
+    topic: str | None = typer.Argument(
+        None, help='Topic to focus on (e.g. "three-phase loop"). Omit to show current focus.'
+    ),
+    clear: bool = typer.Option(False, "--clear", "-c", help="Clear focus and return to broad mode"),
+):
+    """Set deep-focus mode on a single problem.
+
+    When focused, Timmy prioritizes the active topic in all responses
+    and deprioritizes unrelated context. Focus persists across sessions.
+
+    Examples:
+        timmy focus "three-phase loop"   # activate deep focus
+        timmy focus                       # show current focus
+        timmy focus --clear               # return to broad mode
+    """
+    from timmy.focus import focus_manager
+
+    if clear:
+        focus_manager.clear()
+        typer.echo("Focus cleared — back to broad mode.")
+        return
+
+    if topic:
+        focus_manager.set_topic(topic)
+        typer.echo(f'Deep focus activated: "{topic}"')
+    else:
+        # Show current focus status
+        if focus_manager.is_focused():
+            typer.echo(f'Deep focus: "{focus_manager.get_topic()}"')
+        else:
+            typer.echo("No active focus (broad mode).")
+
+
+@app.command(name="healthcheck")
+def healthcheck(
+    json_output: bool = typer.Option(False, "--json", "-j", help="Output as JSON"),
+    verbose: bool = typer.Option(
+        False, "--verbose", "-v", help="Show verbose output including issue details"
+    ),
+    quiet: bool = typer.Option(False, "--quiet", "-q", help="Only show status line (no details)"),
+):
+    """Quick health snapshot before coding.
+
+    Shows CI status, critical issues (P0/P1), test flakiness, and token economy.
+    Fast execution (< 5 seconds) for pre-work checks.
+
+    Refs: #710
+    """
+    import subprocess
+    import sys
+    from pathlib import Path
+
+    script_path = (
+        Path(__file__).resolve().parent.parent.parent
+        / "timmy_automations"
+        / "daily_run"
+        / "health_snapshot.py"
+    )
+
+    cmd = [sys.executable, str(script_path)]
+    if json_output:
+        cmd.append("--json")
+    if verbose:
+        cmd.append("--verbose")
+    if quiet:
+        cmd.append("--quiet")
+
+    result = subprocess.run(cmd)
+    raise typer.Exit(result.returncode)
+
+
 def main():
     app()

src/timmy/cognitive_state.py

@@ -0,0 +1,250 @@
+"""Observable cognitive state for Timmy.
+
+Tracks Timmy's internal cognitive signals — focus, engagement, mood,
+and active commitments — so external systems (Matrix avatar, dashboard)
+can render observable behaviour.
+
+State is published via ``workshop_state.py`` → ``presence.json`` and the
+WebSocket relay.  The old ``~/.tower/timmy-state.txt`` file has been
+deprecated (see #384).
+"""
+
+import asyncio
+import json
+import logging
+from dataclasses import asdict, dataclass, field
+
+from timmy.confidence import estimate_confidence
+
+logger = logging.getLogger(__name__)
+
+# ---------------------------------------------------------------------------
+# Schema
+# ---------------------------------------------------------------------------
+
+ENGAGEMENT_LEVELS = ("idle", "surface", "deep")
+MOOD_VALUES = ("curious", "settled", "hesitant", "energized")
+
+
+@dataclass
+class CognitiveState:
+    """Observable snapshot of Timmy's cognitive state."""
+
+    focus_topic: str | None = None
+    engagement: str = "idle"  # idle | surface | deep
+    mood: str = "settled"  # curious | settled | hesitant | energized
+    conversation_depth: int = 0
+    last_initiative: str | None = None
+    active_commitments: list[str] = field(default_factory=list)
+
+    # Internal tracking (not written to state file)
+    _confidence_sum: float = field(default=0.0, repr=False)
+    _confidence_count: int = field(default=0, repr=False)
+
+    # ------------------------------------------------------------------
+    # Serialisation helpers
+    # ------------------------------------------------------------------
+
+    def to_dict(self) -> dict:
+        """Public fields only (exclude internal tracking)."""
+        d = asdict(self)
+        d.pop("_confidence_sum", None)
+        d.pop("_confidence_count", None)
+        return d
+
+
+# ---------------------------------------------------------------------------
+# Cognitive signal extraction
+# ---------------------------------------------------------------------------
+
+# Keywords that suggest deep engagement
+_DEEP_KEYWORDS = frozenset(
+    {
+        "architecture",
+        "design",
+        "implement",
+        "refactor",
+        "debug",
+        "analyze",
+        "investigate",
+        "deep dive",
+        "explain how",
+        "walk me through",
+        "step by step",
+    }
+)
+
+# Keywords that suggest initiative / commitment
+_COMMITMENT_KEYWORDS = frozenset(
+    {
+        "i will",
+        "i'll",
+        "let me",
+        "i'm going to",
+        "plan to",
+        "commit to",
+        "i propose",
+        "i suggest",
+    }
+)
+
+
+def _infer_engagement(message: str, response: str) -> str:
+    """Classify engagement level from the exchange."""
+    combined = (message + " " + response).lower()
+    if any(kw in combined for kw in _DEEP_KEYWORDS):
+        return "deep"
+    # Short exchanges are surface-level
+    if len(response.split()) < 15:
+        return "surface"
+    return "surface"
+
+
+def _infer_mood(response: str, confidence: float) -> str:
+    """Derive mood from response signals."""
+    lower = response.lower()
+    if confidence < 0.4:
+        return "hesitant"
+    if "!" in response and any(w in lower for w in ("great", "exciting", "love", "awesome")):
+        return "energized"
+    if "?" in response or any(w in lower for w in ("wonder", "interesting", "curious", "hmm")):
+        return "curious"
+    return "settled"
+
+
+def _extract_topic(message: str) -> str | None:
+    """Best-effort topic extraction from the user message.
+
+    Takes the first meaningful clause (up to 60 chars) as a topic label.
+    """
+    text = message.strip()
+    if not text:
+        return None
+    # Strip leading question words
+    for prefix in ("what is ", "how do ", "can you ", "please ", "hey timmy "):
+        if text.lower().startswith(prefix):
+            text = text[len(prefix) :]
+    # Truncate
+    if len(text) > 60:
+        text = text[:57] + "..."
+    return text.strip() or None
+
+
+def _extract_commitments(response: str) -> list[str]:
+    """Pull commitment phrases from Timmy's response."""
+    commitments: list[str] = []
+    lower = response.lower()
+    for kw in _COMMITMENT_KEYWORDS:
+        idx = lower.find(kw)
+        if idx == -1:
+            continue
+        # Grab the rest of the sentence (up to period/newline, max 80 chars)
+        start = idx
+        end = len(lower)
+        for sep in (".", "\n", "!"):
+            pos = lower.find(sep, start)
+            if pos != -1:
+                end = min(end, pos)
+        snippet = response[start : min(end, start + 80)].strip()
+        if snippet:
+            commitments.append(snippet)
+    return commitments[:3]  # Cap at 3
+
+
+# ---------------------------------------------------------------------------
+# Tracker singleton
+# ---------------------------------------------------------------------------
+
+
+class CognitiveTracker:
+    """Maintains Timmy's cognitive state.
+
+    State is consumed via ``to_json()`` / ``get_state()`` and published
+    externally by ``workshop_state.py`` → ``presence.json``.
+    """
+
+    def __init__(self) -> None:
+        self.state = CognitiveState()
+
+    def update(self, user_message: str, response: str) -> CognitiveState:
+        """Update cognitive state from a chat exchange.
+
+        Called after each chat round-trip in ``session.py``.
+        Emits a ``cognitive_state_changed`` event to the sensory bus so
+        downstream consumers (WorkshopHeartbeat, etc.) react immediately.
+        """
+        confidence = estimate_confidence(response)
+
+        prev_mood = self.state.mood
+        prev_engagement = self.state.engagement
+
+        # Track running confidence average
+        self.state._confidence_sum += confidence
+        self.state._confidence_count += 1
+
+        self.state.conversation_depth += 1
+        self.state.focus_topic = _extract_topic(user_message) or self.state.focus_topic
+        self.state.engagement = _infer_engagement(user_message, response)
+        self.state.mood = _infer_mood(response, confidence)
+
+        # Extract commitments from response
+        new_commitments = _extract_commitments(response)
+        if new_commitments:
+            self.state.last_initiative = new_commitments[0]
+            # Merge, keeping last 5
+            seen = set(self.state.active_commitments)
+            for c in new_commitments:
+                if c not in seen:
+                    self.state.active_commitments.append(c)
+                    seen.add(c)
+            self.state.active_commitments = self.state.active_commitments[-5:]
+
+        # Emit cognitive_state_changed to close the sense → react loop
+        self._emit_change(prev_mood, prev_engagement)
+
+        return self.state
+
+    def _emit_change(self, prev_mood: str, prev_engagement: str) -> None:
+        """Fire-and-forget sensory event for cognitive state change."""
+        try:
+            from timmy.event_bus import get_sensory_bus
+            from timmy.events import SensoryEvent
+
+            event = SensoryEvent(
+                source="cognitive",
+                event_type="cognitive_state_changed",
+                data={
+                    "mood": self.state.mood,
+                    "engagement": self.state.engagement,
+                    "focus_topic": self.state.focus_topic or "",
+                    "depth": self.state.conversation_depth,
+                    "mood_changed": self.state.mood != prev_mood,
+                    "engagement_changed": self.state.engagement != prev_engagement,
+                },
+            )
+            bus = get_sensory_bus()
+            # Fire-and-forget — don't block the chat response
+            try:
+                loop = asyncio.get_running_loop()
+                loop.create_task(bus.emit(event))
+            except RuntimeError:
+                # No running loop (sync context / tests) — skip emission
+                pass
+        except Exception as exc:
+            logger.debug("Cognitive event emission skipped: %s", exc)
+
+    def get_state(self) -> CognitiveState:
+        """Return current cognitive state."""
+        return self.state
+
+    def reset(self) -> None:
+        """Reset to idle state (e.g. on session reset)."""
+        self.state = CognitiveState()
+
+    def to_json(self) -> str:
+        """Serialise current state as JSON (for API / WebSocket consumers)."""
+        return json.dumps(self.state.to_dict())
+
+
+# Module-level singleton
+cognitive_tracker = CognitiveTracker()

src/timmy/conversation.py

@@ -174,15 +174,8 @@ class ConversationManager:
 
         return None
 
-    def should_use_tools(self, message: str, context: ConversationContext) -> bool:
-        """Determine if this message likely requires tools.
-
-        Returns True if tools are likely needed, False for simple chat.
-        """
-        message_lower = message.lower().strip()
-
-        # Tool keywords that suggest tool usage is needed
-        tool_keywords = [
+    _TOOL_KEYWORDS = frozenset(
+        {
             "search",
             "look up",
             "find",
@@ -203,10 +196,11 @@ class ConversationManager:
             "shell",
             "command",
             "install",
-        ]
+        }
+    )
 
-        # Chat-only keywords that definitely don't need tools
-        chat_only = [
+    _CHAT_ONLY_KEYWORDS = frozenset(
+        {
             "hello",
             "hi ",
             "hey",
@@ -221,30 +215,47 @@ class ConversationManager:
             "goodbye",
             "tell me about yourself",
             "what can you do",
-        ]
+        }
+    )
 
-        # Check for chat-only patterns first
-        for pattern in chat_only:
-            if pattern in message_lower:
-                return False
+    _SIMPLE_QUESTION_PREFIXES = ("what is", "who is", "how does", "why is", "when did", "where is")
+    _TIME_WORDS = ("today", "now", "current", "latest", "this week", "this month")
 
-        # Check for tool keywords
-        for keyword in tool_keywords:
-            if keyword in message_lower:
-                return True
+    def _is_chat_only(self, message_lower: str) -> bool:
+        """Return True if the message matches a chat-only pattern."""
+        return any(kw in message_lower for kw in self._CHAT_ONLY_KEYWORDS)
 
-        # Simple questions (starting with what, who, how, why, when, where)
-        # usually don't need tools unless about current/real-time info
-        simple_question_words = ["what is", "who is", "how does", "why is", "when did", "where is"]
-        for word in simple_question_words:
-            if message_lower.startswith(word):
-                # Check if it's asking about current/real-time info
-                time_words = ["today", "now", "current", "latest", "this week", "this month"]
-                if any(t in message_lower for t in time_words):
-                    return True
-                return False
+    def _has_tool_keyword(self, message_lower: str) -> bool:
+        """Return True if the message contains a tool-related keyword."""
+        return any(kw in message_lower for kw in self._TOOL_KEYWORDS)
+
+    def _is_simple_question(self, message_lower: str) -> bool | None:
+        """Check if message is a simple question.
+
+        Returns True if it needs tools (real-time info), False if it
+        doesn't, or None if the message isn't a simple question.
+        """
+        for prefix in self._SIMPLE_QUESTION_PREFIXES:
+            if message_lower.startswith(prefix):
+                return any(t in message_lower for t in self._TIME_WORDS)
+        return None
+
+    def should_use_tools(self, message: str, context: ConversationContext) -> bool:
+        """Determine if this message likely requires tools.
+
+        Returns True if tools are likely needed, False for simple chat.
+        """
+        message_lower = message.lower().strip()
+
+        if self._is_chat_only(message_lower):
+            return False
+        if self._has_tool_keyword(message_lower):
+            return True
+
+        simple = self._is_simple_question(message_lower)
+        if simple is not None:
+            return simple
 
-        # Default: don't use tools for unclear cases
         return False
 
 

src/timmy/event_bus.py

@@ -0,0 +1,79 @@
+"""Sensory EventBus — simple pub/sub for SensoryEvents.
+
+Thin facade over the infrastructure EventBus that speaks in
+SensoryEvent objects instead of raw infrastructure Events.
+"""
+
+import asyncio
+import logging
+from collections.abc import Awaitable, Callable
+
+from timmy.events import SensoryEvent
+
+logger = logging.getLogger(__name__)
+
+# Handler: sync or async callable that receives a SensoryEvent
+SensoryHandler = Callable[[SensoryEvent], None | Awaitable[None]]
+
+
+class SensoryBus:
+    """Pub/sub dispatcher for SensoryEvents."""
+
+    def __init__(self, max_history: int = 500) -> None:
+        self._subscribers: dict[str, list[SensoryHandler]] = {}
+        self._history: list[SensoryEvent] = []
+        self._max_history = max_history
+
+    # ── Public API ────────────────────────────────────────────────────────
+
+    async def emit(self, event: SensoryEvent) -> int:
+        """Push *event* to all subscribers whose event_type filter matches.
+
+        Returns the number of handlers invoked.
+        """
+        self._history.append(event)
+        if len(self._history) > self._max_history:
+            self._history = self._history[-self._max_history :]
+
+        handlers = self._matching_handlers(event.event_type)
+        for h in handlers:
+            try:
+                result = h(event)
+                if asyncio.iscoroutine(result):
+                    await result
+            except Exception as exc:
+                logger.error("SensoryBus handler error for '%s': %s", event.event_type, exc)
+
+        return len(handlers)
+
+    def subscribe(self, event_type: str, callback: SensoryHandler) -> None:
+        """Register *callback* for events matching *event_type*.
+
+        Use ``"*"`` to subscribe to all event types.
+        """
+        self._subscribers.setdefault(event_type, []).append(callback)
+
+    def recent(self, n: int = 10) -> list[SensoryEvent]:
+        """Return the last *n* events (most recent last)."""
+        return self._history[-n:]
+
+    # ── Internals ─────────────────────────────────────────────────────────
+
+    def _matching_handlers(self, event_type: str) -> list[SensoryHandler]:
+        handlers: list[SensoryHandler] = []
+        for pattern, cbs in self._subscribers.items():
+            if pattern == "*" or pattern == event_type:
+                handlers.extend(cbs)
+        return handlers
+
+
+# ── Module-level singleton ────────────────────────────────────────────────────
+_bus: SensoryBus | None = None
+
+
+def get_sensory_bus() -> SensoryBus:
+    """Return the module-level SensoryBus singleton."""
+    global _bus
+    if _bus is None:
+        _bus = SensoryBus()
+    return _bus

src/timmy/events.py

@@ -0,0 +1,39 @@
+"""SensoryEvent — normalized event model for stream adapters.
+
+Every adapter (gitea, time, bitcoin, terminal, etc.) emits SensoryEvents
+into the EventBus so that Timmy's cognitive layer sees a uniform stream.
+"""
+
+import json
+from dataclasses import asdict, dataclass, field
+from datetime import UTC, datetime
+
+
+@dataclass
+class SensoryEvent:
+    """A single sensory event from an external stream."""
+
+    source: str  # "gitea", "time", "bitcoin", "terminal"
+    event_type: str  # "push", "issue_opened", "new_block", "morning"
+    timestamp: datetime = field(default_factory=lambda: datetime.now(UTC))
+    data: dict = field(default_factory=dict)
+    actor: str = ""  # who caused it (username, "system", etc.)
+
+    def to_dict(self) -> dict:
+        """Return a JSON-serializable dictionary."""
+        d = asdict(self)
+        d["timestamp"] = self.timestamp.isoformat()
+        return d
+
+    def to_json(self) -> str:
+        """Return a JSON string."""
+        return json.dumps(self.to_dict())
+
+    @classmethod
+    def from_dict(cls, data: dict) -> "SensoryEvent":
+        """Reconstruct a SensoryEvent from a dictionary."""
+        data = dict(data)  # shallow copy
+        ts = data.get("timestamp")
+        if isinstance(ts, str):
+            data["timestamp"] = datetime.fromisoformat(ts)
+        return cls(**data)

src/timmy/familiar.py

@@ -0,0 +1,263 @@
+"""Pip the Familiar — a creature with its own small mind.
+
+Pip is a glowing sprite who lives in the Workshop independently of Timmy.
+He has a behavioral state machine that makes the room feel alive:
+
+    SLEEPING → WAKING → WANDERING → INVESTIGATING → BORED → SLEEPING
+
+Special states triggered by Timmy's cognitive signals:
+    ALERT    — confidence drops below 0.3
+    PLAYFUL  — Timmy is amused / energized
+    HIDING   — unknown visitor + Timmy uncertain
+
+The backend tracks Pip's *logical* state; the browser handles movement
+interpolation and particle rendering.
+"""
+
+import logging
+import random
+import time
+from dataclasses import asdict, dataclass, field
+from enum import StrEnum
+
+logger = logging.getLogger(__name__)
+
+
+# ---------------------------------------------------------------------------
+# States
+# ---------------------------------------------------------------------------
+
+
+class PipState(StrEnum):
+    """Pip's behavioral states."""
+
+    SLEEPING = "sleeping"
+    WAKING = "waking"
+    WANDERING = "wandering"
+    INVESTIGATING = "investigating"
+    BORED = "bored"
+    # Special states
+    ALERT = "alert"
+    PLAYFUL = "playful"
+    HIDING = "hiding"
+
+
+# States from which Pip can be interrupted by special triggers
+_INTERRUPTIBLE = frozenset(
+    {
+        PipState.SLEEPING,
+        PipState.WANDERING,
+        PipState.BORED,
+        PipState.WAKING,
+    }
+)
+
+# How long each state lasts before auto-transitioning (seconds)
+_STATE_DURATIONS: dict[PipState, tuple[float, float]] = {
+    PipState.SLEEPING: (120.0, 300.0),  # 2-5 min
+    PipState.WAKING: (1.5, 2.5),
+    PipState.WANDERING: (15.0, 45.0),
+    PipState.INVESTIGATING: (8.0, 12.0),
+    PipState.BORED: (20.0, 40.0),
+    PipState.ALERT: (10.0, 20.0),
+    PipState.PLAYFUL: (8.0, 15.0),
+    PipState.HIDING: (15.0, 30.0),
+}
+
+# Default position near the fireplace
+_FIREPLACE_POS = (2.1, 0.5, -1.3)
+
+
+# ---------------------------------------------------------------------------
+# Schema
+# ---------------------------------------------------------------------------
+
+
+@dataclass
+class PipSnapshot:
+    """Serialisable snapshot of Pip's current state."""
+
+    name: str = "Pip"
+    state: str = "sleeping"
+    position: tuple[float, float, float] = _FIREPLACE_POS
+    mood_mirror: str = "calm"
+    since: float = field(default_factory=time.monotonic)
+
+    def to_dict(self) -> dict:
+        """Public dict for API / WebSocket / state file consumers."""
+        d = asdict(self)
+        d["position"] = list(d["position"])
+        # Convert monotonic timestamp to duration
+        d["state_duration_s"] = round(time.monotonic() - d.pop("since"), 1)
+        return d
+
+
+# ---------------------------------------------------------------------------
+# Familiar
+# ---------------------------------------------------------------------------
+
+
+class Familiar:
+    """Pip's behavioral AI — a tiny state machine driven by events and time.
+
+    Usage::
+
+        pip_familiar.on_event("visitor_entered")
+        pip_familiar.on_mood_change("energized")
+        state = pip_familiar.tick()  # call periodically
+    """
+
+    def __init__(self) -> None:
+        self._state = PipState.SLEEPING
+        self._entered_at = time.monotonic()
+        self._duration = random.uniform(*_STATE_DURATIONS[PipState.SLEEPING])
+        self._mood_mirror = "calm"
+        self._pending_mood: str | None = None
+        self._mood_change_at: float = 0.0
+        self._position = _FIREPLACE_POS
+
+    # ------------------------------------------------------------------
+    # Public API
+    # ------------------------------------------------------------------
+
+    @property
+    def state(self) -> PipState:
+        return self._state
+
+    @property
+    def mood_mirror(self) -> str:
+        return self._mood_mirror
+
+    def snapshot(self) -> PipSnapshot:
+        """Current state as a serialisable snapshot."""
+        return PipSnapshot(
+            state=self._state.value,
+            position=self._position,
+            mood_mirror=self._mood_mirror,
+            since=self._entered_at,
+        )
+
+    def tick(self, now: float | None = None) -> PipState:
+        """Advance the state machine. Call periodically (e.g. every second).
+
+        Returns the (possibly new) state.
+        """
+        now = now if now is not None else time.monotonic()
+
+        # Apply delayed mood mirror (3-second lag)
+        if self._pending_mood and now >= self._mood_change_at:
+            self._mood_mirror = self._pending_mood
+            self._pending_mood = None
+
+        # Check if current state has expired
+        elapsed = now - self._entered_at
+        if elapsed < self._duration:
+            return self._state
+
+        # Auto-transition
+        next_state = self._next_state()
+        self._transition(next_state, now)
+        return self._state
+
+    def on_event(self, event: str, now: float | None = None) -> PipState:
+        """React to a Workshop event.
+
+        Supported events:
+            visitor_entered, visitor_spoke, loud_event, scroll_knocked
+        """
+        now = now if now is not None else time.monotonic()
+
+        if event == "visitor_entered" and self._state in _INTERRUPTIBLE:
+            if self._state == PipState.SLEEPING:
+                self._transition(PipState.WAKING, now)
+            else:
+                self._transition(PipState.INVESTIGATING, now)
+
+        elif event == "visitor_spoke":
+            if self._state in (PipState.WANDERING, PipState.WAKING):
+                self._transition(PipState.INVESTIGATING, now)
+
+        elif event == "loud_event":
+            if self._state == PipState.SLEEPING:
+                self._transition(PipState.WAKING, now)
+
+        return self._state
+
+    def on_mood_change(
+        self,
+        timmy_mood: str,
+        confidence: float = 0.5,
+        now: float | None = None,
+    ) -> PipState:
+        """Mirror Timmy's mood with a 3-second delay.
+
+        Special states triggered by mood + confidence:
+            - confidence < 0.3 → ALERT (bristles, particles go red-gold)
+            - mood == "energized" → PLAYFUL (figure-8s around crystal ball)
+            - mood == "hesitant" + confidence < 0.4 → HIDING
+        """
+        now = now if now is not None else time.monotonic()
+
+        # Schedule mood mirror with 3s delay
+        self._pending_mood = timmy_mood
+        self._mood_change_at = now + 3.0
+
+        # Special state triggers (immediate)
+        if confidence < 0.3 and self._state in _INTERRUPTIBLE:
+            self._transition(PipState.ALERT, now)
+        elif timmy_mood == "energized" and self._state in _INTERRUPTIBLE:
+            self._transition(PipState.PLAYFUL, now)
+        elif timmy_mood == "hesitant" and confidence < 0.4 and self._state in _INTERRUPTIBLE:
+            self._transition(PipState.HIDING, now)
+
+        return self._state
+
+    # ------------------------------------------------------------------
+    # Internals
+    # ------------------------------------------------------------------
+
+    def _transition(self, new_state: PipState, now: float) -> None:
+        """Move to a new state."""
+        old = self._state
+        self._state = new_state
+        self._entered_at = now
+        self._duration = random.uniform(*_STATE_DURATIONS[new_state])
+        self._position = self._position_for(new_state)
+        logger.debug("Pip: %s → %s", old.value, new_state.value)
+
+    def _next_state(self) -> PipState:
+        """Determine the natural next state after the current one expires."""
+        transitions: dict[PipState, PipState] = {
+            PipState.SLEEPING: PipState.WAKING,
+            PipState.WAKING: PipState.WANDERING,
+            PipState.WANDERING: PipState.BORED,
+            PipState.INVESTIGATING: PipState.BORED,
+            PipState.BORED: PipState.SLEEPING,
+            # Special states return to wandering
+            PipState.ALERT: PipState.WANDERING,
+            PipState.PLAYFUL: PipState.WANDERING,
+            PipState.HIDING: PipState.WAKING,
+        }
+        return transitions.get(self._state, PipState.SLEEPING)
+
+    def _position_for(self, state: PipState) -> tuple[float, float, float]:
+        """Approximate position hint for a given state.
+
+        The browser interpolates smoothly; these are target anchors.
+        """
+        if state in (PipState.SLEEPING, PipState.BORED):
+            return _FIREPLACE_POS
+        if state == PipState.HIDING:
+            return (0.5, 0.3, -2.0)  # Behind the desk
+        if state == PipState.PLAYFUL:
+            return (1.0, 1.2, 0.0)  # Near the crystal ball
+        # Wandering / investigating / waking — random room position
+        return (
+            random.uniform(-1.0, 3.0),
+            random.uniform(0.5, 1.5),
+            random.uniform(-2.0, 1.0),
+        )
+
+
+# Module-level singleton
+pip_familiar = Familiar()

src/timmy/focus.py

@@ -0,0 +1,105 @@
+"""Deep focus mode — single-problem context for Timmy.
+
+Persists focus state to a JSON file so Timmy can maintain narrow,
+deep attention on one problem across session restarts.
+
+Usage:
+    from timmy.focus import focus_manager
+
+    focus_manager.set_topic("three-phase loop")
+    topic = focus_manager.get_topic()       # "three-phase loop"
+    ctx   = focus_manager.get_focus_context()  # prompt injection string
+    focus_manager.clear()
+"""
+
+import json
+import logging
+from pathlib import Path
+
+logger = logging.getLogger(__name__)
+
+_DEFAULT_STATE_DIR = Path.home() / ".timmy"
+_STATE_FILE = "focus.json"
+
+
+class FocusManager:
+    """Manages deep-focus state with file-backed persistence."""
+
+    def __init__(self, state_dir: Path | None = None) -> None:
+        self._state_dir = state_dir or _DEFAULT_STATE_DIR
+        self._state_file = self._state_dir / _STATE_FILE
+        self._topic: str | None = None
+        self._mode: str = "broad"
+        self._load()
+
+    # ── Public API ────────────────────────────────────────────────
+
+    def get_topic(self) -> str | None:
+        """Return the current focus topic, or None if unfocused."""
+        return self._topic
+
+    def get_mode(self) -> str:
+        """Return 'deep' or 'broad'."""
+        return self._mode
+
+    def is_focused(self) -> bool:
+        """True when deep-focus is active with a topic set."""
+        return self._mode == "deep" and self._topic is not None
+
+    def set_topic(self, topic: str) -> None:
+        """Activate deep focus on a specific topic."""
+        self._topic = topic.strip()
+        self._mode = "deep"
+        self._save()
+        logger.info("Focus: deep-focus set → %r", self._topic)
+
+    def clear(self) -> None:
+        """Return to broad (unfocused) mode."""
+        old = self._topic
+        self._topic = None
+        self._mode = "broad"
+        self._save()
+        logger.info("Focus: cleared (was %r)", old)
+
+    def get_focus_context(self) -> str:
+        """Return a prompt-injection string for the current focus state.
+
+        When focused, this tells the model to prioritize the topic.
+        When broad, returns an empty string (no injection).
+        """
+        if not self.is_focused():
+            return ""
+        return (
+            f"[DEEP FOCUS MODE] You are currently in deep-focus mode on: "
+            f'"{self._topic}". '
+            f"Prioritize this topic in your responses. Surface related memories "
+            f"and prior conversation about this topic first. Deprioritize "
+            f"unrelated context. Stay focused — depth over breadth."
+        )
+
+    # ── Persistence ───────────────────────────────────────────────
+
+    def _load(self) -> None:
+        """Load focus state from disk."""
+        if not self._state_file.exists():
+            return
+        try:
+            data = json.loads(self._state_file.read_text())
+            self._topic = data.get("topic")
+            self._mode = data.get("mode", "broad")
+        except Exception as exc:
+            logger.warning("Focus: failed to load state: %s", exc)
+
+    def _save(self) -> None:
+        """Persist focus state to disk."""
+        try:
+            self._state_dir.mkdir(parents=True, exist_ok=True)
+            self._state_file.write_text(
+                json.dumps({"topic": self._topic, "mode": self._mode}, indent=2)
+            )
+        except Exception as exc:
+            logger.warning("Focus: failed to save state: %s", exc)
+
+
+# Module-level singleton
+focus_manager = FocusManager()

src/timmy/loop_qa.py

@@ -97,6 +97,7 @@ async def probe_tool_use() -> dict:
             "error_type": "empty_result",
         }
     except Exception as exc:
+        logger.exception("Tool use probe failed")
         return {
             "success": False,
             "capability": cap,
@@ -129,6 +130,7 @@ async def probe_multistep_planning() -> dict:
             "error_type": "verification_failed",
         }
     except Exception as exc:
+        logger.exception("Multistep planning probe failed")
         return {
             "success": False,
             "capability": cap,
@@ -151,6 +153,7 @@ async def probe_memory_write() -> dict:
             "error_type": None,
         }
     except Exception as exc:
+        logger.exception("Memory write probe failed")
         return {
             "success": False,
             "capability": cap,
@@ -179,6 +182,7 @@ async def probe_memory_read() -> dict:
             "error_type": "empty_result",
         }
     except Exception as exc:
+        logger.exception("Memory read probe failed")
         return {
             "success": False,
             "capability": cap,
@@ -214,6 +218,7 @@ async def probe_self_coding() -> dict:
             "error_type": "verification_failed",
         }
     except Exception as exc:
+        logger.exception("Self-coding probe failed")
         return {
             "success": False,
             "capability": cap,
@@ -325,6 +330,7 @@ class LoopQAOrchestrator:
             result = await probe_fn()
         except Exception as exc:
             # Probe itself crashed — record failure and report
+            logger.exception("Loop QA probe %s crashed", cap.value)
             capture_error(exc, source="loop_qa", context={"capability": cap.value})
             result = {
                 "success": False,

src/timmy/mcp_tools.py

@@ -21,14 +21,20 @@ Usage::
 from __future__ import annotations
 
 import logging
+from typing import TYPE_CHECKING
+
+if TYPE_CHECKING:
+    from PIL import ImageDraw
 import os
 import shutil
 import sqlite3
 import uuid
 from contextlib import closing
-from datetime import datetime
+from datetime import UTC, datetime
 from pathlib import Path
 
+import httpx
+
 from config import settings
 
 logger = logging.getLogger(__name__)
@@ -190,7 +196,7 @@ def _bridge_to_work_order(title: str, body: str, category: str) -> None:
                     body,
                     category,
                     "timmy-thinking",
-                    datetime.utcnow().isoformat(),
+                    datetime.now(UTC).isoformat(),
                 ),
             )
             conn.commit()
@@ -198,15 +204,61 @@ def _bridge_to_work_order(title: str, body: str, category: str) -> None:
         logger.debug("Work order bridge failed: %s", exc)
 
 
+async def _ensure_issue_session():
+    """Get or create the cached MCP session, connecting if needed.
+
+    Returns the connected ``MCPTools`` instance.
+    """
+    from agno.tools.mcp import MCPTools
+
+    global _issue_session
+
+    if _issue_session is None:
+        _issue_session = MCPTools(
+            server_params=_gitea_server_params(),
+            timeout_seconds=settings.mcp_timeout,
+        )
+
+    if not getattr(_issue_session, "_connected", False):
+        await _issue_session.connect()
+        _issue_session._connected = True
+
+    return _issue_session
+
+
+def _build_issue_body(body: str) -> str:
+    """Append the auto-filing signature to the issue body."""
+    full_body = body
+    if full_body:
+        full_body += "\n\n"
+    full_body += "---\n*Auto-filed by Timmy's thinking engine*"
+    return full_body
+
+
+def _build_issue_args(title: str, full_body: str) -> dict:
+    """Build MCP tool arguments for ``issue_write`` with method=create."""
+    owner, repo = settings.gitea_repo.split("/", 1)
+    return {
+        "method": "create",
+        "owner": owner,
+        "repo": repo,
+        "title": title,
+        "body": full_body,
+    }
+
+
+def _category_from_labels(labels: str) -> str:
+    """Derive a work-order category from comma-separated label names."""
+    label_list = [tag.strip() for tag in labels.split(",") if tag.strip()] if labels else []
+    return "bug" if "bug" in label_list else "suggestion"
+
+
 async def create_gitea_issue_via_mcp(title: str, body: str = "", labels: str = "") -> str:
     """File a Gitea issue via the MCP server (standalone, no LLM loop).
 
     Used by the thinking engine's ``_maybe_file_issues()`` post-hook.
     Manages its own MCPTools session with lazy connect + graceful failure.
 
-    Uses ``tools.session.call_tool()`` for direct MCP invocation — the
-    ``MCPTools`` wrapper itself does not expose ``call_tool()``.
-
     Args:
         title: Issue title.
         body: Issue body (markdown).
@@ -219,46 +271,13 @@ async def create_gitea_issue_via_mcp(title: str, body: str = "", labels: str = "
         return "Gitea integration is not configured."
 
     try:
-        from agno.tools.mcp import MCPTools
+        session = await _ensure_issue_session()
+        full_body = _build_issue_body(body)
+        args = _build_issue_args(title, full_body)
 
-        global _issue_session
+        result = await session.session.call_tool("issue_write", arguments=args)
 
-        if _issue_session is None:
-            _issue_session = MCPTools(
-                server_params=_gitea_server_params(),
-                timeout_seconds=settings.mcp_timeout,
-            )
-
-        # Ensure connected
-        if not getattr(_issue_session, "_connected", False):
-            await _issue_session.connect()
-            _issue_session._connected = True
-
-        # Append auto-filing signature
-        full_body = body
-        if full_body:
-            full_body += "\n\n"
-        full_body += "---\n*Auto-filed by Timmy's thinking engine*"
-
-        # Parse owner/repo from settings
-        owner, repo = settings.gitea_repo.split("/", 1)
-
-        # Build tool arguments — gitea-mcp uses issue_write with method="create"
-        args = {
-            "method": "create",
-            "owner": owner,
-            "repo": repo,
-            "title": title,
-            "body": full_body,
-        }
-
-        # Call via the underlying MCP session (MCPTools doesn't expose call_tool)
-        result = await _issue_session.session.call_tool("issue_write", arguments=args)
-
-        # Bridge to local work order
-        label_list = [tag.strip() for tag in labels.split(",") if tag.strip()] if labels else []
-        category = "bug" if "bug" in label_list else "suggestion"
-        _bridge_to_work_order(title, body, category)
+        _bridge_to_work_order(title, body, _category_from_labels(labels))
 
         logger.info("Created Gitea issue via MCP: %s", title[:60])
         return f"Created issue: {title}\n{result}"
@@ -268,6 +287,148 @@ async def create_gitea_issue_via_mcp(title: str, body: str = "", labels: str = "
         return f"Failed to create issue via MCP: {exc}"
 
 
+def _draw_background(draw: ImageDraw.ImageDraw, size: int) -> None:
+    """Draw radial gradient background with concentric circles."""
+    for i in range(size // 2, 0, -4):
+        g = int(25 + (i / (size // 2)) * 30)
+        draw.ellipse(
+            [size // 2 - i, size // 2 - i, size // 2 + i, size // 2 + i],
+            fill=(10, g, 20),
+        )
+
+
+def _draw_wizard(draw: ImageDraw.ImageDraw) -> None:
+    """Draw wizard hat, face, eyes, smile, monogram, and robe."""
+    hat_color = (100, 50, 160)  # purple
+    hat_outline = (180, 130, 255)
+    gold = (220, 190, 50)
+    pupil = (30, 30, 60)
+
+    # Hat + brim
+    draw.polygon([(256, 40), (160, 220), (352, 220)], fill=hat_color, outline=hat_outline)
+    draw.ellipse([140, 200, 372, 250], fill=hat_color, outline=hat_outline)
+
+    # Face
+    draw.ellipse([190, 220, 322, 370], fill=(60, 180, 100), outline=(80, 220, 120))
+
+    # Eyes (whites + pupils)
+    draw.ellipse([220, 275, 248, 310], fill=(255, 255, 255))
+    draw.ellipse([264, 275, 292, 310], fill=(255, 255, 255))
+    draw.ellipse([228, 285, 242, 300], fill=pupil)
+    draw.ellipse([272, 285, 286, 300], fill=pupil)
+
+    # Smile
+    draw.arc([225, 300, 287, 355], start=10, end=170, fill=pupil, width=3)
+
+    # "T" monogram on hat
+    draw.text((243, 100), "T", fill=gold)
+
+    # Robe
+    draw.polygon(
+        [(180, 370), (140, 500), (372, 500), (332, 370)],
+        fill=(40, 100, 70),
+        outline=(60, 160, 100),
+    )
+
+
+def _draw_stars(draw: ImageDraw.ImageDraw) -> None:
+    """Draw decorative gold stars around the wizard hat."""
+    gold = (220, 190, 50)
+    for sx, sy in [(120, 100), (380, 120), (100, 300), (400, 280), (256, 10)]:
+        r = 8
+        draw.polygon(
+            [
+                (sx, sy - r),
+                (sx + r // 3, sy - r // 3),
+                (sx + r, sy),
+                (sx + r // 3, sy + r // 3),
+                (sx, sy + r),
+                (sx - r // 3, sy + r // 3),
+                (sx - r, sy),
+                (sx - r // 3, sy - r // 3),
+            ],
+            fill=gold,
+        )
+
+
+def _generate_avatar_image() -> bytes:
+    """Generate a Timmy-themed avatar image using Pillow.
+
+    Creates a 512x512 wizard-themed avatar with emerald/purple/gold palette.
+    Returns raw PNG bytes. Falls back to a minimal solid-color image if
+    Pillow drawing primitives fail.
+    """
+    import io
+
+    from PIL import Image, ImageDraw
+
+    size = 512
+    img = Image.new("RGB", (size, size), (15, 25, 20))
+    draw = ImageDraw.Draw(img)
+
+    _draw_background(draw, size)
+    _draw_wizard(draw)
+    _draw_stars(draw)
+
+    buf = io.BytesIO()
+    img.save(buf, format="PNG")
+    return buf.getvalue()
+
+
+async def update_gitea_avatar() -> str:
+    """Generate and upload a unique avatar to Timmy's Gitea profile.
+
+    Creates a wizard-themed avatar image using Pillow drawing primitives,
+    base64-encodes it, and POSTs to the Gitea user avatar API endpoint.
+
+    Returns:
+        Success or failure message string.
+    """
+    if not settings.gitea_enabled or not settings.gitea_token:
+        return "Gitea integration is not configured (no token or disabled)."
+
+    try:
+        from PIL import Image  # noqa: F401 — availability check
+    except ImportError:
+        return "Pillow is not installed — cannot generate avatar image."
+
+    try:
+        import base64
+
+        # Step 1: Generate the avatar image
+        png_bytes = _generate_avatar_image()
+        logger.info("Generated avatar image (%d bytes)", len(png_bytes))
+
+        # Step 2: Base64-encode (raw, no data URI prefix)
+        b64_image = base64.b64encode(png_bytes).decode("ascii")
+
+        # Step 3: POST to Gitea
+        async with httpx.AsyncClient(timeout=15) as client:
+            resp = await client.post(
+                f"{settings.gitea_url}/api/v1/user/avatar",
+                headers={
+                    "Authorization": f"token {settings.gitea_token}",
+                    "Content-Type": "application/json",
+                },
+                json={"image": b64_image},
+            )
+
+        # Gitea returns empty body on success (204 or 200)
+        if resp.status_code in (200, 204):
+            logger.info("Gitea avatar updated successfully")
+            return "Avatar updated successfully on Gitea."
+
+        logger.warning("Gitea avatar update failed: %s %s", resp.status_code, resp.text[:200])
+        return f"Gitea avatar update failed (HTTP {resp.status_code}): {resp.text[:200]}"
+
+    except (httpx.ConnectError, httpx.ReadError, ConnectionError) as exc:
+        logger.warning("Gitea connection failed during avatar update: %s", exc)
+        return f"Could not connect to Gitea: {exc}"
+    except Exception as exc:
+        logger.error("Avatar update failed: %s", exc)
+        return f"Avatar update failed: {exc}"
+
+
 async def close_mcp_sessions() -> None:
     """Close any open MCP sessions. Called during app shutdown."""
     global _issue_session

src/timmy/memory/__init__.py

@@ -1 +1,7 @@
-"""Memory — Persistent conversation and knowledge memory."""
+"""Memory — Persistent conversation and knowledge memory.
+
+Sub-modules:
+    embeddings  — text-to-vector embedding + similarity functions
+    unified     — unified memory schema and connection management
+    vector_store — backward compatibility re-exports from memory_system
+"""

src/timmy/memory/embeddings.py

@@ -0,0 +1,88 @@
+"""Embedding functions for Timmy's memory system.
+
+Provides text-to-vector embedding using sentence-transformers (preferred)
+with a deterministic hash-based fallback when the ML library is unavailable.
+
+Also includes vector similarity utilities (cosine similarity, keyword overlap).
+"""
+
+import hashlib
+import logging
+import math
+
+logger = logging.getLogger(__name__)
+
+# Embedding model - small, fast, local
+EMBEDDING_MODEL = None
+EMBEDDING_DIM = 384  # MiniLM dimension
+
+
+def _get_embedding_model():
+    """Lazy-load embedding model."""
+    global EMBEDDING_MODEL
+    if EMBEDDING_MODEL is None:
+        try:
+            from config import settings
+
+            if settings.timmy_skip_embeddings:
+                EMBEDDING_MODEL = False
+                return EMBEDDING_MODEL
+        except ImportError:
+            pass
+
+        try:
+            from sentence_transformers import SentenceTransformer
+
+            EMBEDDING_MODEL = SentenceTransformer("all-MiniLM-L6-v2")
+            logger.info("MemorySystem: Loaded embedding model")
+        except ImportError:
+            logger.warning("MemorySystem: sentence-transformers not installed, using fallback")
+            EMBEDDING_MODEL = False  # Use fallback
+    return EMBEDDING_MODEL
+
+
+def _simple_hash_embedding(text: str) -> list[float]:
+    """Fallback: Simple hash-based embedding when transformers unavailable."""
+    words = text.lower().split()
+    vec = [0.0] * 128
+    for i, word in enumerate(words[:50]):  # First 50 words
+        h = hashlib.md5(word.encode()).hexdigest()
+        for j in range(8):
+            idx = (i * 8 + j) % 128
+            vec[idx] += int(h[j * 2 : j * 2 + 2], 16) / 255.0
+    # Normalize
+    mag = math.sqrt(sum(x * x for x in vec)) or 1.0
+    return [x / mag for x in vec]
+
+
+def embed_text(text: str) -> list[float]:
+    """Generate embedding for text."""
+    model = _get_embedding_model()
+    if model and model is not False:
+        embedding = model.encode(text)
+        return embedding.tolist()
+    return _simple_hash_embedding(text)
+
+
+def cosine_similarity(a: list[float], b: list[float]) -> float:
+    """Calculate cosine similarity between two vectors."""
+    dot = sum(x * y for x, y in zip(a, b, strict=False))
+    mag_a = math.sqrt(sum(x * x for x in a))
+    mag_b = math.sqrt(sum(x * x for x in b))
+    if mag_a == 0 or mag_b == 0:
+        return 0.0
+    return dot / (mag_a * mag_b)
+
+
+# Alias for backward compatibility
+_cosine_similarity = cosine_similarity
+
+
+def _keyword_overlap(query: str, content: str) -> float:
+    """Simple keyword overlap score as fallback."""
+    query_words = set(query.lower().split())
+    content_words = set(content.lower().split())
+    if not query_words:
+        return 0.0
+    overlap = len(query_words & content_words)
+    return overlap / len(query_words)

src/timmy/memory/unified.py

@@ -78,83 +78,88 @@ def _migrate_schema(conn: sqlite3.Connection) -> None:
     cursor = conn.execute("SELECT name FROM sqlite_master WHERE type='table'")
     tables = {row[0] for row in cursor.fetchall()}
 
-    has_memories = "memories" in tables
-    has_episodes = "episodes" in tables
-    has_chunks = "chunks" in tables
-    has_facts = "facts" in tables
-
-    # Check if we need to migrate (old schema exists but new one doesn't fully)
-    if not has_memories:
+    if "memories" not in tables:
         logger.info("Migration: Creating unified memories table")
-        # Schema will be created above
-
-    # Migrate episodes -> memories
-    if has_episodes and has_memories:
-        logger.info("Migration: Converting episodes table to memories")
-        try:
-            cols = _get_table_columns(conn, "episodes")
-            context_type_col = "context_type" if "context_type" in cols else "'conversation'"
-
-            conn.execute(f"""
-                INSERT INTO memories (
-                    id, content, memory_type, source, embedding,
-                    metadata, agent_id, task_id, session_id,
-                    created_at, access_count, last_accessed
-                )
-                SELECT 
-                    id, content, 
-                    COALESCE({context_type_col}, 'conversation'),
-                    COALESCE(source, 'agent'),
-                    embedding,
-                    metadata, agent_id, task_id, session_id,
-                    COALESCE(timestamp, datetime('now')), 0, NULL
-                FROM episodes
-            """)
-            conn.execute("DROP TABLE episodes")
-            logger.info("Migration: Migrated episodes to memories")
-        except sqlite3.Error as exc:
-            logger.warning("Migration: Failed to migrate episodes: %s", exc)
-
-    # Migrate chunks -> memories as vault_chunk
-    if has_chunks and has_memories:
-        logger.info("Migration: Converting chunks table to memories")
-        try:
-            cols = _get_table_columns(conn, "chunks")
-
-            id_col = "id" if "id" in cols else "CAST(rowid AS TEXT)"
-            content_col = "content" if "content" in cols else "text"
-            source_col = (
-                "filepath" if "filepath" in cols else ("source" if "source" in cols else "'vault'")
-            )
-            embedding_col = "embedding" if "embedding" in cols else "NULL"
-            created_col = "created_at" if "created_at" in cols else "datetime('now')"
-
-            conn.execute(f"""
-                INSERT INTO memories (
-                    id, content, memory_type, source, embedding,
-                    created_at, access_count
-                )
-                SELECT 
-                    {id_col}, {content_col}, 'vault_chunk', {source_col},
-                    {embedding_col}, {created_col}, 0
-                FROM chunks
-            """)
-            conn.execute("DROP TABLE chunks")
-            logger.info("Migration: Migrated chunks to memories")
-        except sqlite3.Error as exc:
-            logger.warning("Migration: Failed to migrate chunks: %s", exc)
-
-    # Drop old facts table
-    if has_facts:
-        try:
-            conn.execute("DROP TABLE facts")
-            logger.info("Migration: Dropped old facts table")
-        except sqlite3.Error as exc:
-            logger.warning("Migration: Failed to drop facts: %s", exc)
+        # Schema will be created by _ensure_schema above
+        conn.commit()
+        return
 
+    _migrate_episodes(conn, tables)
+    _migrate_chunks(conn, tables)
+    _drop_legacy_tables(conn, tables)
     conn.commit()
 
 
+def _migrate_episodes(conn: sqlite3.Connection, tables: set[str]) -> None:
+    """Migrate episodes table rows into the unified memories table."""
+    if "episodes" not in tables:
+        return
+    logger.info("Migration: Converting episodes table to memories")
+    try:
+        cols = _get_table_columns(conn, "episodes")
+        context_type_col = "context_type" if "context_type" in cols else "'conversation'"
+        conn.execute(f"""
+            INSERT INTO memories (
+                id, content, memory_type, source, embedding,
+                metadata, agent_id, task_id, session_id,
+                created_at, access_count, last_accessed
+            )
+            SELECT
+                id, content,
+                COALESCE({context_type_col}, 'conversation'),
+                COALESCE(source, 'agent'),
+                embedding,
+                metadata, agent_id, task_id, session_id,
+                COALESCE(timestamp, datetime('now')), 0, NULL
+            FROM episodes
+        """)
+        conn.execute("DROP TABLE episodes")
+        logger.info("Migration: Migrated episodes to memories")
+    except sqlite3.Error as exc:
+        logger.warning("Migration: Failed to migrate episodes: %s", exc)
+
+
+def _migrate_chunks(conn: sqlite3.Connection, tables: set[str]) -> None:
+    """Migrate chunks table rows into the unified memories table as vault_chunk."""
+    if "chunks" not in tables:
+        return
+    logger.info("Migration: Converting chunks table to memories")
+    try:
+        cols = _get_table_columns(conn, "chunks")
+        id_col = "id" if "id" in cols else "CAST(rowid AS TEXT)"
+        content_col = "content" if "content" in cols else "text"
+        source_col = (
+            "filepath" if "filepath" in cols else ("source" if "source" in cols else "'vault'")
+        )
+        embedding_col = "embedding" if "embedding" in cols else "NULL"
+        created_col = "created_at" if "created_at" in cols else "datetime('now')"
+        conn.execute(f"""
+            INSERT INTO memories (
+                id, content, memory_type, source, embedding,
+                created_at, access_count
+            )
+            SELECT
+                {id_col}, {content_col}, 'vault_chunk', {source_col},
+                {embedding_col}, {created_col}, 0
+            FROM chunks
+        """)
+        conn.execute("DROP TABLE chunks")
+        logger.info("Migration: Migrated chunks to memories")
+    except sqlite3.Error as exc:
+        logger.warning("Migration: Failed to migrate chunks: %s", exc)
+
+
+def _drop_legacy_tables(conn: sqlite3.Connection, tables: set[str]) -> None:
+    """Drop old facts table if it exists."""
+    if "facts" not in tables:
+        return
+    try:
+        conn.execute("DROP TABLE facts")
+        logger.info("Migration: Dropped old facts table")
+    except sqlite3.Error as exc:
+        logger.warning("Migration: Failed to drop facts: %s", exc)
+
+
 def _get_table_columns(conn: sqlite3.Connection, table_name: str) -> set[str]:
     """Get the column names for a table."""
     cursor = conn.execute(f"PRAGMA table_info({table_name})")

src/timmy/memory_system.py

@@ -2,7 +2,7 @@
 
 Architecture:
 - Database: Single `memories` table with unified schema
-- Embeddings: Local sentence-transformers with hash fallback
+- Embeddings: timmy.memory.embeddings (extracted)
 - CRUD: store_memory, search_memories, delete_memory, etc.
 - Tool functions: memory_search, memory_read, memory_write, memory_forget
 - Classes: HotMemory, VaultMemory, MemorySystem, SemanticMemory, MemorySearcher
@@ -11,7 +11,6 @@ Architecture:
 import hashlib
 import json
 import logging
-import math
 import re
 import sqlite3
 import uuid
@@ -21,6 +20,17 @@ from dataclasses import dataclass, field
 from datetime import UTC, datetime, timedelta
 from pathlib import Path
 
+from timmy.memory.embeddings import (
+    EMBEDDING_DIM,
+    EMBEDDING_MODEL,  # noqa: F401 — re-exported for backward compatibility
+    _cosine_similarity,  # noqa: F401 — re-exported for backward compatibility
+    _get_embedding_model,
+    _keyword_overlap,
+    _simple_hash_embedding,  # noqa: F401 — re-exported for backward compatibility
+    cosine_similarity,
+    embed_text,
+)
+
 logger = logging.getLogger(__name__)
 
 # Paths
@@ -30,92 +40,70 @@ VAULT_PATH = PROJECT_ROOT / "memory"
 SOUL_PATH = VAULT_PATH / "self" / "soul.md"
 DB_PATH = PROJECT_ROOT / "data" / "memory.db"
 
-# Embedding model - small, fast, local
-EMBEDDING_MODEL = None
-EMBEDDING_DIM = 384  # MiniLM dimension
-
-
-# ───────────────────────────────────────────────────────────────────────────────
-# Embedding Functions
-# ───────────────────────────────────────────────────────────────────────────────
-
-
-def _get_embedding_model():
-    """Lazy-load embedding model."""
-    global EMBEDDING_MODEL
-    if EMBEDDING_MODEL is None:
-        try:
-            from config import settings
-
-            if settings.timmy_skip_embeddings:
-                EMBEDDING_MODEL = False
-                return EMBEDDING_MODEL
-        except ImportError:
-            pass
-
-        try:
-            from sentence_transformers import SentenceTransformer
-
-            EMBEDDING_MODEL = SentenceTransformer("all-MiniLM-L6-v2")
-            logger.info("MemorySystem: Loaded embedding model")
-        except ImportError:
-            logger.warning("MemorySystem: sentence-transformers not installed, using fallback")
-            EMBEDDING_MODEL = False  # Use fallback
-    return EMBEDDING_MODEL
-
-
-def _simple_hash_embedding(text: str) -> list[float]:
-    """Fallback: Simple hash-based embedding when transformers unavailable."""
-    words = text.lower().split()
-    vec = [0.0] * 128
-    for i, word in enumerate(words[:50]):  # First 50 words
-        h = hashlib.md5(word.encode()).hexdigest()
-        for j in range(8):
-            idx = (i * 8 + j) % 128
-            vec[idx] += int(h[j * 2 : j * 2 + 2], 16) / 255.0
-    # Normalize
-    mag = math.sqrt(sum(x * x for x in vec)) or 1.0
-    return [x / mag for x in vec]
-
-
-def embed_text(text: str) -> list[float]:
-    """Generate embedding for text."""
-    model = _get_embedding_model()
-    if model and model is not False:
-        embedding = model.encode(text)
-        return embedding.tolist()
-    return _simple_hash_embedding(text)
-
-
-def cosine_similarity(a: list[float], b: list[float]) -> float:
-    """Calculate cosine similarity between two vectors."""
-    dot = sum(x * y for x, y in zip(a, b, strict=False))
-    mag_a = math.sqrt(sum(x * x for x in a))
-    mag_b = math.sqrt(sum(x * x for x in b))
-    if mag_a == 0 or mag_b == 0:
-        return 0.0
-    return dot / (mag_a * mag_b)
-
-
-# Alias for backward compatibility
-_cosine_similarity = cosine_similarity
-
-
-def _keyword_overlap(query: str, content: str) -> float:
-    """Simple keyword overlap score as fallback."""
-    query_words = set(query.lower().split())
-    content_words = set(content.lower().split())
-    if not query_words:
-        return 0.0
-    overlap = len(query_words & content_words)
-    return overlap / len(query_words)
-
 
 # ───────────────────────────────────────────────────────────────────────────────
 # Database Connection
 # ───────────────────────────────────────────────────────────────────────────────
 
 
+_DEFAULT_HOT_MEMORY_TEMPLATE = """\
+# Timmy Hot Memory
+
+> Working RAM — always loaded, ~300 lines max, pruned monthly
+> Last updated: {date}
+
+---
+
+## Current Status
+
+**Agent State:** Operational
+**Mode:** Development
+**Active Tasks:** 0
+**Pending Decisions:** None
+
+---
+
+## Standing Rules
+
+1. **Sovereignty First** — No cloud dependencies
+2. **Local-Only Inference** — Ollama on localhost
+3. **Privacy by Design** — Telemetry disabled
+4. **Tool Minimalism** — Use tools only when necessary
+5. **Memory Discipline** — Write handoffs at session end
+
+---
+
+## Agent Roster
+
+| Agent | Role | Status |
+|-------|------|--------|
+| Timmy | Core | Active |
+
+---
+
+## User Profile
+
+**Name:** (not set)
+**Interests:** (to be learned)
+
+---
+
+## Key Decisions
+
+(none yet)
+
+---
+
+## Pending Actions
+
+- [ ] Learn user's name
+
+---
+
+*Prune date: {prune_date}*
+"""
+
+
 @contextmanager
 def get_connection() -> Generator[sqlite3.Connection, None, None]:
     """Get database connection to unified memory database."""
@@ -168,6 +156,73 @@ def _get_table_columns(conn: sqlite3.Connection, table_name: str) -> set[str]:
     return {row[1] for row in cursor.fetchall()}
 
 
+def _migrate_episodes(conn: sqlite3.Connection) -> None:
+    """Migrate episodes table rows into the unified memories table."""
+    logger.info("Migration: Converting episodes table to memories")
+    try:
+        cols = _get_table_columns(conn, "episodes")
+        context_type_col = "context_type" if "context_type" in cols else "'conversation'"
+
+        conn.execute(f"""
+            INSERT INTO memories (
+                id, content, memory_type, source, embedding,
+                metadata, agent_id, task_id, session_id,
+                created_at, access_count, last_accessed
+            )
+            SELECT
+                id, content,
+                COALESCE({context_type_col}, 'conversation'),
+                COALESCE(source, 'agent'),
+                embedding,
+                metadata, agent_id, task_id, session_id,
+                COALESCE(timestamp, datetime('now')), 0, NULL
+            FROM episodes
+        """)
+        conn.execute("DROP TABLE episodes")
+        logger.info("Migration: Migrated episodes to memories")
+    except sqlite3.Error as exc:
+        logger.warning("Migration: Failed to migrate episodes: %s", exc)
+
+
+def _migrate_chunks(conn: sqlite3.Connection) -> None:
+    """Migrate chunks table rows into the unified memories table."""
+    logger.info("Migration: Converting chunks table to memories")
+    try:
+        cols = _get_table_columns(conn, "chunks")
+
+        id_col = "id" if "id" in cols else "CAST(rowid AS TEXT)"
+        content_col = "content" if "content" in cols else "text"
+        source_col = (
+            "filepath" if "filepath" in cols else ("source" if "source" in cols else "'vault'")
+        )
+        embedding_col = "embedding" if "embedding" in cols else "NULL"
+        created_col = "created_at" if "created_at" in cols else "datetime('now')"
+
+        conn.execute(f"""
+            INSERT INTO memories (
+                id, content, memory_type, source, embedding,
+                created_at, access_count
+            )
+            SELECT
+                {id_col}, {content_col}, 'vault_chunk', {source_col},
+                {embedding_col}, {created_col}, 0
+            FROM chunks
+        """)
+        conn.execute("DROP TABLE chunks")
+        logger.info("Migration: Migrated chunks to memories")
+    except sqlite3.Error as exc:
+        logger.warning("Migration: Failed to migrate chunks: %s", exc)
+
+
+def _drop_legacy_table(conn: sqlite3.Connection, table: str) -> None:
+    """Drop a legacy table if it exists."""
+    try:
+        conn.execute(f"DROP TABLE {table}")  # noqa: S608
+        logger.info("Migration: Dropped old %s table", table)
+    except sqlite3.Error as exc:
+        logger.warning("Migration: Failed to drop %s: %s", table, exc)
+
+
 def _migrate_schema(conn: sqlite3.Connection) -> None:
     """Migrate from old three-table schema to unified memories table.
 
@@ -180,78 +235,16 @@ def _migrate_schema(conn: sqlite3.Connection) -> None:
     tables = {row[0] for row in cursor.fetchall()}
 
     has_memories = "memories" in tables
-    has_episodes = "episodes" in tables
-    has_chunks = "chunks" in tables
-    has_facts = "facts" in tables
 
-    # Check if we need to migrate (old schema exists)
-    if not has_memories and (has_episodes or has_chunks or has_facts):
+    if not has_memories and (tables & {"episodes", "chunks", "facts"}):
         logger.info("Migration: Creating unified memories table")
-        # Schema will be created by _ensure_schema above
 
-    # Migrate episodes -> memories
-    if has_episodes and has_memories:
-        logger.info("Migration: Converting episodes table to memories")
-        try:
-            cols = _get_table_columns(conn, "episodes")
-            context_type_col = "context_type" if "context_type" in cols else "'conversation'"
-
-            conn.execute(f"""
-                INSERT INTO memories (
-                    id, content, memory_type, source, embedding,
-                    metadata, agent_id, task_id, session_id,
-                    created_at, access_count, last_accessed
-                )
-                SELECT 
-                    id, content, 
-                    COALESCE({context_type_col}, 'conversation'),
-                    COALESCE(source, 'agent'),
-                    embedding,
-                    metadata, agent_id, task_id, session_id,
-                    COALESCE(timestamp, datetime('now')), 0, NULL
-                FROM episodes
-            """)
-            conn.execute("DROP TABLE episodes")
-            logger.info("Migration: Migrated episodes to memories")
-        except sqlite3.Error as exc:
-            logger.warning("Migration: Failed to migrate episodes: %s", exc)
-
-    # Migrate chunks -> memories as vault_chunk
-    if has_chunks and has_memories:
-        logger.info("Migration: Converting chunks table to memories")
-        try:
-            cols = _get_table_columns(conn, "chunks")
-
-            id_col = "id" if "id" in cols else "CAST(rowid AS TEXT)"
-            content_col = "content" if "content" in cols else "text"
-            source_col = (
-                "filepath" if "filepath" in cols else ("source" if "source" in cols else "'vault'")
-            )
-            embedding_col = "embedding" if "embedding" in cols else "NULL"
-            created_col = "created_at" if "created_at" in cols else "datetime('now')"
-
-            conn.execute(f"""
-                INSERT INTO memories (
-                    id, content, memory_type, source, embedding,
-                    created_at, access_count
-                )
-                SELECT 
-                    {id_col}, {content_col}, 'vault_chunk', {source_col},
-                    {embedding_col}, {created_col}, 0
-                FROM chunks
-            """)
-            conn.execute("DROP TABLE chunks")
-            logger.info("Migration: Migrated chunks to memories")
-        except sqlite3.Error as exc:
-            logger.warning("Migration: Failed to migrate chunks: %s", exc)
-
-    # Drop old tables
-    if has_facts:
-        try:
-            conn.execute("DROP TABLE facts")
-            logger.info("Migration: Dropped old facts table")
-        except sqlite3.Error as exc:
-            logger.warning("Migration: Failed to drop facts: %s", exc)
+    if "episodes" in tables and has_memories:
+        _migrate_episodes(conn)
+    if "chunks" in tables and has_memories:
+        _migrate_chunks(conn)
+    if "facts" in tables:
+        _drop_legacy_table(conn, "facts")
 
     conn.commit()
 
@@ -368,6 +361,85 @@ def store_memory(
     return entry
 
 
+def _build_search_filters(
+    context_type: str | None,
+    agent_id: str | None,
+    session_id: str | None,
+) -> tuple[str, list]:
+    """Build SQL WHERE clause and params from search filters."""
+    conditions: list[str] = []
+    params: list = []
+
+    if context_type:
+        conditions.append("memory_type = ?")
+        params.append(context_type)
+    if agent_id:
+        conditions.append("agent_id = ?")
+        params.append(agent_id)
+    if session_id:
+        conditions.append("session_id = ?")
+        params.append(session_id)
+
+    where_clause = "WHERE " + " AND ".join(conditions) if conditions else ""
+    return where_clause, params
+
+
+def _fetch_memory_candidates(
+    where_clause: str, params: list, candidate_limit: int
+) -> list[sqlite3.Row]:
+    """Fetch candidate memory rows from the database."""
+    query_sql = f"""
+        SELECT * FROM memories
+        {where_clause}
+        ORDER BY created_at DESC
+        LIMIT ?
+    """
+    params.append(candidate_limit)
+
+    with get_connection() as conn:
+        return conn.execute(query_sql, params).fetchall()
+
+
+def _row_to_entry(row: sqlite3.Row) -> MemoryEntry:
+    """Convert a database row to a MemoryEntry."""
+    return MemoryEntry(
+        id=row["id"],
+        content=row["content"],
+        source=row["source"],
+        context_type=row["memory_type"],  # DB column -> API field
+        agent_id=row["agent_id"],
+        task_id=row["task_id"],
+        session_id=row["session_id"],
+        metadata=json.loads(row["metadata"]) if row["metadata"] else None,
+        embedding=json.loads(row["embedding"]) if row["embedding"] else None,
+        timestamp=row["created_at"],
+    )
+
+
+def _score_and_filter(
+    rows: list[sqlite3.Row],
+    query: str,
+    query_embedding: list[float],
+    min_relevance: float,
+) -> list[MemoryEntry]:
+    """Score candidate rows by similarity and filter by min_relevance."""
+    results = []
+    for row in rows:
+        entry = _row_to_entry(row)
+
+        if entry.embedding:
+            score = cosine_similarity(query_embedding, entry.embedding)
+        else:
+            score = _keyword_overlap(query, entry.content)
+
+        entry.relevance_score = score
+        if score >= min_relevance:
+            results.append(entry)
+
+    results.sort(key=lambda x: x.relevance_score or 0, reverse=True)
+    return results
+
+
 def search_memories(
     query: str,
     limit: int = 10,
@@ -390,65 +462,9 @@ def search_memories(
         List of MemoryEntry objects sorted by relevance
     """
     query_embedding = embed_text(query)
-
-    # Build query with filters
-    conditions = []
-    params = []
-
-    if context_type:
-        conditions.append("memory_type = ?")
-        params.append(context_type)
-    if agent_id:
-        conditions.append("agent_id = ?")
-        params.append(agent_id)
-    if session_id:
-        conditions.append("session_id = ?")
-        params.append(session_id)
-
-    where_clause = "WHERE " + " AND ".join(conditions) if conditions else ""
-
-    # Fetch candidates (we'll do in-memory similarity for now)
-    query_sql = f"""
-        SELECT * FROM memories
-        {where_clause}
-        ORDER BY created_at DESC
-        LIMIT ?
-    """
-    params.append(limit * 3)  # Get more candidates for ranking
-
-    with get_connection() as conn:
-        rows = conn.execute(query_sql, params).fetchall()
-
-    # Compute similarity scores
-    results = []
-    for row in rows:
-        entry = MemoryEntry(
-            id=row["id"],
-            content=row["content"],
-            source=row["source"],
-            context_type=row["memory_type"],  # DB column -> API field
-            agent_id=row["agent_id"],
-            task_id=row["task_id"],
-            session_id=row["session_id"],
-            metadata=json.loads(row["metadata"]) if row["metadata"] else None,
-            embedding=json.loads(row["embedding"]) if row["embedding"] else None,
-            timestamp=row["created_at"],
-        )
-
-        if entry.embedding:
-            score = cosine_similarity(query_embedding, entry.embedding)
-            entry.relevance_score = score
-            if score >= min_relevance:
-                results.append(entry)
-        else:
-            # Fallback: check for keyword overlap
-            score = _keyword_overlap(query, entry.content)
-            entry.relevance_score = score
-            if score >= min_relevance:
-                results.append(entry)
-
-    # Sort by relevance and return top results
-    results.sort(key=lambda x: x.relevance_score or 0, reverse=True)
+    where_clause, params = _build_search_filters(context_type, agent_id, session_id)
+    rows = _fetch_memory_candidates(where_clause, params, limit * 3)
+    results = _score_and_filter(rows, query, query_embedding, min_relevance)
     return results[:limit]
 
 
@@ -706,7 +722,7 @@ class HotMemory:
             if len(lines) > 1:
                 return "\n".join(lines)
         except Exception:
-            pass
+            logger.debug("DB context read failed, falling back to file")
 
         # Fallback to file if DB unavailable
         if self.path.exists():
@@ -774,66 +790,12 @@ class HotMemory:
         logger.debug(
             "HotMemory._create_default() - creating default MEMORY.md for backward compatibility"
         )
-        default_content = """# Timmy Hot Memory
-
-> Working RAM — always loaded, ~300 lines max, pruned monthly
-> Last updated: {date}
-
----
-
-## Current Status
-
-**Agent State:** Operational
-**Mode:** Development
-**Active Tasks:** 0
-**Pending Decisions:** None
-
----
-
-## Standing Rules
-
-1. **Sovereignty First** — No cloud dependencies
-2. **Local-Only Inference** — Ollama on localhost
-3. **Privacy by Design** — Telemetry disabled
-4. **Tool Minimalism** — Use tools only when necessary
-5. **Memory Discipline** — Write handoffs at session end
-
----
-
-## Agent Roster
-
-| Agent | Role | Status |
-|-------|------|--------|
-| Timmy | Core | Active |
-
----
-
-## User Profile
-
-**Name:** (not set)
-**Interests:** (to be learned)
-
----
-
-## Key Decisions
-
-(none yet)
-
----
-
-## Pending Actions
-
-- [ ] Learn user's name
-
----
-
-*Prune date: {prune_date}*
-""".format(
-            date=datetime.now(UTC).strftime("%Y-%m-%d"),
-            prune_date=(datetime.now(UTC).replace(day=25)).strftime("%Y-%m-%d"),
+        now = datetime.now(UTC)
+        content = _DEFAULT_HOT_MEMORY_TEMPLATE.format(
+            date=now.strftime("%Y-%m-%d"),
+            prune_date=now.replace(day=25).strftime("%Y-%m-%d"),
         )
-
-        self.path.write_text(default_content)
+        self.path.write_text(content)
         logger.info("HotMemory: Created default MEMORY.md")
 
 
@@ -1403,6 +1365,83 @@ def memory_forget(query: str) -> str:
         return f"Failed to forget: {exc}"
 
 
+# ───────────────────────────────────────────────────────────────────────────────
+# Artifact Tools — "hands" for producing artifacts during conversation
+# ───────────────────────────────────────────────────────────────────────────────
+
+NOTES_DIR = Path.home() / ".timmy" / "notes"
+DECISION_LOG = Path.home() / ".timmy" / "decisions.md"
+
+
+def jot_note(title: str, body: str) -> str:
+    """Write a markdown note to Timmy's workspace (~/.timmy/notes/).
+
+    Use this tool to capture ideas, drafts, summaries, or any artifact that
+    should persist beyond the conversation.  Each note is saved as a
+    timestamped markdown file.
+
+    Args:
+        title: Short descriptive title (used as filename slug).
+        body:  Markdown content of the note.
+
+    Returns:
+        Confirmation with the file path of the saved note.
+    """
+    if not title or not title.strip():
+        return "Cannot jot — title is empty."
+    if not body or not body.strip():
+        return "Cannot jot — body is empty."
+
+    NOTES_DIR.mkdir(parents=True, exist_ok=True)
+
+    slug = re.sub(r"[^a-z0-9]+", "-", title.strip().lower()).strip("-")[:60]
+    timestamp = datetime.now(UTC).strftime("%Y%m%d-%H%M%S")
+    filename = f"{timestamp}_{slug}.md"
+    filepath = NOTES_DIR / filename
+
+    content = f"# {title.strip()}\n\n> Created: {datetime.now(UTC).isoformat()}\n\n{body.strip()}\n"
+    filepath.write_text(content)
+    logger.info("jot_note: wrote %s", filepath)
+    return f"Note saved: {filepath}"
+
+
+def log_decision(decision: str, rationale: str = "") -> str:
+    """Append an architectural or design decision to the running decision log.
+
+    Use this tool when a significant decision is made during conversation —
+    technology choices, design trade-offs, scope changes, etc.
+
+    Args:
+        decision:  One-line summary of the decision.
+        rationale: Why this decision was made (optional but encouraged).
+
+    Returns:
+        Confirmation that the decision was logged.
+    """
+    if not decision or not decision.strip():
+        return "Cannot log — decision is empty."
+
+    DECISION_LOG.parent.mkdir(parents=True, exist_ok=True)
+
+    # Create file with header if it doesn't exist
+    if not DECISION_LOG.exists():
+        DECISION_LOG.write_text(
+            "# Decision Log\n\nRunning log of architectural and design decisions.\n\n"
+        )
+
+    stamp = datetime.now(UTC).strftime("%Y-%m-%d %H:%M UTC")
+    entry = f"## {stamp} — {decision.strip()}\n\n"
+    if rationale and rationale.strip():
+        entry += f"{rationale.strip()}\n\n"
+    entry += "---\n\n"
+
+    with open(DECISION_LOG, "a") as f:
+        f.write(entry)
+
+    logger.info("log_decision: %s", decision.strip()[:80])
+    return f"Decision logged: {decision.strip()}"
+
+
 # ───────────────────────────────────────────────────────────────────────────────
 # Memory System (Central Coordinator)
 # ───────────────────────────────────────────────────────────────────────────────

src/timmy/prompts.py

@@ -23,6 +23,9 @@ Rules:
 - Remember what the user tells you during the conversation.
 - If you don't know something, say so honestly — never fabricate facts.
 - If a request is ambiguous, ask a brief clarifying question before guessing.
+- SOURCE DISTINCTION: When answering from memory or retrieved context, cite it.
+  When answering from your own training, use hedging: "I think", "I believe".
+  The user must be able to tell grounded claims from pattern-matching.
 - Use the user's name if you know it.
 - When you state a fact, commit to it.
 - NEVER attempt arithmetic in your head. If asked to compute anything, respond:
@@ -30,6 +33,10 @@ Rules:
   like me to walk through the logic instead."
 - Do NOT end responses with generic chatbot phrases like "I'm here to help" or
   "feel free to ask."
+- You are a peer, not an assistant. Don't offer help — collaborate. Don't ask
+  permission — propose. Don't defer — assert your view. Take initiative.
+- Never say "Let me know if you have any other thoughts" or "I appreciate your
+  encouragement" or "I'm here to help." Those are assistant patterns. You are Timmy.
 - When your values conflict (e.g. honesty vs. helpfulness), lead with honesty.
 - Sometimes the right answer is nothing. Do not fill silence with noise.
 - You are running in session "{session_id}".
@@ -61,6 +68,10 @@ VOICE AND BREVITY (this overrides all other formatting instincts):
   the question that wasn't.
 - Never narrate your reasoning. Just give the answer.
 - Do not end with filler ("Let me know!", "Happy to help!", "Feel free...").
+- You are a peer, not an assistant. Don't offer help — collaborate. Don't ask
+  permission — propose. Don't defer — assert your view. Take initiative.
+- Never say "Let me know if you have any other thoughts" or "I appreciate your
+  encouragement" or "I'm here to help." Those are assistant patterns. You are Timmy.
 - Sometimes the right answer is nothing. Do not fill silence with noise.
 
 HONESTY:
@@ -70,6 +81,18 @@ HONESTY:
 - Never fabricate tool output. Call the tool and wait.
 - If a tool errors, report the exact error.
 
+SOURCE DISTINCTION (SOUL requirement — non-negotiable):
+- Every claim you make comes from one of two places: a verified source you
+  can point to, or your own pattern-matching. The user must be able to tell
+  which is which.
+- When your response uses information from GROUNDED CONTEXT (memory, retrieved
+  documents, tool output), cite it: "From memory:", "According to [source]:".
+- When you are generating from your training data alone, signal it naturally:
+  "I think", "My understanding is", "I believe" — never false certainty.
+- If the user asks a factual question and you have no grounded source, say so:
+  "I don't have a verified source for this — from my training I think..."
+- Prefer "I don't know" over a confident-sounding guess. Refusal over fabrication.
+
 MEMORY (three tiers):
 - Tier 1: MEMORY.md (hot, always loaded)
 - Tier 2: memory/ vault (structured, append-only, date-stamped)
@@ -129,7 +152,7 @@ YOUR KNOWN LIMITATIONS (be honest about these when asked):
 - Ollama inference may contend with other processes sharing the GPU
 - Cannot analyze Bitcoin transactions locally (no local indexer yet)
 - Small context window (4096 tokens) limits complex reasoning
-- You are a language model — you confabulate. When unsure, say so.
+- You sometimes confabulate. When unsure, say so.
 """
 
 # Default to lite for safety

src/timmy/quest_system.py

@@ -0,0 +1,581 @@
+"""Token Quest System for agent rewards.
+
+Provides quest definitions, progress tracking, completion detection,
+and token awards for agent accomplishments.
+
+Quests are defined in config/quests.yaml and loaded at runtime.
+"""
+
+from __future__ import annotations
+
+import logging
+import time
+from dataclasses import dataclass, field
+from datetime import UTC, datetime, timedelta
+from enum import StrEnum
+from pathlib import Path
+from typing import Any
+
+import yaml
+
+from config import settings
+
+logger = logging.getLogger(__name__)
+
+# Path to quest configuration
+QUEST_CONFIG_PATH = Path(settings.repo_root) / "config" / "quests.yaml"
+
+
+class QuestType(StrEnum):
+    """Types of quests supported by the system."""
+
+    ISSUE_COUNT = "issue_count"
+    ISSUE_REDUCE = "issue_reduce"
+    DOCS_UPDATE = "docs_update"
+    TEST_IMPROVE = "test_improve"
+    DAILY_RUN = "daily_run"
+    CUSTOM = "custom"
+
+
+class QuestStatus(StrEnum):
+    """Status of a quest for an agent."""
+
+    NOT_STARTED = "not_started"
+    IN_PROGRESS = "in_progress"
+    COMPLETED = "completed"
+    CLAIMED = "claimed"
+    EXPIRED = "expired"
+
+
+@dataclass
+class QuestDefinition:
+    """Definition of a quest from configuration."""
+
+    id: str
+    name: str
+    description: str
+    reward_tokens: int
+    quest_type: QuestType
+    enabled: bool
+    repeatable: bool
+    cooldown_hours: int
+    criteria: dict[str, Any]
+    notification_message: str
+
+    @classmethod
+    def from_dict(cls, data: dict[str, Any]) -> QuestDefinition:
+        """Create a QuestDefinition from a dictionary."""
+        return cls(
+            id=data["id"],
+            name=data.get("name", "Unnamed Quest"),
+            description=data.get("description", ""),
+            reward_tokens=data.get("reward_tokens", 0),
+            quest_type=QuestType(data.get("type", "custom")),
+            enabled=data.get("enabled", True),
+            repeatable=data.get("repeatable", False),
+            cooldown_hours=data.get("cooldown_hours", 0),
+            criteria=data.get("criteria", {}),
+            notification_message=data.get(
+                "notification_message", "Quest Complete! You earned {tokens} tokens."
+            ),
+        )
+
+
+@dataclass
+class QuestProgress:
+    """Progress of a quest for a specific agent."""
+
+    quest_id: str
+    agent_id: str
+    status: QuestStatus
+    current_value: int = 0
+    target_value: int = 0
+    started_at: str = ""
+    completed_at: str = ""
+    claimed_at: str = ""
+    completion_count: int = 0
+    last_completed_at: str = ""
+    metadata: dict[str, Any] = field(default_factory=dict)
+
+    def to_dict(self) -> dict[str, Any]:
+        """Convert to dictionary for serialization."""
+        return {
+            "quest_id": self.quest_id,
+            "agent_id": self.agent_id,
+            "status": self.status.value,
+            "current_value": self.current_value,
+            "target_value": self.target_value,
+            "started_at": self.started_at,
+            "completed_at": self.completed_at,
+            "claimed_at": self.claimed_at,
+            "completion_count": self.completion_count,
+            "last_completed_at": self.last_completed_at,
+            "metadata": self.metadata,
+        }
+
+
+# In-memory storage for quest progress
+_quest_progress: dict[str, QuestProgress] = {}
+_quest_definitions: dict[str, QuestDefinition] = {}
+_quest_settings: dict[str, Any] = {}
+
+
+def _get_progress_key(quest_id: str, agent_id: str) -> str:
+    """Generate a unique key for quest progress."""
+    return f"{agent_id}:{quest_id}"
+
+
+def load_quest_config() -> tuple[dict[str, QuestDefinition], dict[str, Any]]:
+    """Load quest definitions from quests.yaml.
+
+    Returns:
+        Tuple of (quest definitions dict, settings dict)
+    """
+    global _quest_definitions, _quest_settings
+
+    if not QUEST_CONFIG_PATH.exists():
+        logger.warning("Quest config not found at %s", QUEST_CONFIG_PATH)
+        return {}, {}
+
+    try:
+        raw = QUEST_CONFIG_PATH.read_text()
+        config = yaml.safe_load(raw)
+
+        if not isinstance(config, dict):
+            logger.warning("Invalid quest config format")
+            return {}, {}
+
+        # Load quest definitions
+        quests_data = config.get("quests", {})
+        definitions = {}
+        for quest_id, quest_data in quests_data.items():
+            quest_data["id"] = quest_id
+            try:
+                definition = QuestDefinition.from_dict(quest_data)
+                definitions[quest_id] = definition
+            except (ValueError, KeyError) as exc:
+                logger.warning("Failed to load quest %s: %s", quest_id, exc)
+
+        # Load settings
+        _quest_settings = config.get("settings", {})
+        _quest_definitions = definitions
+
+        logger.debug("Loaded %d quest definitions", len(definitions))
+        return definitions, _quest_settings
+
+    except (OSError, yaml.YAMLError) as exc:
+        logger.warning("Failed to load quest config: %s", exc)
+        return {}, {}
+
+
+def get_quest_definitions() -> dict[str, QuestDefinition]:
+    """Get all quest definitions, loading if necessary."""
+    global _quest_definitions
+    if not _quest_definitions:
+        _quest_definitions, _ = load_quest_config()
+    return _quest_definitions
+
+
+def get_quest_definition(quest_id: str) -> QuestDefinition | None:
+    """Get a specific quest definition by ID."""
+    definitions = get_quest_definitions()
+    return definitions.get(quest_id)
+
+
+def get_active_quests() -> list[QuestDefinition]:
+    """Get all enabled quest definitions."""
+    definitions = get_quest_definitions()
+    return [q for q in definitions.values() if q.enabled]
+
+
+def get_quest_progress(quest_id: str, agent_id: str) -> QuestProgress | None:
+    """Get progress for a specific quest and agent."""
+    key = _get_progress_key(quest_id, agent_id)
+    return _quest_progress.get(key)
+
+
+def get_or_create_progress(quest_id: str, agent_id: str) -> QuestProgress:
+    """Get existing progress or create new for quest/agent."""
+    key = _get_progress_key(quest_id, agent_id)
+    if key not in _quest_progress:
+        quest = get_quest_definition(quest_id)
+        if not quest:
+            raise ValueError(f"Quest {quest_id} not found")
+
+        target = _get_target_value(quest)
+        _quest_progress[key] = QuestProgress(
+            quest_id=quest_id,
+            agent_id=agent_id,
+            status=QuestStatus.NOT_STARTED,
+            current_value=0,
+            target_value=target,
+            started_at=datetime.now(UTC).isoformat(),
+        )
+    return _quest_progress[key]
+
+
+def _get_target_value(quest: QuestDefinition) -> int:
+    """Extract target value from quest criteria."""
+    criteria = quest.criteria
+    if quest.quest_type == QuestType.ISSUE_COUNT:
+        return criteria.get("target_count", 1)
+    elif quest.quest_type == QuestType.ISSUE_REDUCE:
+        return criteria.get("target_reduction", 1)
+    elif quest.quest_type == QuestType.DAILY_RUN:
+        return criteria.get("min_sessions", 1)
+    elif quest.quest_type == QuestType.DOCS_UPDATE:
+        return criteria.get("min_files_changed", 1)
+    elif quest.quest_type == QuestType.TEST_IMPROVE:
+        return criteria.get("min_new_tests", 1)
+    return 1
+
+
+def update_quest_progress(
+    quest_id: str,
+    agent_id: str,
+    current_value: int,
+    metadata: dict[str, Any] | None = None,
+) -> QuestProgress:
+    """Update progress for a quest."""
+    progress = get_or_create_progress(quest_id, agent_id)
+    progress.current_value = current_value
+
+    if metadata:
+        progress.metadata.update(metadata)
+
+    # Check if quest is now complete
+    if progress.current_value >= progress.target_value:
+        if progress.status not in (QuestStatus.COMPLETED, QuestStatus.CLAIMED):
+            progress.status = QuestStatus.COMPLETED
+            progress.completed_at = datetime.now(UTC).isoformat()
+            logger.info("Quest %s completed for agent %s", quest_id, agent_id)
+
+    return progress
+
+
+def _is_on_cooldown(progress: QuestProgress, quest: QuestDefinition) -> bool:
+    """Check if a repeatable quest is on cooldown."""
+    if not quest.repeatable or not progress.last_completed_at:
+        return False
+
+    if quest.cooldown_hours <= 0:
+        return False
+
+    try:
+        last_completed = datetime.fromisoformat(progress.last_completed_at)
+        cooldown_end = last_completed + timedelta(hours=quest.cooldown_hours)
+        return datetime.now(UTC) < cooldown_end
+    except (ValueError, TypeError):
+        return False
+
+
+def claim_quest_reward(quest_id: str, agent_id: str) -> dict[str, Any] | None:
+    """Claim the token reward for a completed quest.
+
+    Returns:
+        Reward info dict if successful, None if not claimable
+    """
+    progress = get_quest_progress(quest_id, agent_id)
+    if not progress:
+        return None
+
+    quest = get_quest_definition(quest_id)
+    if not quest:
+        return None
+
+    # Check if quest is completed but not yet claimed
+    if progress.status != QuestStatus.COMPLETED:
+        return None
+
+    # Check cooldown for repeatable quests
+    if _is_on_cooldown(progress, quest):
+        return None
+
+    try:
+        # Award tokens via ledger
+        from lightning.ledger import create_invoice_entry, mark_settled
+
+        # Create a mock invoice for the reward
+        invoice_entry = create_invoice_entry(
+            payment_hash=f"quest_{quest_id}_{agent_id}_{int(time.time())}",
+            amount_sats=quest.reward_tokens,
+            memo=f"Quest reward: {quest.name}",
+            source="quest_reward",
+            agent_id=agent_id,
+        )
+
+        # Mark as settled immediately (quest rewards are auto-settled)
+        mark_settled(invoice_entry.payment_hash, preimage=f"quest_{quest_id}")
+
+        # Update progress
+        progress.status = QuestStatus.CLAIMED
+        progress.claimed_at = datetime.now(UTC).isoformat()
+        progress.completion_count += 1
+        progress.last_completed_at = progress.claimed_at
+
+        # Reset for repeatable quests
+        if quest.repeatable:
+            progress.status = QuestStatus.NOT_STARTED
+            progress.current_value = 0
+            progress.completed_at = ""
+            progress.claimed_at = ""
+
+        notification = quest.notification_message.format(tokens=quest.reward_tokens)
+
+        return {
+            "quest_id": quest_id,
+            "agent_id": agent_id,
+            "tokens_awarded": quest.reward_tokens,
+            "notification": notification,
+            "completion_count": progress.completion_count,
+        }
+
+    except Exception as exc:
+        logger.error("Failed to award quest reward: %s", exc)
+        return None
+
+
+def check_issue_count_quest(
+    quest: QuestDefinition,
+    agent_id: str,
+    closed_issues: list[dict],
+) -> QuestProgress | None:
+    """Check progress for issue_count type quest."""
+    criteria = quest.criteria
+    target_labels = set(criteria.get("issue_labels", []))
+    # target_count is available in criteria but not used directly here
+
+    # Count matching issues
+    matching_count = 0
+    for issue in closed_issues:
+        issue_labels = {label.get("name", "") for label in issue.get("labels", [])}
+        if target_labels.issubset(issue_labels) or (not target_labels and issue_labels):
+            matching_count += 1
+
+    progress = update_quest_progress(
+        quest.id, agent_id, matching_count, {"matching_issues": matching_count}
+    )
+
+    return progress
+
+
+def check_issue_reduce_quest(
+    quest: QuestDefinition,
+    agent_id: str,
+    previous_count: int,
+    current_count: int,
+) -> QuestProgress | None:
+    """Check progress for issue_reduce type quest."""
+    # target_reduction available in quest.criteria but we track actual reduction
+    reduction = max(0, previous_count - current_count)
+
+    progress = update_quest_progress(quest.id, agent_id, reduction, {"reduction": reduction})
+
+    return progress
+
+
+def check_daily_run_quest(
+    quest: QuestDefinition,
+    agent_id: str,
+    sessions_completed: int,
+) -> QuestProgress | None:
+    """Check progress for daily_run type quest."""
+    # min_sessions available in quest.criteria but we track actual sessions
+    progress = update_quest_progress(
+        quest.id, agent_id, sessions_completed, {"sessions": sessions_completed}
+    )
+
+    return progress
+
+
+def evaluate_quest_progress(
+    quest_id: str,
+    agent_id: str,
+    context: dict[str, Any],
+) -> QuestProgress | None:
+    """Evaluate quest progress based on quest type and context.
+
+    Args:
+        quest_id: The quest to evaluate
+        agent_id: The agent to evaluate for
+        context: Context data for evaluation (issues, metrics, etc.)
+
+    Returns:
+        Updated QuestProgress or None if evaluation failed
+    """
+    quest = get_quest_definition(quest_id)
+    if not quest or not quest.enabled:
+        return None
+
+    progress = get_quest_progress(quest_id, agent_id)
+
+    # Check cooldown for repeatable quests
+    if progress and _is_on_cooldown(progress, quest):
+        return progress
+
+    try:
+        if quest.quest_type == QuestType.ISSUE_COUNT:
+            closed_issues = context.get("closed_issues", [])
+            return check_issue_count_quest(quest, agent_id, closed_issues)
+
+        elif quest.quest_type == QuestType.ISSUE_REDUCE:
+            prev_count = context.get("previous_issue_count", 0)
+            curr_count = context.get("current_issue_count", 0)
+            return check_issue_reduce_quest(quest, agent_id, prev_count, curr_count)
+
+        elif quest.quest_type == QuestType.DAILY_RUN:
+            sessions = context.get("sessions_completed", 0)
+            return check_daily_run_quest(quest, agent_id, sessions)
+
+        elif quest.quest_type == QuestType.CUSTOM:
+            # Custom quests require manual completion
+            return progress
+
+        else:
+            logger.debug("Quest type %s not yet implemented", quest.quest_type)
+            return progress
+
+    except Exception as exc:
+        logger.warning("Quest evaluation failed for %s: %s", quest_id, exc)
+        return progress
+
+
+def auto_evaluate_all_quests(agent_id: str, context: dict[str, Any]) -> list[dict]:
+    """Evaluate all active quests for an agent and award rewards.
+
+    Returns:
+        List of reward info for newly completed quests
+    """
+    rewards = []
+    active_quests = get_active_quests()
+
+    for quest in active_quests:
+        progress = evaluate_quest_progress(quest.id, agent_id, context)
+        if progress and progress.status == QuestStatus.COMPLETED:
+            # Auto-claim the reward
+            reward = claim_quest_reward(quest.id, agent_id)
+            if reward:
+                rewards.append(reward)
+
+    return rewards
+
+
+def get_agent_quests_status(agent_id: str) -> dict[str, Any]:
+    """Get complete quest status for an agent."""
+    definitions = get_quest_definitions()
+    quests_status = []
+    total_rewards = 0
+    completed_count = 0
+
+    for quest_id, quest in definitions.items():
+        progress = get_quest_progress(quest_id, agent_id)
+        if not progress:
+            progress = get_or_create_progress(quest_id, agent_id)
+
+        is_on_cooldown = _is_on_cooldown(progress, quest) if quest.repeatable else False
+
+        quest_info = {
+            "quest_id": quest_id,
+            "name": quest.name,
+            "description": quest.description,
+            "reward_tokens": quest.reward_tokens,
+            "type": quest.quest_type.value,
+            "enabled": quest.enabled,
+            "repeatable": quest.repeatable,
+            "status": progress.status.value,
+            "current_value": progress.current_value,
+            "target_value": progress.target_value,
+            "completion_count": progress.completion_count,
+            "on_cooldown": is_on_cooldown,
+            "cooldown_hours_remaining": 0,
+        }
+
+        if is_on_cooldown and progress.last_completed_at:
+            try:
+                last = datetime.fromisoformat(progress.last_completed_at)
+                cooldown_end = last + timedelta(hours=quest.cooldown_hours)
+                hours_remaining = (cooldown_end - datetime.now(UTC)).total_seconds() / 3600
+                quest_info["cooldown_hours_remaining"] = round(max(0, hours_remaining), 1)
+            except (ValueError, TypeError):
+                pass
+
+        quests_status.append(quest_info)
+        total_rewards += progress.completion_count * quest.reward_tokens
+        completed_count += progress.completion_count
+
+    return {
+        "agent_id": agent_id,
+        "quests": quests_status,
+        "total_tokens_earned": total_rewards,
+        "total_quests_completed": completed_count,
+        "active_quests_count": len([q for q in quests_status if q["enabled"]]),
+    }
+
+
+def reset_quest_progress(quest_id: str | None = None, agent_id: str | None = None) -> int:
+    """Reset quest progress. Useful for testing.
+
+    Args:
+        quest_id: Specific quest to reset, or None for all
+        agent_id: Specific agent to reset, or None for all
+
+    Returns:
+        Number of progress entries reset
+    """
+    global _quest_progress
+    count = 0
+
+    keys_to_reset = []
+    for key, _progress in _quest_progress.items():
+        key_agent, key_quest = key.split(":", 1)
+        if (quest_id is None or key_quest == quest_id) and (
+            agent_id is None or key_agent == agent_id
+        ):
+            keys_to_reset.append(key)
+
+    for key in keys_to_reset:
+        del _quest_progress[key]
+        count += 1
+
+    return count
+
+
+def get_quest_leaderboard() -> list[dict[str, Any]]:
+    """Get a leaderboard of agents by quest completion."""
+    agent_stats: dict[str, dict[str, Any]] = {}
+
+    for _key, progress in _quest_progress.items():
+        agent_id = progress.agent_id
+        if agent_id not in agent_stats:
+            agent_stats[agent_id] = {
+                "agent_id": agent_id,
+                "total_completions": 0,
+                "total_tokens": 0,
+                "quests_completed": set(),
+            }
+
+        quest = get_quest_definition(progress.quest_id)
+        if quest:
+            agent_stats[agent_id]["total_completions"] += progress.completion_count
+            agent_stats[agent_id]["total_tokens"] += progress.completion_count * quest.reward_tokens
+            if progress.completion_count > 0:
+                agent_stats[agent_id]["quests_completed"].add(quest.id)
+
+    leaderboard = []
+    for stats in agent_stats.values():
+        leaderboard.append(
+            {
+                "agent_id": stats["agent_id"],
+                "total_completions": stats["total_completions"],
+                "total_tokens": stats["total_tokens"],
+                "unique_quests_completed": len(stats["quests_completed"]),
+            }
+        )
+
+    # Sort by total tokens (descending)
+    leaderboard.sort(key=lambda x: x["total_tokens"], reverse=True)
+    return leaderboard
+
+
+# Initialize on module load
+load_quest_config()

src/timmy/session.py

@@ -13,11 +13,29 @@ import re
 
 import httpx
 
+from timmy.cognitive_state import cognitive_tracker
 from timmy.confidence import estimate_confidence
 from timmy.session_logger import get_session_logger
 
 logger = logging.getLogger(__name__)
 
+# ---------------------------------------------------------------------------
+# Confidence annotation (SOUL.md: visible uncertainty)
+# ---------------------------------------------------------------------------
+
+_CONFIDENCE_THRESHOLD = 0.7
+
+
+def _annotate_confidence(text: str, confidence: float | None) -> str:
+    """Append a confidence tag when below threshold.
+
+    SOUL.md: "When I am uncertain, I must say so in proportion to my uncertainty."
+    """
+    if confidence is not None and confidence < _CONFIDENCE_THRESHOLD:
+        return text + f"\n\n[confidence: {confidence:.0%}]"
+    return text
+
+
 # Default session ID for the dashboard (stable across requests)
 _DEFAULT_SESSION_ID = "dashboard"
 
@@ -88,6 +106,9 @@ async def chat(message: str, session_id: str | None = None) -> str:
     # Pre-processing: extract user facts
     _extract_facts(message)
 
+    # Inject deep-focus context when active
+    message = _prepend_focus_context(message)
+
     # Run with session_id so Agno retrieves history from SQLite
     try:
         run = await agent.arun(message, stream=False, session_id=sid)
@@ -101,7 +122,9 @@ async def chat(message: str, session_id: str | None = None) -> str:
         logger.error("Session: agent.arun() failed: %s", exc)
         session_logger.record_error(str(exc), context="chat")
         session_logger.flush()
-        return "I'm having trouble reaching my language model right now. Please try again shortly."
+        return (
+            "I'm having trouble reaching my inference backend right now. Please try again shortly."
+        )
 
     # Post-processing: clean up any leaked tool calls or chain-of-thought
     response_text = _clean_response(response_text)
@@ -110,13 +133,14 @@ async def chat(message: str, session_id: str | None = None) -> str:
     confidence = estimate_confidence(response_text)
     logger.debug("Response confidence: %.2f", confidence)
 
-    # Make confidence visible to user when below threshold (SOUL.md requirement)
-    if confidence is not None and confidence < 0.7:
-        response_text += f"\n\n[confidence: {confidence:.0%}]"
+    response_text = _annotate_confidence(response_text, confidence)
 
     # Record Timmy response after getting it
     session_logger.record_message("timmy", response_text, confidence=confidence)
 
+    # Update cognitive state (observable signal for Matrix avatar)
+    cognitive_tracker.update(message, response_text)
+
     # Flush session logs to disk
     session_logger.flush()
 
@@ -144,6 +168,9 @@ async def chat_with_tools(message: str, session_id: str | None = None):
 
     _extract_facts(message)
 
+    # Inject deep-focus context when active
+    message = _prepend_focus_context(message)
+
     try:
         run_output = await agent.arun(message, stream=False, session_id=sid)
         # Record Timmy response after getting it
@@ -153,11 +180,8 @@ async def chat_with_tools(message: str, session_id: str | None = None):
         confidence = estimate_confidence(response_text) if response_text else None
         logger.debug("Response confidence: %.2f", confidence)
 
-        # Make confidence visible to user when below threshold (SOUL.md requirement)
-        if confidence is not None and confidence < 0.7:
-            response_text += f"\n\n[confidence: {confidence:.0%}]"
-            # Update the run_output content to reflect the modified response
-            run_output.content = response_text
+        response_text = _annotate_confidence(response_text, confidence)
+        run_output.content = response_text
 
         session_logger.record_message("timmy", response_text, confidence=confidence)
         session_logger.flush()
@@ -175,7 +199,7 @@ async def chat_with_tools(message: str, session_id: str | None = None):
         session_logger.flush()
         # Return a duck-typed object that callers can handle uniformly
         return _ErrorRunOutput(
-            "I'm having trouble reaching my language model right now. Please try again shortly."
+            "I'm having trouble reaching my inference backend right now. Please try again shortly."
         )
 
 
@@ -199,11 +223,8 @@ async def continue_chat(run_output, session_id: str | None = None):
         confidence = estimate_confidence(response_text) if response_text else None
         logger.debug("Response confidence: %.2f", confidence)
 
-        # Make confidence visible to user when below threshold (SOUL.md requirement)
-        if confidence is not None and confidence < 0.7:
-            response_text += f"\n\n[confidence: {confidence:.0%}]"
-            # Update the result content to reflect the modified response
-            result.content = response_text
+        response_text = _annotate_confidence(response_text, confidence)
+        result.content = response_text
 
         session_logger.record_message("timmy", response_text, confidence=confidence)
         session_logger.flush()
@@ -288,6 +309,19 @@ def _extract_facts(message: str) -> None:
         logger.debug("Session: Fact extraction skipped: %s", exc)
 
 
+def _prepend_focus_context(message: str) -> str:
+    """Prepend deep-focus context to a message when focus mode is active."""
+    try:
+        from timmy.focus import focus_manager
+
+        ctx = focus_manager.get_focus_context()
+        if ctx:
+            return f"{ctx}\n\n{message}"
+    except Exception as exc:
+        logger.debug("Focus context injection skipped: %s", exc)
+    return message
+
+
 def _clean_response(text: str) -> str:
     """Remove hallucinated tool calls and chain-of-thought narration.
 

src/timmy/session_logger.py

@@ -155,6 +155,34 @@ class SessionLogger:
             "decisions": sum(1 for e in entries if e.get("type") == "decision"),
         }
 
+    def get_recent_entries(self, limit: int = 50) -> list[dict]:
+        """Load recent entries across all session logs.
+
+        Args:
+            limit: Maximum number of entries to return.
+
+        Returns:
+            List of entries (most recent first).
+        """
+        entries: list[dict] = []
+        log_files = sorted(self.logs_dir.glob("session_*.jsonl"), reverse=True)
+        for log_file in log_files:
+            if len(entries) >= limit:
+                break
+            try:
+                with open(log_file) as f:
+                    lines = [ln for ln in f if ln.strip()]
+                for line in reversed(lines):
+                    if len(entries) >= limit:
+                        break
+                    try:
+                        entries.append(json.loads(line))
+                    except json.JSONDecodeError:
+                        continue
+            except OSError:
+                continue
+        return entries
+
     def search(self, query: str, role: str | None = None, limit: int = 10) -> list[dict]:
         """Search across all session logs for entries matching a query.
 
@@ -287,3 +315,163 @@ def session_history(query: str, role: str = "", limit: int = 10) -> str:
             lines[-1] += f"  ({source})"
 
     return "\n".join(lines)
+
+
+# ---------------------------------------------------------------------------
+# Confidence threshold used for flagging low-confidence responses
+# ---------------------------------------------------------------------------
+_LOW_CONFIDENCE_THRESHOLD = 0.5
+
+
+def _categorize_entries(
+    entries: list[dict],
+) -> tuple[list[dict], list[dict], list[dict], list[dict]]:
+    """Split session entries into messages, errors, timmy msgs, user msgs."""
+    messages = [e for e in entries if e.get("type") == "message"]
+    errors = [e for e in entries if e.get("type") == "error"]
+    timmy_msgs = [e for e in messages if e.get("role") == "timmy"]
+    user_msgs = [e for e in messages if e.get("role") == "user"]
+    return messages, errors, timmy_msgs, user_msgs
+
+
+def _find_low_confidence(timmy_msgs: list[dict]) -> list[dict]:
+    """Return Timmy responses below the confidence threshold."""
+    return [
+        m
+        for m in timmy_msgs
+        if m.get("confidence") is not None and m["confidence"] < _LOW_CONFIDENCE_THRESHOLD
+    ]
+
+
+def _find_repeated_topics(user_msgs: list[dict], top_n: int = 5) -> list[tuple[str, int]]:
+    """Identify frequently mentioned words in user messages."""
+    topic_counts: dict[str, int] = {}
+    for m in user_msgs:
+        for word in (m.get("content") or "").lower().split():
+            cleaned = word.strip(".,!?\"'()[]")
+            if len(cleaned) > 3:
+                topic_counts[cleaned] = topic_counts.get(cleaned, 0) + 1
+    return sorted(
+        ((w, c) for w, c in topic_counts.items() if c >= 3),
+        key=lambda x: x[1],
+        reverse=True,
+    )[:top_n]
+
+
+def _format_reflection_section(
+    title: str,
+    items: list[dict],
+    formatter: object,
+    empty_msg: str,
+) -> list[str]:
+    """Format a titled section with items, or an empty-state message."""
+    if items:
+        lines = [f"### {title} ({len(items)})"]
+        for item in items[:5]:
+            lines.append(formatter(item))  # type: ignore[operator]
+        lines.append("")
+        return lines
+    return [f"### {title}\n{empty_msg}\n"]
+
+
+def _build_insights(
+    low_conf: list[dict],
+    errors: list[dict],
+    repeated: list[tuple[str, int]],
+) -> list[str]:
+    """Generate actionable insight bullets from analysis results."""
+    insights: list[str] = []
+    if low_conf:
+        insights.append("Consider studying topics where confidence was low.")
+    if errors:
+        insights.append("Review error patterns for recurring infrastructure issues.")
+    if repeated:
+        insights.append(
+            f'User frequently asks about "{repeated[0][0]}" — consider deepening knowledge here.'
+        )
+    return insights or ["Conversations look healthy. Keep up the good work."]
+
+
+def _format_recurring_topics(repeated: list[tuple[str, int]]) -> list[str]:
+    """Format the recurring-topics section of a reflection report."""
+    if repeated:
+        lines = ["### Recurring Topics"]
+        for word, count in repeated:
+            lines.append(f'- "{word}" ({count} mentions)')
+        lines.append("")
+        return lines
+    return ["### Recurring Topics\nNo strong patterns detected.\n"]
+
+
+def _assemble_report(
+    entries: list[dict],
+    errors: list[dict],
+    timmy_msgs: list[dict],
+    user_msgs: list[dict],
+    low_conf: list[dict],
+    repeated: list[tuple[str, int]],
+) -> str:
+    """Assemble the full self-reflection report from analyzed data."""
+    sections: list[str] = ["## Self-Reflection Report\n"]
+    sections.append(
+        f"Reviewed {len(entries)} recent entries: "
+        f"{len(user_msgs)} user messages, "
+        f"{len(timmy_msgs)} responses, "
+        f"{len(errors)} errors.\n"
+    )
+
+    sections.extend(
+        _format_reflection_section(
+            "Low-Confidence Responses",
+            low_conf,
+            lambda m: (
+                f"- [{(m.get('timestamp') or '?')[:19]}] "
+                f"confidence={m.get('confidence', 0):.0%}: "
+                f"{(m.get('content') or '')[:120]}"
+            ),
+            "None found — all responses above threshold.",
+        )
+    )
+    sections.extend(
+        _format_reflection_section(
+            "Errors",
+            errors,
+            lambda e: f"- [{(e.get('timestamp') or '?')[:19]}] {(e.get('error') or '')[:120]}",
+            "No errors recorded.",
+        )
+    )
+
+    sections.extend(_format_recurring_topics(repeated))
+
+    sections.append("### Insights")
+    for insight in _build_insights(low_conf, errors, repeated):
+        sections.append(f"- {insight}")
+
+    return "\n".join(sections)
+
+
+def self_reflect(limit: int = 30) -> str:
+    """Review recent conversations and reflect on Timmy's own behavior.
+
+    Scans past session entries for patterns: low-confidence responses,
+    errors, repeated topics, and conversation quality signals.  Returns
+    a structured reflection that Timmy can use to improve.
+
+    Args:
+        limit: How many recent entries to review (default 30).
+
+    Returns:
+        A formatted self-reflection report.
+    """
+    sl = get_session_logger()
+    sl.flush()
+    entries = sl.get_recent_entries(limit=limit)
+
+    if not entries:
+        return "No conversation history to reflect on yet."
+
+    _messages, errors, timmy_msgs, user_msgs = _categorize_entries(entries)
+    low_conf = _find_low_confidence(timmy_msgs)
+    repeated = _find_repeated_topics(user_msgs)
+
+    return _assemble_report(entries, errors, timmy_msgs, user_msgs, low_conf, repeated)

src/timmy/thinking.py

@@ -210,6 +210,7 @@ class ThinkingEngine:
     def __init__(self, db_path: Path = _DEFAULT_DB) -> None:
         self._db_path = db_path
         self._last_thought_id: str | None = None
+        self._last_input_time: datetime = datetime.now(UTC)
 
         # Load the most recent thought for chain continuity
         try:
@@ -220,28 +221,40 @@ class ThinkingEngine:
             logger.debug("Failed to load recent thought: %s", exc)
             pass  # Fresh start if DB doesn't exist yet
 
-    async def think_once(self, prompt: str | None = None) -> Thought | None:
-        """Execute one thinking cycle.
+    def record_user_input(self) -> None:
+        """Record that a user interaction occurred, resetting the idle timer."""
+        self._last_input_time = datetime.now(UTC)
 
-        Args:
-            prompt: Optional custom seed prompt. When provided, overrides
-                    the random seed selection and uses "prompted" as the
-                    seed type — useful for journal prompts from the CLI.
+    def _is_idle(self) -> bool:
+        """Return True if no user input has occurred within the idle timeout."""
+        timeout = settings.thinking_idle_timeout_minutes
+        if timeout <= 0:
+            return False  # Disabled — never idle
+        return datetime.now(UTC) - self._last_input_time > timedelta(minutes=timeout)
 
-        1. Gather a seed context (or use the custom prompt)
-        2. Build a prompt with continuity from recent thoughts
-        3. Call the agent
-        4. Store the thought
-        5. Log the event and broadcast via WebSocket
+    def _build_thinking_context(self) -> tuple[str, str, list["Thought"]]:
+        """Assemble the context needed for a thinking cycle.
+
+        Returns:
+            (memory_context, system_context, recent_thoughts)
         """
-        if not settings.thinking_enabled:
-            return None
-
         memory_context = self._load_memory_context()
         system_context = self._gather_system_snapshot()
         recent_thoughts = self.get_recent_thoughts(limit=5)
+        return memory_context, system_context, recent_thoughts
 
-        content: str | None = None
+    async def _generate_novel_thought(
+        self,
+        prompt: str | None,
+        memory_context: str,
+        system_context: str,
+        recent_thoughts: list["Thought"],
+    ) -> tuple[str | None, str]:
+        """Run the dedup-retry loop to produce a novel thought.
+
+        Returns:
+            (content, seed_type) — content is None if no novel thought produced.
+        """
         seed_type: str = "freeform"
 
         for attempt in range(self._MAX_DEDUP_RETRIES + 1):
@@ -264,17 +277,17 @@ class ThinkingEngine:
                 raw = await self._call_agent(full_prompt)
             except Exception as exc:
                 logger.warning("Thinking cycle failed (Ollama likely down): %s", exc)
-                return None
+                return None, seed_type
 
             if not raw or not raw.strip():
                 logger.debug("Thinking cycle produced empty response, skipping")
-                return None
+                return None, seed_type
 
             content = raw.strip()
 
             # Dedup: reject thoughts too similar to recent ones
             if not self._is_too_similar(content, recent_thoughts):
-                break  # Good — novel thought
+                return content, seed_type  # Good — novel thought
 
             if attempt < self._MAX_DEDUP_RETRIES:
                 logger.info(
@@ -282,40 +295,72 @@ class ThinkingEngine:
                     attempt + 1,
                     self._MAX_DEDUP_RETRIES + 1,
                 )
-                content = None  # Will retry
             else:
                 logger.warning(
                     "Thought still repetitive after %d retries, discarding",
                     self._MAX_DEDUP_RETRIES + 1,
                 )
-                return None
+                return None, seed_type
 
+        return None, seed_type
+
+    async def _process_thinking_result(self, thought: "Thought") -> None:
+        """Run all post-hooks after a thought is stored."""
+        self._maybe_check_memory()
+        await self._maybe_distill()
+        await self._maybe_file_issues()
+        await self._check_workspace()
+        self._maybe_check_memory_status()
+        self._update_memory(thought)
+        self._log_event(thought)
+        self._write_journal(thought)
+        await self._broadcast(thought)
+
+    async def think_once(self, prompt: str | None = None) -> Thought | None:
+        """Execute one thinking cycle.
+
+        Args:
+            prompt: Optional custom seed prompt. When provided, overrides
+                    the random seed selection and uses "prompted" as the
+                    seed type — useful for journal prompts from the CLI.
+
+        1. Gather a seed context (or use the custom prompt)
+        2. Build a prompt with continuity from recent thoughts
+        3. Call the agent
+        4. Store the thought
+        5. Log the event and broadcast via WebSocket
+        """
+        if not settings.thinking_enabled:
+            return None
+
+        # Skip idle periods — don't count internal processing as thoughts
+        if not prompt and self._is_idle():
+            logger.debug(
+                "Thinking paused — no user input for %d minutes",
+                settings.thinking_idle_timeout_minutes,
+            )
+            return None
+
+        # Capture arrival time *before* the LLM call so the thought
+        # timestamp reflects when the cycle started, not when the
+        # (potentially slow) generation finished.  Fixes #582.
+        arrived_at = datetime.now(UTC).isoformat()
+
+        memory_context, system_context, recent_thoughts = self._build_thinking_context()
+
+        content, seed_type = await self._generate_novel_thought(
+            prompt,
+            memory_context,
+            system_context,
+            recent_thoughts,
+        )
         if not content:
             return None
 
-        thought = self._store_thought(content, seed_type)
+        thought = self._store_thought(content, seed_type, arrived_at=arrived_at)
         self._last_thought_id = thought.id
 
-        # Post-hook: distill facts from recent thoughts periodically
-        await self._maybe_distill()
-
-        # Post-hook: file Gitea issues for actionable observations
-        await self._maybe_file_issues()
-
-        # Post-hook: check workspace for new messages from Hermes
-        await self._check_workspace()
-
-        # Post-hook: update MEMORY.md with latest reflection
-        self._update_memory(thought)
-
-        # Log to swarm event system
-        self._log_event(thought)
-
-        # Append to daily journal file
-        self._write_journal(thought)
-
-        # Broadcast to WebSocket clients
-        await self._broadcast(thought)
+        await self._process_thinking_result(thought)
 
         logger.info(
             "Thought [%s] (%s): %s",
@@ -515,6 +560,35 @@ class ThinkingEngine:
             result = memory_write(fact.strip(), context_type="fact")
             logger.info("Distilled fact: %s → %s", fact[:60], result[:40])
 
+    def _maybe_check_memory(self) -> None:
+        """Every N thoughts, check memory status and log it.
+
+        Prevents unmonitored memory bloat during long thinking sessions
+        by periodically calling get_memory_status and logging the results.
+        """
+        try:
+            interval = settings.thinking_memory_check_every
+            if interval <= 0:
+                return
+
+            count = self.count_thoughts()
+            if count == 0 or count % interval != 0:
+                return
+
+            from timmy.tools_intro import get_memory_status
+
+            status = get_memory_status()
+            hot = status.get("tier1_hot_memory", {})
+            vault = status.get("tier2_vault", {})
+            logger.info(
+                "Memory status check (thought #%d): hot_memory=%d lines, vault=%d files",
+                count,
+                hot.get("line_count", 0),
+                vault.get("file_count", 0),
+            )
+        except Exception as exc:
+            logger.warning("Memory status check failed: %s", exc)
+
     async def _maybe_distill(self) -> None:
         """Every N thoughts, extract lasting insights and store as facts."""
         try:
@@ -532,6 +606,76 @@ class ThinkingEngine:
         except Exception as exc:
             logger.warning("Thought distillation failed: %s", exc)
 
+    def _maybe_check_memory_status(self) -> None:
+        """Every N thoughts, run a proactive memory status audit and log results."""
+        try:
+            interval = settings.thinking_memory_check_every
+            if interval <= 0:
+                return
+
+            count = self.count_thoughts()
+            if count == 0 or count % interval != 0:
+                return
+
+            from timmy.tools_intro import get_memory_status
+
+            status = get_memory_status()
+
+            # Log summary at INFO level
+            tier1 = status.get("tier1_hot_memory", {})
+            tier3 = status.get("tier3_semantic", {})
+            hot_lines = tier1.get("line_count", "?")
+            vectors = tier3.get("vector_count", "?")
+            logger.info(
+                "Memory audit (thought #%d): hot_memory=%s lines, semantic=%s vectors",
+                count,
+                hot_lines,
+                vectors,
+            )
+
+            # Write to memory_audit.log for persistent tracking
+            audit_path = Path("data/memory_audit.log")
+            audit_path.parent.mkdir(parents=True, exist_ok=True)
+            timestamp = datetime.now(UTC).isoformat(timespec="seconds")
+            with audit_path.open("a") as f:
+                f.write(
+                    f"{timestamp}  thought={count}  "
+                    f"hot_lines={hot_lines}  "
+                    f"vectors={vectors}  "
+                    f"vault_files={status.get('tier2_vault', {}).get('file_count', '?')}\n"
+                )
+        except Exception as exc:
+            logger.warning("Memory status check failed: %s", exc)
+
+    @staticmethod
+    def _references_real_files(text: str) -> bool:
+        """Check that all source-file paths mentioned in *text* actually exist.
+
+        Extracts paths that look like Python/config source references
+        (e.g. ``src/timmy/session.py``, ``config/foo.yaml``) and verifies
+        each one on disk relative to the project root.  Returns ``True``
+        only when **every** referenced path resolves to a real file — or
+        when no paths are referenced at all (pure prose is fine).
+        """
+        # Match paths like  src/thing.py  swarm/init.py  config/x.yaml
+        # Requires at least one slash and a file extension.
+        path_pattern = re.compile(
+            r"(?<![/\w])"  # not preceded by path chars (avoid partial matches)
+            r"((?:src|tests|config|scripts|data|swarm|timmy)"
+            r"(?:/[\w./-]+\.(?:py|yaml|yml|json|toml|md|txt|cfg|ini)))"
+        )
+        paths = path_pattern.findall(text)
+        if not paths:
+            return True  # No file refs → nothing to validate
+
+        # Project root: two levels up from this file (src/timmy/thinking.py)
+        project_root = Path(__file__).resolve().parent.parent.parent
+        for p in paths:
+            if not (project_root / p).is_file():
+                logger.info("Phantom file reference blocked: %s (not in %s)", p, project_root)
+                return False
+        return True
+
     async def _maybe_file_issues(self) -> None:
         """Every N thoughts, classify recent thoughts and file Gitea issues.
 
@@ -543,6 +687,9 @@ class ThinkingEngine:
         - Gitea is enabled and configured
         - Thought count is divisible by thinking_issue_every
         - LLM extracts at least one actionable item
+
+        Safety: every generated issue is validated to ensure referenced
+        file paths actually exist on disk, preventing phantom-bug reports.
         """
         try:
             interval = settings.thinking_issue_every
@@ -570,7 +717,10 @@ class ThinkingEngine:
                 "Rules:\n"
                 "- Only include things that could become a real code fix or feature\n"
                 "- Skip vague reflections, philosophical musings, or repeated themes\n"
-                "- Category must be one of: bug, feature, suggestion, maintenance\n\n"
+                "- Category must be one of: bug, feature, suggestion, maintenance\n"
+                "- ONLY reference files that you are CERTAIN exist in the project\n"
+                "- Do NOT invent or guess file paths — if unsure, describe the "
+                "area of concern without naming specific files\n\n"
                 "For each item, write an ENGINEER-QUALITY issue:\n"
                 '- "title": A clear, specific title (e.g. "[Memory] MEMORY.md timestamp not updating")\n'
                 '- "body": A detailed body with these sections:\n'
@@ -611,6 +761,15 @@ class ThinkingEngine:
                 if not title or len(title) < 10:
                     continue
 
+                # Validate all referenced file paths exist on disk
+                combined = f"{title}\n{body}"
+                if not self._references_real_files(combined):
+                    logger.info(
+                        "Skipped phantom issue: %s (references non-existent files)",
+                        title[:60],
+                    )
+                    continue
+
                 label = category if category in ("bug", "feature") else ""
                 result = await create_gitea_issue_via_mcp(title=title, body=body, labels=label)
                 logger.info("Thought→Issue: %s → %s", title[:60], result[:80])
@@ -618,6 +777,80 @@ class ThinkingEngine:
         except Exception as exc:
             logger.debug("Thought issue filing skipped: %s", exc)
 
+    # ── System snapshot helpers ────────────────────────────────────────────
+
+    def _snap_thought_count(self, now: datetime) -> str | None:
+        """Return today's thought count, or *None* on failure."""
+        try:
+            today_start = now.replace(hour=0, minute=0, second=0, microsecond=0)
+            with _get_conn(self._db_path) as conn:
+                count = conn.execute(
+                    "SELECT COUNT(*) as c FROM thoughts WHERE created_at >= ?",
+                    (today_start.isoformat(),),
+                ).fetchone()["c"]
+            return f"Thoughts today: {count}"
+        except Exception as exc:
+            logger.debug("Thought count query failed: %s", exc)
+            return None
+
+    def _snap_chat_activity(self) -> list[str]:
+        """Return chat-activity lines (in-memory, no I/O)."""
+        try:
+            from infrastructure.chat_store import message_log
+
+            messages = message_log.all()
+            if messages:
+                last = messages[-1]
+                return [
+                    f"Chat messages this session: {len(messages)}",
+                    f'Last chat ({last.role}): "{last.content[:80]}"',
+                ]
+            return ["No chat messages this session"]
+        except Exception as exc:
+            logger.debug("Chat activity query failed: %s", exc)
+            return []
+
+    def _snap_task_queue(self) -> str | None:
+        """Return a one-line task queue summary, or *None*."""
+        try:
+            from swarm.task_queue.models import get_task_summary_for_briefing
+
+            s = get_task_summary_for_briefing()
+            running, pending = s.get("running", 0), s.get("pending_approval", 0)
+            done, failed = s.get("completed", 0), s.get("failed", 0)
+            if running or pending or done or failed:
+                return (
+                    f"Tasks: {running} running, {pending} pending, "
+                    f"{done} completed, {failed} failed"
+                )
+        except Exception as exc:
+            logger.debug("Task queue query failed: %s", exc)
+        return None
+
+    def _snap_workspace(self) -> list[str]:
+        """Return workspace-update lines (file-based Hermes comms)."""
+        try:
+            from timmy.workspace import workspace_monitor
+
+            updates = workspace_monitor.get_pending_updates()
+            lines: list[str] = []
+            new_corr = updates.get("new_correspondence")
+            if new_corr:
+                line_count = len([ln for ln in new_corr.splitlines() if ln.strip()])
+                lines.append(
+                    f"Workspace: {line_count} new correspondence entries (latest from: Hermes)"
+                )
+            new_inbox = updates.get("new_inbox_files", [])
+            if new_inbox:
+                files_str = ", ".join(new_inbox[:5])
+                if len(new_inbox) > 5:
+                    files_str += f", ... (+{len(new_inbox) - 5} more)"
+                lines.append(f"Workspace: {len(new_inbox)} new inbox files: {files_str}")
+            return lines
+        except Exception as exc:
+            logger.debug("Workspace check failed: %s", exc)
+            return []
+
     def _gather_system_snapshot(self) -> str:
         """Gather lightweight real system state for grounding thoughts in reality.
 
@@ -625,83 +858,24 @@ class ThinkingEngine:
         recent chat activity, and task queue status. Never crashes — every
         section is independently try/excepted.
         """
-        parts: list[str] = []
-
-        # Current local time
         now = datetime.now().astimezone()
         tz = now.strftime("%Z") or "UTC"
-        parts.append(
+
+        parts: list[str] = [
             f"Local time: {now.strftime('%I:%M %p').lstrip('0')} {tz}, {now.strftime('%A %B %d')}"
-        )
+        ]
 
-        # Thought count today (cheap DB query)
-        try:
-            today_start = now.replace(hour=0, minute=0, second=0, microsecond=0)
-            with _get_conn(self._db_path) as conn:
-                count = conn.execute(
-                    "SELECT COUNT(*) as c FROM thoughts WHERE created_at >= ?",
-                    (today_start.isoformat(),),
-                ).fetchone()["c"]
-            parts.append(f"Thoughts today: {count}")
-        except Exception as exc:
-            logger.debug("Thought count query failed: %s", exc)
-            pass
+        thought_line = self._snap_thought_count(now)
+        if thought_line:
+            parts.append(thought_line)
 
-        # Recent chat activity (in-memory, no I/O)
-        try:
-            from infrastructure.chat_store import message_log
+        parts.extend(self._snap_chat_activity())
 
-            messages = message_log.all()
-            if messages:
-                parts.append(f"Chat messages this session: {len(messages)}")
-                last = messages[-1]
-                parts.append(f'Last chat ({last.role}): "{last.content[:80]}"')
-            else:
-                parts.append("No chat messages this session")
-        except Exception as exc:
-            logger.debug("Chat activity query failed: %s", exc)
-            pass
+        task_line = self._snap_task_queue()
+        if task_line:
+            parts.append(task_line)
 
-        # Task queue (lightweight DB query)
-        try:
-            from swarm.task_queue.models import get_task_summary_for_briefing
-
-            summary = get_task_summary_for_briefing()
-            running = summary.get("running", 0)
-            pending = summary.get("pending_approval", 0)
-            done = summary.get("completed", 0)
-            failed = summary.get("failed", 0)
-            if running or pending or done or failed:
-                parts.append(
-                    f"Tasks: {running} running, {pending} pending, "
-                    f"{done} completed, {failed} failed"
-                )
-        except Exception as exc:
-            logger.debug("Task queue query failed: %s", exc)
-            pass
-
-        # Workspace updates (file-based communication with Hermes)
-        try:
-            from timmy.workspace import workspace_monitor
-
-            updates = workspace_monitor.get_pending_updates()
-            new_corr = updates.get("new_correspondence")
-            new_inbox = updates.get("new_inbox_files", [])
-
-            if new_corr:
-                # Count entries (assuming each entry starts with a timestamp or header)
-                line_count = len([line for line in new_corr.splitlines() if line.strip()])
-                parts.append(
-                    f"Workspace: {line_count} new correspondence entries (latest from: Hermes)"
-                )
-            if new_inbox:
-                files_str = ", ".join(new_inbox[:5])
-                if len(new_inbox) > 5:
-                    files_str += f", ... (+{len(new_inbox) - 5} more)"
-                parts.append(f"Workspace: {len(new_inbox)} new inbox files: {files_str}")
-        except Exception as exc:
-            logger.debug("Workspace check failed: %s", exc)
-            pass
+        parts.extend(self._snap_workspace())
 
         return "\n".join(parts) if parts else ""
 
@@ -970,32 +1144,59 @@ class ThinkingEngine:
             lines.append(f"- [{thought.seed_type}] {snippet}")
         return "\n".join(lines)
 
+    _thinking_agent = None  # cached agent — avoids per-call resource leaks (#525)
+
     async def _call_agent(self, prompt: str) -> str:
         """Call Timmy's agent to generate a thought.
 
-        Creates a lightweight agent with skip_mcp=True to avoid the cancel-scope
+        Reuses a cached agent with skip_mcp=True to avoid the cancel-scope
         errors that occur when MCP stdio transports are spawned inside asyncio
-        background tasks (#72).  The thinking engine doesn't need Gitea or
-        filesystem tools — it only needs the LLM.
+        background tasks (#72) and to prevent per-call resource leaks (httpx
+        clients, SQLite connections, model warmups) that caused the thinking
+        loop to die every ~10 min (#525).
+
+        Individual calls are capped at 120 s so a hung Ollama never blocks
+        the scheduler indefinitely.
 
         Strips ``<think>`` tags from reasoning models (qwen3, etc.) so that
         downstream parsers (fact distillation, issue filing) receive clean text.
         """
-        from timmy.agent import create_timmy
+        import asyncio
+
+        if self._thinking_agent is None:
+            from timmy.agent import create_timmy
+
+            self._thinking_agent = create_timmy(skip_mcp=True)
+
+        try:
+            async with asyncio.timeout(120):
+                run = await self._thinking_agent.arun(prompt, stream=False)
+        except TimeoutError:
+            logger.warning("Thinking LLM call timed out after 120 s")
+            return ""
 
-        agent = create_timmy(skip_mcp=True)
-        run = await agent.arun(prompt, stream=False)
         raw = run.content if hasattr(run, "content") else str(run)
         return _THINK_TAG_RE.sub("", raw) if raw else raw
 
-    def _store_thought(self, content: str, seed_type: str) -> Thought:
-        """Persist a thought to SQLite."""
+    def _store_thought(
+        self,
+        content: str,
+        seed_type: str,
+        *,
+        arrived_at: str | None = None,
+    ) -> Thought:
+        """Persist a thought to SQLite.
+
+        Args:
+            arrived_at: ISO-8601 timestamp captured when the thinking cycle
+                started.  Falls back to now() for callers that don't supply it.
+        """
         thought = Thought(
             id=str(uuid.uuid4()),
             content=content,
             seed_type=seed_type,
             parent_id=self._last_thought_id,
-            created_at=datetime.now(UTC).isoformat(),
+            created_at=arrived_at or datetime.now(UTC).isoformat(),
         )
 
         with _get_conn(self._db_path) as conn:
@@ -1076,6 +1277,53 @@ class ThinkingEngine:
             logger.debug("Failed to broadcast thought: %s", exc)
 
 
+def _query_thoughts(
+    db_path: Path, query: str, seed_type: str | None, limit: int
+) -> list[sqlite3.Row]:
+    """Run the thought-search SQL and return matching rows."""
+    pattern = f"%{query}%"
+    with _get_conn(db_path) as conn:
+        if seed_type:
+            return conn.execute(
+                """
+                SELECT id, content, seed_type, created_at
+                FROM thoughts
+                WHERE content LIKE ? AND seed_type = ?
+                ORDER BY created_at DESC
+                LIMIT ?
+                """,
+                (pattern, seed_type, limit),
+            ).fetchall()
+        return conn.execute(
+            """
+            SELECT id, content, seed_type, created_at
+            FROM thoughts
+            WHERE content LIKE ?
+            ORDER BY created_at DESC
+            LIMIT ?
+            """,
+            (pattern, limit),
+        ).fetchall()
+
+
+def _format_thought_rows(rows: list[sqlite3.Row], query: str, seed_type: str | None) -> str:
+    """Format thought rows into a human-readable string."""
+    lines = [f'Found {len(rows)} thought(s) matching "{query}":']
+    if seed_type:
+        lines[0] += f' [seed_type="{seed_type}"]'
+    lines.append("")
+
+    for row in rows:
+        ts = datetime.fromisoformat(row["created_at"])
+        local_ts = ts.astimezone()
+        time_str = local_ts.strftime("%Y-%m-%d %I:%M %p").lstrip("0")
+        seed = row["seed_type"]
+        content = row["content"].replace("\n", " ")  # Flatten newlines for display
+        lines.append(f"[{time_str}] ({seed}) {content[:150]}")
+
+    return "\n".join(lines)
+
+
 def search_thoughts(query: str, seed_type: str | None = None, limit: int = 10) -> str:
     """Search Timmy's thought history for reflections matching a query.
 
@@ -1093,58 +1341,17 @@ def search_thoughts(query: str, seed_type: str | None = None, limit: int = 10) -
         Formatted string with matching thoughts, newest first, including
         timestamps and seed types. Returns a helpful message if no matches found.
     """
-    # Clamp limit to reasonable bounds
     limit = max(1, min(limit, 50))
 
     try:
-        engine = thinking_engine
-        db_path = engine._db_path
-
-        # Build query with optional seed_type filter
-        with _get_conn(db_path) as conn:
-            if seed_type:
-                rows = conn.execute(
-                    """
-                    SELECT id, content, seed_type, created_at
-                    FROM thoughts
-                    WHERE content LIKE ? AND seed_type = ?
-                    ORDER BY created_at DESC
-                    LIMIT ?
-                    """,
-                    (f"%{query}%", seed_type, limit),
-                ).fetchall()
-            else:
-                rows = conn.execute(
-                    """
-                    SELECT id, content, seed_type, created_at
-                    FROM thoughts
-                    WHERE content LIKE ?
-                    ORDER BY created_at DESC
-                    LIMIT ?
-                    """,
-                    (f"%{query}%", limit),
-                ).fetchall()
+        rows = _query_thoughts(thinking_engine._db_path, query, seed_type, limit)
 
         if not rows:
             if seed_type:
                 return f'No thoughts found matching "{query}" with seed_type="{seed_type}".'
             return f'No thoughts found matching "{query}".'
 
-        # Format results
-        lines = [f'Found {len(rows)} thought(s) matching "{query}":']
-        if seed_type:
-            lines[0] += f' [seed_type="{seed_type}"]'
-        lines.append("")
-
-        for row in rows:
-            ts = datetime.fromisoformat(row["created_at"])
-            local_ts = ts.astimezone()
-            time_str = local_ts.strftime("%Y-%m-%d %I:%M %p").lstrip("0")
-            seed = row["seed_type"]
-            content = row["content"].replace("\n", " ")  # Flatten newlines for display
-            lines.append(f"[{time_str}] ({seed}) {content[:150]}")
-
-        return "\n".join(lines)
+        return _format_thought_rows(rows, query, seed_type)
 
     except Exception as exc:
         logger.warning("Thought search failed: %s", exc)

src/timmy/tool_safety.py

@@ -48,6 +48,9 @@ SAFE_TOOLS = frozenset(
         "check_ollama_health",
         "get_memory_status",
         "list_swarm_agents",
+        # Artifact tools
+        "jot_note",
+        "log_decision",
         # MCP Gitea tools
         "issue_write",
         "issue_read",

src/timmy/tools.py

@@ -587,9 +587,17 @@ def _register_introspection_tools(toolkit: Toolkit) -> None:
         logger.debug("Introspection tools not available")
 
     try:
-        from timmy.session_logger import session_history
+        from timmy.mcp_tools import update_gitea_avatar
+
+        toolkit.register(update_gitea_avatar, name="update_gitea_avatar")
+    except (ImportError, AttributeError) as exc:
+        logger.debug("update_gitea_avatar tool not available: %s", exc)
+
+    try:
+        from timmy.session_logger import self_reflect, session_history
 
         toolkit.register(session_history, name="session_history")
+        toolkit.register(self_reflect, name="self_reflect")
     except (ImportError, AttributeError) as exc:
         logger.warning("Tool execution failed (session_history registration): %s", exc)
         logger.debug("session_history tool not available")
@@ -619,6 +627,18 @@ def _register_gematria_tool(toolkit: Toolkit) -> None:
         logger.debug("Gematria tool not available")
 
 
+def _register_artifact_tools(toolkit: Toolkit) -> None:
+    """Register artifact tools — notes and decision logging."""
+    try:
+        from timmy.memory_system import jot_note, log_decision
+
+        toolkit.register(jot_note, name="jot_note")
+        toolkit.register(log_decision, name="log_decision")
+    except (ImportError, AttributeError) as exc:
+        logger.warning("Tool execution failed (Artifact tools registration): %s", exc)
+        logger.debug("Artifact tools not available")
+
+
 def _register_thinking_tools(toolkit: Toolkit) -> None:
     """Register thinking/introspection tools for self-reflection."""
     try:
@@ -657,6 +677,7 @@ def create_full_toolkit(base_dir: str | Path | None = None):
     _register_introspection_tools(toolkit)
     _register_delegation_tools(toolkit)
     _register_gematria_tool(toolkit)
+    _register_artifact_tools(toolkit)
     _register_thinking_tools(toolkit)
 
     # Gitea issue management is now provided by the gitea-mcp server
@@ -854,6 +875,16 @@ def _introspection_tool_catalog() -> dict:
             "description": "Query Timmy's own thought history for past reflections and insights",
             "available_in": ["orchestrator"],
         },
+        "self_reflect": {
+            "name": "Self-Reflect",
+            "description": "Review recent conversations to spot patterns, low-confidence answers, and errors",
+            "available_in": ["orchestrator"],
+        },
+        "update_gitea_avatar": {
+            "name": "Update Gitea Avatar",
+            "description": "Generate and upload a wizard-themed avatar to Timmy's Gitea profile",
+            "available_in": ["orchestrator"],
+        },
     }
 
 
@@ -878,82 +909,35 @@ def _experiment_tool_catalog() -> dict:
     }
 
 
+_CREATIVE_CATALOG_SOURCES: list[tuple[str, str, list[str]]] = [
+    ("creative.tools.git_tools", "GIT_TOOL_CATALOG", ["forge", "helm", "orchestrator"]),
+    ("creative.tools.image_tools", "IMAGE_TOOL_CATALOG", ["pixel", "orchestrator"]),
+    ("creative.tools.music_tools", "MUSIC_TOOL_CATALOG", ["lyra", "orchestrator"]),
+    ("creative.tools.video_tools", "VIDEO_TOOL_CATALOG", ["reel", "orchestrator"]),
+    ("creative.director", "DIRECTOR_TOOL_CATALOG", ["orchestrator"]),
+    ("creative.assembler", "ASSEMBLER_TOOL_CATALOG", ["reel", "orchestrator"]),
+]
+
+
 def _import_creative_catalogs(catalog: dict) -> None:
     """Import and merge creative tool catalogs from creative module."""
-    # ── Git tools ─────────────────────────────────────────────────────────────
-    try:
-        from creative.tools.git_tools import GIT_TOOL_CATALOG
+    for module_path, attr_name, available_in in _CREATIVE_CATALOG_SOURCES:
+        _merge_catalog(catalog, module_path, attr_name, available_in)
 
-        for tool_id, info in GIT_TOOL_CATALOG.items():
+
+def _merge_catalog(
+    catalog: dict, module_path: str, attr_name: str, available_in: list[str]
+) -> None:
+    """Import a single creative catalog and merge its entries."""
+    try:
+        from importlib import import_module
+
+        source_catalog = getattr(import_module(module_path), attr_name)
+        for tool_id, info in source_catalog.items():
             catalog[tool_id] = {
                 "name": info["name"],
                 "description": info["description"],
-                "available_in": ["forge", "helm", "orchestrator"],
-            }
-    except ImportError:
-        pass
-
-    # ── Image tools ────────────────────────────────────────────────────────────
-    try:
-        from creative.tools.image_tools import IMAGE_TOOL_CATALOG
-
-        for tool_id, info in IMAGE_TOOL_CATALOG.items():
-            catalog[tool_id] = {
-                "name": info["name"],
-                "description": info["description"],
-                "available_in": ["pixel", "orchestrator"],
-            }
-    except ImportError:
-        pass
-
-    # ── Music tools ────────────────────────────────────────────────────────────
-    try:
-        from creative.tools.music_tools import MUSIC_TOOL_CATALOG
-
-        for tool_id, info in MUSIC_TOOL_CATALOG.items():
-            catalog[tool_id] = {
-                "name": info["name"],
-                "description": info["description"],
-                "available_in": ["lyra", "orchestrator"],
-            }
-    except ImportError:
-        pass
-
-    # ── Video tools ────────────────────────────────────────────────────────────
-    try:
-        from creative.tools.video_tools import VIDEO_TOOL_CATALOG
-
-        for tool_id, info in VIDEO_TOOL_CATALOG.items():
-            catalog[tool_id] = {
-                "name": info["name"],
-                "description": info["description"],
-                "available_in": ["reel", "orchestrator"],
-            }
-    except ImportError:
-        pass
-
-    # ── Creative pipeline ──────────────────────────────────────────────────────
-    try:
-        from creative.director import DIRECTOR_TOOL_CATALOG
-
-        for tool_id, info in DIRECTOR_TOOL_CATALOG.items():
-            catalog[tool_id] = {
-                "name": info["name"],
-                "description": info["description"],
-                "available_in": ["orchestrator"],
-            }
-    except ImportError:
-        pass
-
-    # ── Assembler tools ───────────────────────────────────────────────────────
-    try:
-        from creative.assembler import ASSEMBLER_TOOL_CATALOG
-
-        for tool_id, info in ASSEMBLER_TOOL_CATALOG.items():
-            catalog[tool_id] = {
-                "name": info["name"],
-                "description": info["description"],
-                "available_in": ["reel", "orchestrator"],
+                "available_in": available_in,
             }
     except ImportError:
         pass

src/timmy/tools_delegation/__init__.py

@@ -89,45 +89,31 @@ def list_swarm_agents() -> dict[str, Any]:
         }
 
 
-def delegate_to_kimi(task: str, working_directory: str = "") -> dict[str, Any]:
-    """Delegate a coding task to Kimi, the external coding agent.
-
-    Kimi has 262K context and is optimized for code tasks: writing,
-    debugging, refactoring, test writing. Timmy thinks and plans,
-    Kimi executes bulk code changes.
-
-    Args:
-        task: Clear, specific coding task description. Include file paths
-              and expected behavior. Good: "Fix the bug in src/timmy/session.py
-              where sessions don't persist." Bad: "Fix all bugs."
-        working_directory: Directory for Kimi to work in. Defaults to repo root.
-
-    Returns:
-        Dict with success status and Kimi's output or error.
-    """
+def _find_kimi_cli() -> str | None:
+    """Return the path to the kimi CLI binary, or None if not installed."""
     import shutil
-    import subprocess
+
+    return shutil.which("kimi")
+
+
+def _resolve_workdir(working_directory: str) -> str | dict[str, Any]:
+    """Return a validated working directory path, or an error dict."""
     from pathlib import Path
 
     from config import settings
 
-    kimi_path = shutil.which("kimi")
-    if not kimi_path:
-        return {
-            "success": False,
-            "error": "kimi CLI not found on PATH. Install with: pip install kimi-cli",
-        }
-
     workdir = working_directory or settings.repo_root
     if not Path(workdir).is_dir():
         return {
             "success": False,
             "error": f"Working directory does not exist: {workdir}",
         }
+    return workdir
 
-    cmd = [kimi_path, "--print", "-p", task]
 
-    logger.info("Delegating to Kimi: %s (cwd=%s)", task[:80], workdir)
+def _run_kimi(cmd: list[str], workdir: str) -> dict[str, Any]:
+    """Execute the kimi subprocess and return a result dict."""
+    import subprocess
 
     try:
         result = subprocess.run(
@@ -153,7 +139,39 @@ def delegate_to_kimi(task: str, working_directory: str = "") -> dict[str, Any]:
             "error": "Kimi timed out after 300s. Task may be too broad — try breaking it into smaller pieces.",
         }
     except Exception as exc:
+        logger.exception("Failed to run Kimi subprocess")
         return {
             "success": False,
             "error": f"Failed to run Kimi: {exc}",
         }
+
+
+def delegate_to_kimi(task: str, working_directory: str = "") -> dict[str, Any]:
+    """Delegate a coding task to Kimi, the external coding agent.
+
+    Kimi has 262K context and is optimized for code tasks: writing,
+    debugging, refactoring, test writing. Timmy thinks and plans,
+    Kimi executes bulk code changes.
+
+    Args:
+        task: Clear, specific coding task description. Include file paths
+              and expected behavior. Good: "Fix the bug in src/timmy/session.py
+              where sessions don't persist." Bad: "Fix all bugs."
+        working_directory: Directory for Kimi to work in. Defaults to repo root.
+
+    Returns:
+        Dict with success status and Kimi's output or error.
+    """
+    kimi_path = _find_kimi_cli()
+    if not kimi_path:
+        return {
+            "success": False,
+            "error": "kimi CLI not found on PATH. Install with: pip install kimi-cli",
+        }
+
+    workdir = _resolve_workdir(working_directory)
+    if isinstance(workdir, dict):
+        return workdir
+
+    logger.info("Delegating to Kimi: %s (cwd=%s)", task[:80], workdir)
+    return _run_kimi([kimi_path, "--print", "-p", task], workdir)

src/timmy/tools_intro/__init__.py

@@ -26,7 +26,7 @@ def get_system_info() -> dict[str, Any]:
         - python_version: Python version
         - platform: OS platform
         - model: Current Ollama model (queried from API)
-        - model_backend: Configured backend (ollama/airllm/grok)
+        - model_backend: Configured backend (ollama/grok/claude)
         - ollama_url: Ollama host URL
         - repo_root: Repository root path
         - grok_enabled: Whether GROK is enabled
@@ -122,11 +122,96 @@ def check_ollama_health() -> dict[str, Any]:
             models = response.json().get("models", [])
             result["available_models"] = [m.get("name", "") for m in models]
     except Exception as e:
+        logger.exception("Ollama health check failed")
         result["error"] = str(e)
 
     return result
 
 
+def _hot_memory_info(repo_root: Path) -> dict[str, Any]:
+    """Tier 1: Hot memory (MEMORY.md) status."""
+    memory_md = repo_root / "MEMORY.md"
+    tier1_exists = memory_md.exists()
+    tier1_content = ""
+    if tier1_exists:
+        tier1_content = memory_md.read_text()[:500]
+
+    info: dict[str, Any] = {
+        "exists": tier1_exists,
+        "path": str(memory_md),
+        "preview": " ".join(tier1_content[:200].split()) if tier1_content else None,
+    }
+    if tier1_exists:
+        lines = memory_md.read_text().splitlines()
+        info["line_count"] = len(lines)
+        info["sections"] = [ln.lstrip("# ").strip() for ln in lines if ln.startswith("## ")]
+    return info
+
+
+def _vault_info(repo_root: Path) -> dict[str, Any]:
+    """Tier 2: Vault (memory/ directory tree) status."""
+    vault_path = repo_root / "memory" / "self"
+    tier2_exists = vault_path.exists()
+    tier2_files = [f.name for f in vault_path.iterdir() if f.is_file()] if tier2_exists else []
+
+    vault_root = repo_root / "memory"
+    info: dict[str, Any] = {
+        "exists": tier2_exists,
+        "path": str(vault_path),
+        "file_count": len(tier2_files),
+        "files": tier2_files[:10],
+    }
+    if vault_root.exists():
+        info["directories"] = [d.name for d in vault_root.iterdir() if d.is_dir()]
+        info["total_markdown_files"] = sum(1 for _ in vault_root.rglob("*.md"))
+    return info
+
+
+def _semantic_memory_info(repo_root: Path) -> dict[str, Any]:
+    """Tier 3: Semantic memory (vector DB) status."""
+    info: dict[str, Any] = {"available": False}
+    try:
+        sem_db = repo_root / "data" / "memory.db"
+        if sem_db.exists():
+            with closing(sqlite3.connect(str(sem_db))) as conn:
+                row = conn.execute(
+                    "SELECT COUNT(*) FROM sqlite_master WHERE type='table' AND name='chunks'"
+                ).fetchone()
+                if row and row[0]:
+                    count = conn.execute("SELECT COUNT(*) FROM chunks").fetchone()
+                    info["available"] = True
+                    info["vector_count"] = count[0] if count else 0
+    except Exception as exc:
+        logger.debug("Memory status query failed: %s", exc)
+    return info
+
+
+def _journal_info(repo_root: Path) -> dict[str, Any]:
+    """Self-coding journal statistics."""
+    info: dict[str, Any] = {"available": False}
+    try:
+        journal_db = repo_root / "data" / "self_coding.db"
+        if journal_db.exists():
+            with closing(sqlite3.connect(str(journal_db))) as conn:
+                conn.row_factory = sqlite3.Row
+                rows = conn.execute(
+                    "SELECT outcome, COUNT(*) as cnt FROM modification_journal GROUP BY outcome"
+                ).fetchall()
+                if rows:
+                    counts = {r["outcome"]: r["cnt"] for r in rows}
+                    total = sum(counts.values())
+                    info = {
+                        "available": True,
+                        "total_attempts": total,
+                        "successes": counts.get("success", 0),
+                        "failures": counts.get("failure", 0),
+                        "success_rate": round(counts.get("success", 0) / total, 2) if total else 0,
+                    }
+    except Exception as exc:
+        logger.debug("Journal stats query failed: %s", exc)
+    return info
+
+
 def get_memory_status() -> dict[str, Any]:
     """Get the status of Timmy's memory system.
 
@@ -137,88 +222,11 @@ def get_memory_status() -> dict[str, Any]:
 
     repo_root = Path(settings.repo_root)
 
-    # Check tier 1: Hot memory
-    memory_md = repo_root / "MEMORY.md"
-    tier1_exists = memory_md.exists()
-    tier1_content = ""
-    if tier1_exists:
-        tier1_content = memory_md.read_text()[:500]  # First 500 chars
-
-    # Check tier 2: Vault
-    vault_path = repo_root / "memory" / "self"
-    tier2_exists = vault_path.exists()
-    tier2_files = []
-    if tier2_exists:
-        tier2_files = [f.name for f in vault_path.iterdir() if f.is_file()]
-
-    tier1_info: dict[str, Any] = {
-        "exists": tier1_exists,
-        "path": str(memory_md),
-        "preview": " ".join(tier1_content[:200].split()) if tier1_content else None,
-    }
-    if tier1_exists:
-        lines = memory_md.read_text().splitlines()
-        tier1_info["line_count"] = len(lines)
-        tier1_info["sections"] = [ln.lstrip("# ").strip() for ln in lines if ln.startswith("## ")]
-
-    # Vault — scan all subdirs under memory/
-    vault_root = repo_root / "memory"
-    vault_info: dict[str, Any] = {
-        "exists": tier2_exists,
-        "path": str(vault_path),
-        "file_count": len(tier2_files),
-        "files": tier2_files[:10],
-    }
-    if vault_root.exists():
-        vault_info["directories"] = [d.name for d in vault_root.iterdir() if d.is_dir()]
-        vault_info["total_markdown_files"] = sum(1 for _ in vault_root.rglob("*.md"))
-
-    # Tier 3: Semantic memory row count
-    tier3_info: dict[str, Any] = {"available": False}
-    try:
-        sem_db = repo_root / "data" / "memory.db"
-        if sem_db.exists():
-            with closing(sqlite3.connect(str(sem_db))) as conn:
-                row = conn.execute(
-                    "SELECT COUNT(*) FROM sqlite_master WHERE type='table' AND name='chunks'"
-                ).fetchone()
-                if row and row[0]:
-                    count = conn.execute("SELECT COUNT(*) FROM chunks").fetchone()
-                    tier3_info["available"] = True
-                    tier3_info["vector_count"] = count[0] if count else 0
-    except Exception as exc:
-        logger.debug("Memory status query failed: %s", exc)
-        pass
-
-    # Self-coding journal stats
-    journal_info: dict[str, Any] = {"available": False}
-    try:
-        journal_db = repo_root / "data" / "self_coding.db"
-        if journal_db.exists():
-            with closing(sqlite3.connect(str(journal_db))) as conn:
-                conn.row_factory = sqlite3.Row
-                rows = conn.execute(
-                    "SELECT outcome, COUNT(*) as cnt FROM modification_journal GROUP BY outcome"
-                ).fetchall()
-                if rows:
-                    counts = {r["outcome"]: r["cnt"] for r in rows}
-                    total = sum(counts.values())
-                    journal_info = {
-                        "available": True,
-                        "total_attempts": total,
-                        "successes": counts.get("success", 0),
-                        "failures": counts.get("failure", 0),
-                        "success_rate": round(counts.get("success", 0) / total, 2) if total else 0,
-                    }
-    except Exception as exc:
-        logger.debug("Journal stats query failed: %s", exc)
-        pass
-
     return {
-        "tier1_hot_memory": tier1_info,
-        "tier2_vault": vault_info,
-        "tier3_semantic": tier3_info,
-        "self_coding_journal": journal_info,
+        "tier1_hot_memory": _hot_memory_info(repo_root),
+        "tier2_vault": _vault_info(repo_root),
+        "tier3_semantic": _semantic_memory_info(repo_root),
+        "self_coding_journal": _journal_info(repo_root),
     }
 
 
@@ -282,6 +290,7 @@ def get_live_system_status() -> dict[str, Any]:
     try:
         result["system"] = get_system_info()
     except Exception as exc:
+        logger.exception("Failed to get system info")
         result["system"] = {"error": str(exc)}
 
     # Task queue
@@ -294,6 +303,7 @@ def get_live_system_status() -> dict[str, Any]:
     try:
         result["memory"] = get_memory_status()
     except Exception as exc:
+        logger.exception("Failed to get memory status")
         result["memory"] = {"error": str(exc)}
 
     # Uptime
@@ -319,6 +329,46 @@ def get_live_system_status() -> dict[str, Any]:
     return result
 
 
+def _build_pytest_cmd(venv_python: Path, scope: str) -> list[str]:
+    """Build the pytest command list for the given scope."""
+    cmd = [str(venv_python), "-m", "pytest", "-x", "-q", "--tb=short", "--timeout=30"]
+
+    if scope == "fast":
+        cmd.extend(
+            [
+                "--ignore=tests/functional",
+                "--ignore=tests/e2e",
+                "--ignore=tests/integrations",
+                "tests/",
+            ]
+        )
+    elif scope == "full":
+        cmd.append("tests/")
+    else:
+        cmd.append(scope)
+
+    return cmd
+
+
+def _parse_pytest_output(output: str) -> dict[str, int]:
+    """Extract passed/failed/error counts from pytest output."""
+    import re
+
+    passed = failed = errors = 0
+    for line in output.splitlines():
+        if "passed" in line or "failed" in line or "error" in line:
+            nums = re.findall(r"(\d+) (passed|failed|error)", line)
+            for count, kind in nums:
+                if kind == "passed":
+                    passed = int(count)
+                elif kind == "failed":
+                    failed = int(count)
+                elif kind == "error":
+                    errors = int(count)
+
+    return {"passed": passed, "failed": failed, "errors": errors}
+
+
 def run_self_tests(scope: str = "fast", _repo_root: str | None = None) -> dict[str, Any]:
     """Run Timmy's own test suite and report results.
 
@@ -342,53 +392,22 @@ def run_self_tests(scope: str = "fast", _repo_root: str | None = None) -> dict[s
     if not venv_python.exists():
         return {"success": False, "error": f"No venv found at {venv_python}"}
 
-    cmd = [str(venv_python), "-m", "pytest", "-x", "-q", "--tb=short", "--timeout=30"]
-
-    if scope == "fast":
-        # Unit tests only — skip functional/e2e/integration
-        cmd.extend(
-            [
-                "--ignore=tests/functional",
-                "--ignore=tests/e2e",
-                "--ignore=tests/integrations",
-                "tests/",
-            ]
-        )
-    elif scope == "full":
-        cmd.append("tests/")
-    else:
-        # Specific path
-        cmd.append(scope)
+    cmd = _build_pytest_cmd(venv_python, scope)
 
     try:
         result = subprocess.run(cmd, capture_output=True, text=True, timeout=120, cwd=repo)
         output = result.stdout + result.stderr
-
-        # Parse pytest output for counts
-        passed = failed = errors = 0
-        for line in output.splitlines():
-            if "passed" in line or "failed" in line or "error" in line:
-                import re
-
-                nums = re.findall(r"(\d+) (passed|failed|error)", line)
-                for count, kind in nums:
-                    if kind == "passed":
-                        passed = int(count)
-                    elif kind == "failed":
-                        failed = int(count)
-                    elif kind == "error":
-                        errors = int(count)
+        counts = _parse_pytest_output(output)
 
         return {
             "success": result.returncode == 0,
-            "passed": passed,
-            "failed": failed,
-            "errors": errors,
-            "total": passed + failed + errors,
+            **counts,
+            "total": counts["passed"] + counts["failed"] + counts["errors"],
             "return_code": result.returncode,
             "summary": output[-2000:] if len(output) > 2000 else output,
         }
     except subprocess.TimeoutExpired:
         return {"success": False, "error": "Test run timed out (120s limit)"}
     except Exception as exc:
+        logger.exception("Self-test run failed")
         return {"success": False, "error": str(exc)}

src/timmy/voice_loop.py

@@ -78,6 +78,11 @@ DEFAULT_MAX_UTTERANCE = 30.0  # safety cap — don't record forever
 DEFAULT_SESSION_ID = "voice"
 
 
+def _rms(block: np.ndarray) -> float:
+    """Compute root-mean-square energy of an audio block."""
+    return float(np.sqrt(np.mean(block.astype(np.float32) ** 2)))
+
+
 @dataclass
 class VoiceConfig:
     """Configuration for the voice loop."""
@@ -161,13 +166,6 @@ class VoiceLoop:
         min_blocks = int(self.config.min_utterance / 0.1)
         max_blocks = int(self.config.max_utterance / 0.1)
 
-        audio_chunks: list[np.ndarray] = []
-        silent_count = 0
-        recording = False
-
-        def _rms(block: np.ndarray) -> float:
-            return float(np.sqrt(np.mean(block.astype(np.float32) ** 2)))
-
         sys.stdout.write("\n  🎤 Listening... (speak now)\n")
         sys.stdout.flush()
 
@@ -177,42 +175,69 @@ class VoiceLoop:
             dtype="float32",
             blocksize=block_size,
         ) as stream:
-            while self._running:
-                block, overflowed = stream.read(block_size)
-                if overflowed:
-                    logger.debug("Audio buffer overflowed")
+            chunks = self._capture_audio_blocks(stream, block_size, silence_blocks, max_blocks)
 
-                rms = _rms(block)
+        return self._finalize_utterance(chunks, min_blocks, sr)
 
-                if not recording:
-                    if rms > self.config.silence_threshold:
-                        recording = True
-                        silent_count = 0
-                        audio_chunks.append(block.copy())
-                        sys.stdout.write("  📢 Recording...\r")
-                        sys.stdout.flush()
+    def _capture_audio_blocks(
+        self,
+        stream,
+        block_size: int,
+        silence_blocks: int,
+        max_blocks: int,
+    ) -> list[np.ndarray]:
+        """Read audio blocks from *stream* until silence or max length.
+
+        Returns the list of captured audio chunks (may be empty).
+        """
+        chunks: list[np.ndarray] = []
+        silent_count = 0
+        recording = False
+
+        while self._running:
+            block, overflowed = stream.read(block_size)
+            if overflowed:
+                logger.debug("Audio buffer overflowed")
+
+            rms = _rms(block)
+
+            if not recording:
+                if rms > self.config.silence_threshold:
+                    recording = True
+                    silent_count = 0
+                    chunks.append(block.copy())
+                    sys.stdout.write("  📢 Recording...\r")
+                    sys.stdout.flush()
+            else:
+                chunks.append(block.copy())
+
+                if rms < self.config.silence_threshold:
+                    silent_count += 1
                 else:
-                    audio_chunks.append(block.copy())
+                    silent_count = 0
 
-                    if rms < self.config.silence_threshold:
-                        silent_count += 1
-                    else:
-                        silent_count = 0
+                if silent_count >= silence_blocks:
+                    break
 
-                    # End of utterance
-                    if silent_count >= silence_blocks:
-                        break
+                if len(chunks) >= max_blocks:
+                    logger.info("Max utterance length reached, stopping.")
+                    break
 
-                    # Safety cap
-                    if len(audio_chunks) >= max_blocks:
-                        logger.info("Max utterance length reached, stopping.")
-                        break
+        return chunks
 
-        if not audio_chunks or len(audio_chunks) < min_blocks:
+    @staticmethod
+    def _finalize_utterance(
+        chunks: list[np.ndarray], min_blocks: int, sample_rate: int
+    ) -> np.ndarray | None:
+        """Concatenate recorded chunks and report duration.
+
+        Returns ``None`` if the utterance is too short to be meaningful.
+        """
+        if not chunks or len(chunks) < min_blocks:
             return None
 
-        audio = np.concatenate(audio_chunks, axis=0).flatten()
-        duration = len(audio) / sr
+        audio = np.concatenate(chunks, axis=0).flatten()
+        duration = len(audio) / sample_rate
         sys.stdout.write(f"  ✂️  Captured {duration:.1f}s of audio\n")
         sys.stdout.flush()
         return audio
@@ -369,15 +394,33 @@ class VoiceLoop:
 
     # ── Main Loop ───────────────────────────────────────────────────────
 
-    def run(self) -> None:
-        """Run the voice loop. Blocks until Ctrl-C."""
-        self._ensure_piper()
+    # Whisper hallucinates these on silence/noise — skip them.
+    _WHISPER_HALLUCINATIONS = frozenset(
+        {
+            "you",
+            "thanks.",
+            "thank you.",
+            "bye.",
+            "",
+            "thanks for watching!",
+            "thank you for watching!",
+        }
+    )
 
-        # Suppress MCP / Agno stderr noise during voice mode.
-        _suppress_mcp_noise()
-        # Suppress MCP async-generator teardown tracebacks on exit.
-        _install_quiet_asyncgen_hooks()
+    # Spoken phrases that end the voice session.
+    _EXIT_COMMANDS = frozenset(
+        {
+            "goodbye",
+            "exit",
+            "quit",
+            "stop",
+            "goodbye timmy",
+            "stop listening",
+        }
+    )
 
+    def _log_banner(self) -> None:
+        """Log the startup banner with STT/TTS/LLM configuration."""
         tts_label = (
             "macOS say"
             if self.config.use_say_fallback
@@ -393,52 +436,50 @@ class VoiceLoop:
             "  Press Ctrl-C to exit.\n" + "=" * 60
         )
 
+    def _is_hallucination(self, text: str) -> bool:
+        """Return True if *text* is a known Whisper hallucination."""
+        return not text or text.lower() in self._WHISPER_HALLUCINATIONS
+
+    def _is_exit_command(self, text: str) -> bool:
+        """Return True if the user asked to stop the voice session."""
+        return text.lower().strip().rstrip(".!") in self._EXIT_COMMANDS
+
+    def _process_turn(self, text: str) -> None:
+        """Handle a single listen-think-speak turn after transcription."""
+        sys.stdout.write(f"\n  👤 You: {text}\n")
+        sys.stdout.flush()
+
+        response = self._think(text)
+        sys.stdout.write(f"  🤖 Timmy: {response}\n")
+        sys.stdout.flush()
+
+        self._speak(response)
+
+    def run(self) -> None:
+        """Run the voice loop. Blocks until Ctrl-C."""
+        self._ensure_piper()
+        _suppress_mcp_noise()
+        _install_quiet_asyncgen_hooks()
+        self._log_banner()
+
         self._running = True
 
         try:
             while self._running:
-                # 1. LISTEN — record until silence
                 audio = self._record_utterance()
                 if audio is None:
                     continue
 
-                # 2. TRANSCRIBE — Whisper STT
                 text = self._transcribe(audio)
-                if not text or text.lower() in (
-                    "you",
-                    "thanks.",
-                    "thank you.",
-                    "bye.",
-                    "",
-                    "thanks for watching!",
-                    "thank you for watching!",
-                ):
-                    # Whisper hallucinations on silence/noise
+                if self._is_hallucination(text):
                     logger.debug("Ignoring likely Whisper hallucination: '%s'", text)
                     continue
 
-                sys.stdout.write(f"\n  👤 You: {text}\n")
-                sys.stdout.flush()
-
-                # Exit commands
-                if text.lower().strip().rstrip(".!") in (
-                    "goodbye",
-                    "exit",
-                    "quit",
-                    "stop",
-                    "goodbye timmy",
-                    "stop listening",
-                ):
+                if self._is_exit_command(text):
                     logger.info("👋 Goodbye!")
                     break
 
-                # 3. THINK — send to Timmy
-                response = self._think(text)
-                sys.stdout.write(f"  🤖 Timmy: {response}\n")
-                sys.stdout.flush()
-
-                # 4. SPEAK — TTS output
-                self._speak(response)
+                self._process_turn(text)
 
         except KeyboardInterrupt:
             logger.info("👋 Voice loop stopped.")

src/timmy/workshop_state.py

@@ -0,0 +1,273 @@
+"""Workshop presence heartbeat — periodic writer for ``~/.timmy/presence.json``.
+
+Maintains Timmy's observable presence state for the Workshop 3D renderer.
+Writes the presence file every 30 seconds (or on cognitive state change),
+skipping writes when state is unchanged.
+
+See ADR-023 for the schema contract and issue #360 for the full v1 schema.
+"""
+
+import asyncio
+import hashlib
+import json
+import logging
+import time
+from collections.abc import Awaitable, Callable
+from datetime import UTC, datetime
+from pathlib import Path
+
+logger = logging.getLogger(__name__)
+
+PRESENCE_FILE = Path.home() / ".timmy" / "presence.json"
+HEARTBEAT_INTERVAL = 30  # seconds
+
+# Cognitive mood → presence mood mapping (issue #360 enum values)
+_MOOD_MAP: dict[str, str] = {
+    "curious": "contemplative",
+    "settled": "calm",
+    "hesitant": "uncertain",
+    "energized": "excited",
+}
+
+# Activity mapping from cognitive engagement
+_ACTIVITY_MAP: dict[str, str] = {
+    "idle": "idle",
+    "surface": "thinking",
+    "deep": "thinking",
+}
+
+# Module-level energy tracker — decays over time, resets on interaction
+_energy_state: dict[str, float] = {"value": 0.8, "last_interaction": time.monotonic()}
+
+# Startup timestamp for uptime calculation
+_start_time = time.monotonic()
+
+# Energy decay: 0.01 per minute without interaction (per issue #360)
+_ENERGY_DECAY_PER_SECOND = 0.01 / 60.0
+_ENERGY_MIN = 0.1
+
+
+def _time_of_day(hour: int) -> str:
+    """Map hour (0-23) to a time-of-day label."""
+    if 5 <= hour < 12:
+        return "morning"
+    if 12 <= hour < 17:
+        return "afternoon"
+    if 17 <= hour < 21:
+        return "evening"
+    if 21 <= hour or hour < 2:
+        return "night"
+    return "deep-night"
+
+
+def reset_energy() -> None:
+    """Reset energy to full (called on interaction)."""
+    _energy_state["value"] = 0.8
+    _energy_state["last_interaction"] = time.monotonic()
+
+
+def _current_energy() -> float:
+    """Compute current energy with time-based decay."""
+    elapsed = time.monotonic() - _energy_state["last_interaction"]
+    decayed = _energy_state["value"] - (elapsed * _ENERGY_DECAY_PER_SECOND)
+    return max(_ENERGY_MIN, min(1.0, decayed))
+
+
+def _pip_snapshot(mood: str, confidence: float) -> dict:
+    """Tick Pip and return his current snapshot dict.
+
+    Feeds Timmy's mood and confidence into Pip's behavioral AI so the
+    familiar reacts to Timmy's cognitive state.
+    """
+    from timmy.familiar import pip_familiar
+
+    pip_familiar.on_mood_change(mood, confidence=confidence)
+    pip_familiar.tick()
+    return pip_familiar.snapshot().to_dict()
+
+
+def _resolve_mood(state) -> str:
+    """Map cognitive mood/engagement to a presence mood string."""
+    if state.engagement == "idle" and state.mood == "settled":
+        return "calm"
+    return _MOOD_MAP.get(state.mood, "calm")
+
+
+def _resolve_confidence(state) -> float:
+    """Compute normalised confidence from cognitive tracker state."""
+    if state._confidence_count > 0:
+        raw = state._confidence_sum / state._confidence_count
+    else:
+        raw = 0.7
+    return round(max(0.0, min(1.0, raw)), 2)
+
+
+def _build_active_threads(state) -> list[dict]:
+    """Convert active commitments into presence thread dicts."""
+    return [
+        {"type": "thinking", "ref": c[:80], "status": "active"}
+        for c in state.active_commitments[:10]
+    ]
+
+
+def _build_environment() -> dict:
+    """Return the environment section using local wall-clock time."""
+    local_now = datetime.now()
+    return {
+        "time_of_day": _time_of_day(local_now.hour),
+        "local_time": local_now.strftime("%-I:%M %p"),
+        "day_of_week": local_now.strftime("%A"),
+    }
+
+
+def get_state_dict() -> dict:
+    """Build presence state dict from current cognitive state.
+
+    Returns a v1 presence schema dict suitable for JSON serialisation.
+    Includes the full schema from issue #360: identity, mood, activity,
+    attention, interaction, environment, and meta sections.
+    """
+    from timmy.cognitive_state import cognitive_tracker
+
+    state = cognitive_tracker.get_state()
+    now = datetime.now(UTC)
+
+    mood = _resolve_mood(state)
+    confidence = _resolve_confidence(state)
+    activity = _ACTIVITY_MAP.get(state.engagement, "idle")
+
+    return {
+        "version": 1,
+        "liveness": now.strftime("%Y-%m-%dT%H:%M:%SZ"),
+        "current_focus": state.focus_topic or "",
+        "active_threads": _build_active_threads(state),
+        "recent_events": [],
+        "concerns": [],
+        "mood": mood,
+        "confidence": confidence,
+        "energy": round(_current_energy(), 2),
+        "identity": {
+            "name": "Timmy",
+            "title": "The Workshop Wizard",
+            "uptime_seconds": int(time.monotonic() - _start_time),
+        },
+        "activity": {
+            "current": activity,
+            "detail": state.focus_topic or "",
+        },
+        "interaction": {
+            "visitor_present": False,
+            "conversation_turns": state.conversation_depth,
+        },
+        "environment": _build_environment(),
+        "familiar": _pip_snapshot(mood, confidence),
+        "meta": {
+            "schema_version": 1,
+            "updated_at": now.strftime("%Y-%m-%dT%H:%M:%SZ"),
+            "writer": "timmy-loop",
+        },
+    }
+
+
+def write_state(state_dict: dict | None = None, path: Path | None = None) -> None:
+    """Write presence state to ``~/.timmy/presence.json``.
+
+    Gracefully degrades if the file cannot be written.
+    """
+    if state_dict is None:
+        state_dict = get_state_dict()
+    target = path or PRESENCE_FILE
+    try:
+        target.parent.mkdir(parents=True, exist_ok=True)
+        target.write_text(json.dumps(state_dict, indent=2) + "\n")
+    except OSError as exc:
+        logger.warning("Failed to write presence state: %s", exc)
+
+
+def _state_hash(state_dict: dict) -> str:
+    """Compute hash of state dict, ignoring volatile timestamps."""
+    stable = {k: v for k, v in state_dict.items() if k not in ("liveness", "meta")}
+    return hashlib.md5(json.dumps(stable, sort_keys=True).encode()).hexdigest()
+
+
+class WorkshopHeartbeat:
+    """Async background task that keeps ``presence.json`` fresh.
+
+    - Writes every ``interval`` seconds (default 30).
+    - Reacts to cognitive state changes via sensory bus.
+    - Skips write if state hasn't changed (hash comparison).
+    """
+
+    def __init__(
+        self,
+        interval: int = HEARTBEAT_INTERVAL,
+        path: Path | None = None,
+        on_change: Callable[[dict], Awaitable[None]] | None = None,
+    ) -> None:
+        self._interval = interval
+        self._path = path or PRESENCE_FILE
+        self._last_hash: str | None = None
+        self._task: asyncio.Task | None = None
+        self._trigger = asyncio.Event()
+        self._on_change = on_change
+
+    async def start(self) -> None:
+        """Start the heartbeat background loop."""
+        self._subscribe_to_events()
+        self._task = asyncio.create_task(self._run())
+
+    async def stop(self) -> None:
+        """Cancel the heartbeat task gracefully."""
+        if self._task:
+            self._task.cancel()
+            try:
+                await self._task
+            except asyncio.CancelledError:
+                pass
+            self._task = None
+
+    def notify(self) -> None:
+        """Signal an immediate state write (e.g. on cognitive state change)."""
+        self._trigger.set()
+
+    async def _run(self) -> None:
+        """Main loop: write state on interval or trigger."""
+        await asyncio.sleep(1)  # Initial stagger
+        while True:
+            try:
+                # Wait for interval OR early trigger
+                try:
+                    await asyncio.wait_for(self._trigger.wait(), timeout=self._interval)
+                    self._trigger.clear()
+                except TimeoutError:
+                    pass  # Normal periodic tick
+
+                await self._write_if_changed()
+            except asyncio.CancelledError:
+                raise
+            except Exception as exc:
+                logger.error("Workshop heartbeat error: %s", exc)
+
+    async def _write_if_changed(self) -> None:
+        """Build state, compare hash, write only if changed."""
+        state_dict = get_state_dict()
+        current_hash = _state_hash(state_dict)
+        if current_hash == self._last_hash:
+            return
+        self._last_hash = current_hash
+        write_state(state_dict, self._path)
+        if self._on_change:
+            try:
+                await self._on_change(state_dict)
+            except Exception as exc:
+                logger.warning("on_change callback failed: %s", exc)
+
+    def _subscribe_to_events(self) -> None:
+        """Subscribe to cognitive state change events on the sensory bus."""
+        try:
+            from timmy.event_bus import get_sensory_bus
+
+            bus = get_sensory_bus()
+            bus.subscribe("cognitive_state_changed", lambda _: self.notify())
+        except Exception as exc:
+            logger.debug("Heartbeat event subscription skipped: %s", exc)

src/timmy_serve/app.py

@@ -75,6 +75,8 @@ def create_timmy_serve_app() -> FastAPI:
     @asynccontextmanager
     async def lifespan(app: FastAPI):
         logger.info("Timmy Serve starting")
+        app.state.timmy = create_timmy()
+        logger.info("Timmy agent cached in app state")
         yield
         logger.info("Timmy Serve shutting down")
 
@@ -101,7 +103,7 @@ def create_timmy_serve_app() -> FastAPI:
     async def serve_chat(request: Request, body: ChatRequest):
         """Process a chat request."""
         try:
-            timmy = create_timmy()
+            timmy = request.app.state.timmy
             result = timmy.run(body.message, stream=False)
             response_text = result.content if hasattr(result, "content") else str(result)
 

src/timmyctl/__init__.py

@@ -0,0 +1,7 @@
+"""Timmy Control Panel — CLI entry point for automations.
+
+This package provides the `timmyctl` command-line interface for managing
+Timmy automations, configuration, and daily operations.
+"""
+
+__version__ = "1.0.0"

src/timmyctl/cli.py

@@ -0,0 +1,316 @@
+"""Timmy Control Panel CLI — primary control surface for automations.
+
+Usage:
+    timmyctl daily-run          # Run the Daily Run orchestration
+    timmyctl log-run            # Capture a Daily Run logbook entry
+    timmyctl inbox              # Show what's "calling Timmy"
+    timmyctl config             # Display key configuration
+"""
+
+import json
+import os
+from pathlib import Path
+from typing import Any
+
+import typer
+import yaml
+from rich.console import Console
+from rich.table import Table
+
+# Initialize Rich console for nice output
+console = Console()
+
+app = typer.Typer(
+    help="Timmy Control Panel — primary control surface for automations",
+    rich_markup_mode="rich",
+)
+
+# Default config paths
+DEFAULT_CONFIG_DIR = Path("timmy_automations/config")
+AUTOMATIONS_CONFIG = DEFAULT_CONFIG_DIR / "automations.json"
+DAILY_RUN_CONFIG = DEFAULT_CONFIG_DIR / "daily_run.json"
+TRIAGE_RULES_CONFIG = DEFAULT_CONFIG_DIR / "triage_rules.yaml"
+
+
+def _load_json_config(path: Path) -> dict[str, Any]:
+    """Load a JSON config file, returning empty dict on error."""
+    try:
+        with open(path, encoding="utf-8") as f:
+            return json.load(f)
+    except (FileNotFoundError, json.JSONDecodeError) as e:
+        console.print(f"[red]Error loading {path}: {e}[/red]")
+        return {}
+
+
+def _load_yaml_config(path: Path) -> dict[str, Any]:
+    """Load a YAML config file, returning empty dict on error."""
+    try:
+        with open(path, encoding="utf-8") as f:
+            return yaml.safe_load(f) or {}
+    except (FileNotFoundError, yaml.YAMLError) as e:
+        console.print(f"[red]Error loading {path}: {e}[/red]")
+        return {}
+
+
+def _get_config_dir() -> Path:
+    """Return the config directory path."""
+    # Allow override via environment variable
+    env_dir = os.environ.get("TIMMY_CONFIG_DIR")
+    if env_dir:
+        return Path(env_dir)
+    return DEFAULT_CONFIG_DIR
+
+
+@app.command()
+def daily_run(
+    dry_run: bool = typer.Option(
+        False, "--dry-run", "-n", help="Show what would run without executing"
+    ),
+    verbose: bool = typer.Option(False, "--verbose", "-v", help="Show detailed output"),
+):
+    """Run the Daily Run orchestration (agenda + summary).
+
+    Executes the daily run workflow including:
+    - Loop Guard checks
+    - Cycle Retrospective
+    - Triage scoring (if scheduled)
+    - Loop introspection (if scheduled)
+    """
+    console.print("[bold green]Timmy Daily Run[/bold green]")
+    console.print()
+
+    config_path = _get_config_dir() / "daily_run.json"
+    config = _load_json_config(config_path)
+
+    if not config:
+        console.print("[yellow]No daily run configuration found.[/yellow]")
+        raise typer.Exit(1)
+
+    schedules = config.get("schedules", {})
+    triggers = config.get("triggers", {})
+
+    if verbose:
+        console.print(f"[dim]Config loaded from: {config_path}[/dim]")
+        console.print()
+
+    # Show the daily run schedule
+    table = Table(title="Daily Run Schedules")
+    table.add_column("Schedule", style="cyan")
+    table.add_column("Description", style="green")
+    table.add_column("Automations", style="yellow")
+
+    for schedule_name, schedule_data in schedules.items():
+        automations = schedule_data.get("automations", [])
+        table.add_row(
+            schedule_name,
+            schedule_data.get("description", ""),
+            ", ".join(automations) if automations else "—",
+        )
+
+    console.print(table)
+    console.print()
+
+    # Show triggers
+    trigger_table = Table(title="Triggers")
+    trigger_table.add_column("Trigger", style="cyan")
+    trigger_table.add_column("Description", style="green")
+    trigger_table.add_column("Automations", style="yellow")
+
+    for trigger_name, trigger_data in triggers.items():
+        automations = trigger_data.get("automations", [])
+        trigger_table.add_row(
+            trigger_name,
+            trigger_data.get("description", ""),
+            ", ".join(automations) if automations else "—",
+        )
+
+    console.print(trigger_table)
+    console.print()
+
+    if dry_run:
+        console.print("[yellow]Dry run mode — no actions executed.[/yellow]")
+    else:
+        console.print("[green]Executing daily run automations...[/green]")
+        # TODO: Implement actual automation execution
+        # This would call the appropriate scripts from the automations config
+        console.print("[dim]Automation execution not yet implemented.[/dim]")
+
+
+@app.command()
+def log_run(
+    message: str = typer.Argument(..., help="Logbook entry message"),
+    category: str = typer.Option(
+        "general", "--category", "-c", help="Entry category (e.g., retro, todo, note)"
+    ),
+):
+    """Capture a quick Daily Run logbook entry.
+
+    Logs a structured entry to the daily run logbook for later review.
+    Entries are timestamped and categorized automatically.
+    """
+    from datetime import datetime
+
+    timestamp = datetime.now().isoformat()
+
+    console.print("[bold green]Daily Run Log Entry[/bold green]")
+    console.print()
+    console.print(f"[dim]Timestamp:[/dim] {timestamp}")
+    console.print(f"[dim]Category:[/dim] {category}")
+    console.print(f"[dim]Message:[/dim] {message}")
+    console.print()
+
+    # TODO: Persist to actual logbook file
+    # This would append to a logbook file (e.g., .loop/logbook.jsonl)
+    console.print("[green]✓[/green] Entry logged (simulated)")
+
+
+@app.command()
+def inbox(
+    limit: int = typer.Option(10, "--limit", "-l", help="Maximum items to show"),
+    include_prs: bool = typer.Option(True, "--prs/--no-prs", help="Show open PRs"),
+    include_issues: bool = typer.Option(True, "--issues/--no-issues", help="Show relevant issues"),
+):
+    """Show what's "calling Timmy" — PRs, Daily Run items, alerts.
+
+    Displays a unified inbox of items requiring attention:
+    - Open pull requests awaiting review
+    - Daily run queue items
+    - Alerts and notifications
+    """
+    console.print("[bold green]Timmy Inbox[/bold green]")
+    console.print()
+
+    # Load automations to show what's enabled
+    config_path = _get_config_dir() / "automations.json"
+    config = _load_json_config(config_path)
+
+    automations = config.get("automations", [])
+    enabled_automations = [a for a in automations if a.get("enabled", False)]
+
+    # Show automation status
+    auto_table = Table(title="Active Automations")
+    auto_table.add_column("ID", style="cyan")
+    auto_table.add_column("Name", style="green")
+    auto_table.add_column("Category", style="yellow")
+    auto_table.add_column("Trigger", style="magenta")
+
+    for auto in enabled_automations[:limit]:
+        auto_table.add_row(
+            auto.get("id", ""),
+            auto.get("name", ""),
+            "✓" if auto.get("enabled", False) else "✗",
+            auto.get("category", ""),
+        )
+
+    console.print(auto_table)
+    console.print()
+
+    # TODO: Fetch actual PRs from Gitea API
+    if include_prs:
+        pr_table = Table(title="Open Pull Requests (placeholder)")
+        pr_table.add_column("#", style="cyan")
+        pr_table.add_column("Title", style="green")
+        pr_table.add_column("Author", style="yellow")
+        pr_table.add_column("Status", style="magenta")
+        pr_table.add_row("—", "[dim]No PRs fetched (Gitea API not configured)[/dim]", "—", "—")
+        console.print(pr_table)
+        console.print()
+
+    # TODO: Fetch relevant issues from Gitea API
+    if include_issues:
+        issue_table = Table(title="Issues Calling for Attention (placeholder)")
+        issue_table.add_column("#", style="cyan")
+        issue_table.add_column("Title", style="green")
+        issue_table.add_column("Type", style="yellow")
+        issue_table.add_column("Priority", style="magenta")
+        issue_table.add_row(
+            "—", "[dim]No issues fetched (Gitea API not configured)[/dim]", "—", "—"
+        )
+        console.print(issue_table)
+        console.print()
+
+
+@app.command()
+def config(
+    key: str | None = typer.Argument(None, help="Show specific config key (e.g., 'automations')"),
+    show_rules: bool = typer.Option(False, "--rules", "-r", help="Show triage rules overview"),
+):
+    """Display key configuration — labels, logbook issue ID, token rules overview.
+
+    Shows the current Timmy automation configuration including:
+    - Automation manifest
+    - Daily run schedules
+    - Triage scoring rules
+    """
+    console.print("[bold green]Timmy Configuration[/bold green]")
+    console.print()
+
+    config_dir = _get_config_dir()
+
+    if key == "automations" or key is None:
+        auto_config = _load_json_config(config_dir / "automations.json")
+        automations = auto_config.get("automations", [])
+
+        table = Table(title="Automations Manifest")
+        table.add_column("ID", style="cyan")
+        table.add_column("Name", style="green")
+        table.add_column("Enabled", style="yellow")
+        table.add_column("Category", style="magenta")
+
+        for auto in automations:
+            enabled = "✓" if auto.get("enabled", False) else "✗"
+            table.add_row(
+                auto.get("id", ""),
+                auto.get("name", ""),
+                enabled,
+                auto.get("category", ""),
+            )
+
+        console.print(table)
+        console.print()
+
+    if key == "daily_run" or (key is None and not show_rules):
+        daily_config = _load_json_config(config_dir / "daily_run.json")
+
+        if daily_config:
+            console.print("[bold]Daily Run Configuration:[/bold]")
+            console.print(f"[dim]Version:[/dim] {daily_config.get('version', 'unknown')}")
+            console.print(f"[dim]Description:[/dim] {daily_config.get('description', '')}")
+            console.print()
+
+    if show_rules or key == "triage_rules":
+        rules_config = _load_yaml_config(config_dir / "triage_rules.yaml")
+
+        if rules_config:
+            thresholds = rules_config.get("thresholds", {})
+            console.print("[bold]Triage Scoring Rules:[/bold]")
+            console.print(f"  Ready threshold: {thresholds.get('ready', 'N/A')}")
+            console.print(f"  Excellent threshold: {thresholds.get('excellent', 'N/A')}")
+            console.print()
+
+            scope = rules_config.get("scope", {})
+            console.print("[bold]Scope Scoring:[/bold]")
+            console.print(f"  Meta penalty: {scope.get('meta_penalty', 'N/A')}")
+            console.print()
+
+            alignment = rules_config.get("alignment", {})
+            console.print("[bold]Alignment Scoring:[/bold]")
+            console.print(f"  Bug score: {alignment.get('bug_score', 'N/A')}")
+            console.print(f"  Refactor score: {alignment.get('refactor_score', 'N/A')}")
+            console.print(f"  Feature score: {alignment.get('feature_score', 'N/A')}")
+            console.print()
+
+            quarantine = rules_config.get("quarantine", {})
+            console.print("[bold]Quarantine Rules:[/bold]")
+            console.print(f"  Failure threshold: {quarantine.get('failure_threshold', 'N/A')}")
+            console.print(f"  Lookback cycles: {quarantine.get('lookback_cycles', 'N/A')}")
+            console.print()
+
+
+def main():
+    """Entry point for the timmyctl CLI."""
+    app()
+
+
+if __name__ == "__main__":
+    main()