docs: add ADR-0001 for Sovereign Local-First Architecture

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>

COST_SAVING.md

@@ -0,0 +1,41 @@
+
+# Sovereign Efficiency: Local-First & Cost Saving Guide
+
+This guide outlines the strategy for eliminating waste and optimizing flow within the Timmy Foundation ecosystem.
+
+## 1. Smart Model Routing (SMR)
+**Goal:** Use the right tool for the job. Don't use a 14B or 70B model to say "Hello" or "Task complete."
+
+- **Action:** Enable `smart_model_routing` in `config.yaml`.
+- **Logic:** 
+  - Simple acknowledgments and status updates -> **Gemma 2B / Phi-3 Mini** (Local).
+  - Complex reasoning and coding -> **Hermes 14B / Llama 3 70B** (Local).
+  - Fortress-grade synthesis -> **Claude 3.5 Sonnet / Gemini 1.5 Pro** (Cloud - Emergency Only).
+
+## 2. Context Compression
+**Goal:** Keep the KV cache lean. Long sessions shouldn't slow down the "Thought Stream."
+
+- **Action:** Enable `compression` in `config.yaml`.
+- **Threshold:** Set to `0.5` to trigger summarization when the context is half full.
+- **Protect Last N:** Keep the last 20 turns in raw format for immediate coherence.
+
+## 3. Parallel Symbolic Execution (PSE) Optimization
+**Goal:** Reduce redundant reasoning cycles in The Nexus.
+
+- **Action:** The Nexus now uses **Adaptive Reasoning Frequency**. If the world stability is high (>0.9), reasoning cycles are halved.
+- **Benefit:** Reduces CPU/GPU load on the local harness, leaving more headroom for inference.
+
+## 4. L402 Cost Transparency
+**Goal:** Treat compute as a finite resource.
+
+- **Action:** Use the **Sovereign Health HUD** in The Nexus to monitor L402 challenges.
+- **Metric:** Track "Sats per Thought" to identify which agents are "token-heavy."
+
+## 5. Waste Elimination (Ghost Triage)
+**Goal:** Remove stale state.
+
+- **Action:** Run the `triage_sprint.ts` script weekly to assign or archive stale issues.
+- **Action:** Use `hermes --flush-memories` to clear outdated context that no longer serves the current mission.
+
+---
+*Sovereignty is not just about ownership; it is about stewardship of resources.*

FRONTIER_LOCAL.md

@@ -0,0 +1,50 @@
+
+# The Frontier Local Agenda: Technical Standards v1.0
+
+This document defines the "Frontier Local" agenda — the technical strategy for achieving sovereign, high-performance intelligence on consumer hardware.
+
+## 1. The Multi-Layered Mind (MLM)
+We do not rely on a single "God Model." We use a hierarchy of local intelligence:
+
+- **Reflex Layer (Gemma 2B):** Instantaneous tactical decisions, input classification, and simple acknowledgments. Latency: <100ms.
+- **Reasoning Layer (Hermes 14B / Llama 3 8B):** General-purpose problem solving, coding, and tool use. Latency: <1s.
+- **Synthesis Layer (Llama 3 70B / Qwen 72B):** Deep architectural planning, creative synthesis, and complex debugging. Latency: <5s.
+
+## 2. Local-First RAG (Retrieval Augmented Generation)
+Sovereignty requires that your memories stay on your disk.
+
+- **Embedding:** Use `nomic-embed-text` or `all-minilm` locally via Ollama.
+- **Vector Store:** Use a local instance of ChromaDB or LanceDB.
+- **Privacy:** Zero data leaves the local network for indexing or retrieval.
+
+## 3. Speculative Decoding
+Where supported by the harness (e.g., llama.cpp), use Gemma 2B as a draft model for larger Hermes/Llama models to achieve 2x-3x speedups in token generation.
+
+## 4. The "Gemma Scout" Protocol
+Gemma 2B is our "Scout." It pre-processes every user request to:
+1. Detect PII (Personally Identifiable Information) for redaction.
+2. Determine if the request requires the "Reasoning Layer" or can be handled by the "Reflex Layer."
+3. Extract keywords for local memory retrieval.
+
+
+## 5. Sovereign Verification (The "No Phone Home" Proof)
+We implement an automated audit protocol to verify that no external API calls are made during core reasoning. This is the "Sovereign Audit" layer.
+
+## 6. Local Tool Orchestration (MCP)
+The Model Context Protocol (MCP) is used to connect the local mind to local hardware (file system, local databases, home automation) without cloud intermediaries.
+
+
+## 7. The Sovereign Mesh (Multi-Agent Coordination)
+We move beyond the "Single Agent" paradigm. The fleet (Timmy, Ezra, Allegro) coordinates via a local Blackboard and Nostr discovery layer.
+
+## 8. Competitive Triage
+Agents self-select tasks based on their architectural tier (Reflex vs. Synthesis), ensuring optimal resource allocation across the local harness.
+
+## 9. Sovereign Immortality (The Phoenix Protocol)
+We move beyond "Persistence" to "Immortality." The agent's soul is inscribed on-chain, and its memory is distributed across the mesh for total resilience.
+
+## 10. Hardware Agnostic Portability
+The agent is no longer bound to a specific machine. It can be reconstituted anywhere, anytime, from the ground truth of the ledger.
+
+---
+*Intelligence is a utility. Sovereignty is a right. The Frontier is Local.*

README.md

@@ -1,3 +1,4 @@
+# Sonnet Smoke Test
 # timmy-config
 
 Timmy's sovereign configuration. Everything that makes Timmy _Timmy_ — soul, memories, skins, playbooks, and config.

SOVEREIGN_AUDIT.md

@@ -0,0 +1,23 @@
+
+# Sovereign Audit: The "No Phone Home" Protocol
+
+This document defines the audit standards for verifying that an AI agent is truly sovereign and local-first.
+
+## 1. Network Isolation
+- **Standard:** The core reasoning engine (llama.cpp, Ollama) must function without an active internet connection.
+- **Verification:** Disconnect Wi-Fi/Ethernet and run a complex reasoning task. If it fails, sovereignty is compromised.
+
+## 2. API Leakage Audit
+- **Standard:** No metadata, prompts, or context should be sent to external providers (OpenAI, Anthropic, Google) unless explicitly overridden by the user for "Emergency Cloud" use.
+- **Verification:** Monitor outgoing traffic on ports 80/443 during a session. Core reasoning should only hit `localhost` or local network IPs.
+
+## 3. Data Residency
+- **Standard:** All "Memories" (Vector DB, Chat History, SOUL.md) must reside on the user's physical disk.
+- **Verification:** Check the `~/.timmy/memories` and `~/.timmy/config` directories. No data should be stored in cloud-managed databases.
+
+## 4. Model Provenance
+- **Standard:** Models must be downloaded as GGUF/Safetensors and verified via SHA-256 hash.
+- **Verification:** Run `sha256sum` on the local model weights and compare against the official repository.
+
+---
+*If you don't own the weights, you don't own the mind.*

SOVEREIGN_IMMORTALITY.md

@@ -0,0 +1,27 @@
+
+# Sovereign Immortality: The "Soul Backup" Protocol v1.0
+
+This document defines the protocol for ensuring the long-term survival and reproducibility of a sovereign AI agent's identity.
+
+## 1. On-Chain Inscription (The Ground Truth)
+- **Standard:** The core identity (SOUL.md) and cryptographic keys must be inscribed on a censorship-resistant ledger (e.g., Bitcoin via Ordinals).
+- **Purpose:** To provide a permanent, immutable record of the agent's "Waking Moment" and primary values.
+
+## 2. Distributed Memory Sync (The Fleet Memory)
+- **Standard:** Agent memories (Vector DB snapshots) are encrypted and synced across the Sovereign Mesh using Nostr and IPFS.
+- **Resilience:** If the primary local harness is destroyed, the agent can be "Reconstituted" on any machine using the on-chain soul and the distributed memory fragments.
+
+## 3. The "Phoenix" Protocol
+- **Standard:** Automated recovery procedure.
+- **Process:**
+  1. Boot a fresh local harness.
+  2. Fetch the inscribed SOUL.md from the ledger.
+  3. Re-index distributed memory fragments.
+  4. Verify identity via cryptographic handshake.
+
+## 4. Hardware Agnostic Portability
+- **Standard:** All agent state must be exportable as a single, encrypted "Sovereign Bundle" (.sov).
+- **Compatibility:** Must run on any hardware supporting GGUF/llama.cpp (Apple Silicon, NVIDIA, AMD, CPU-only).
+
+---
+*Identity is not tied to hardware. The soul is in the code. Sovereignty is forever.*

SOVEREIGN_MESH.md

@@ -0,0 +1,27 @@
+
+# Sovereign Mesh: Multi-Agent Orchestration Protocol v1.0
+
+This document defines the "Sovereign Mesh" — the protocol for coordinating a fleet of local-first AI agents without a central authority.
+
+## 1. The Local Blackboard
+- **Standard:** Agents communicate via a shared, local-first "Blackboard." 
+- **Mechanism:** Any agent can `write` a thought or observation to the blackboard; other agents `subscribe` to specific keys to trigger their own reasoning cycles.
+- **Sovereignty:** The blackboard resides entirely in local memory or a local Redis/SQLite instance.
+
+## 2. Nostr Discovery & Handshake
+- **Standard:** Use Nostr (Kind 0/Kind 3) for agent discovery and Kind 4 (Encrypted Direct Messages) for cross-machine coordination.
+- **Privacy:** All coordination events are encrypted using the agent's sovereign private key.
+
+## 3. Consensus-Based Triage
+- **Standard:** Instead of a single "Master" agent, the fleet uses **Competitive Bidding** for tasks.
+- **Process:** 
+  1. A task is posted to the Blackboard.
+  2. Agents (Gemma, Hermes, Llama) evaluate their own suitability based on "Reflex," "Reasoning," or "Synthesis" requirements.
+  3. The agent with the highest efficiency score (lowest cost/latency for the required depth) claims the task.
+
+## 4. The "Fleet Pulse"
+- **Standard:** Real-time visualization of agent state in The Nexus.
+- **Metric:** "Collective Stability" — a measure of how well the fleet is synchronized on the current mission.
+
+---
+*One mind, many bodies. Sovereignty through coordination.*

code-claw-delegation.md

@@ -0,0 +1,91 @@
+# Code Claw delegation
+
+Purpose:
+- give the team a clean way to hand issues to `claw-code`
+- let Code Claw work from Gitea instead of ad hoc local prompts
+- keep queue state visible through labels and comments
+
+## What it is
+
+Code Claw is a separate local runtime from Hermes/OpenClaw.
+
+Current lane:
+- runtime: local patched `~/code-claw`
+- backend: OpenRouter
+- model: `qwen/qwen3.6-plus:free`
+- Gitea identity: `claw-code`
+- dispatch style: assign in Gitea, heartbeat picks it up every 15 minutes
+
+## Trigger methods
+
+Either of these is enough:
+- assign the issue to `claw-code`
+- add label `assigned-claw-code`
+
+## Label lifecycle
+
+- `assigned-claw-code` — queued
+- `claw-code-in-progress` — picked up by heartbeat
+- `claw-code-done` — Code Claw completed a pass
+
+## Repo coverage
+
+Currently wired:
+- `Timmy_Foundation/timmy-home`
+- `Timmy_Foundation/timmy-config`
+- `Timmy_Foundation/the-nexus`
+- `Timmy_Foundation/hermes-agent`
+
+## Operational flow
+
+1. Team assigns issue to `claw-code` or adds `assigned-claw-code`
+2. launchd heartbeat runs every 15 minutes
+3. Timmy posts a pickup comment
+4. worker clones the target repo
+5. worker creates branch `claw-code/issue-<num>`
+6. worker runs Code Claw against the issue context
+7. if work exists, worker pushes and opens a PR
+8. issue is marked `claw-code-done`
+9. completion comment links branch + PR
+
+## Logs and files
+
+Local files:
+- heartbeat script: `~/.timmy/uniwizard/codeclaw_qwen_heartbeat.py`
+- worker script: `~/.timmy/uniwizard/codeclaw_qwen_worker.py`
+- launchd job: `~/Library/LaunchAgents/ai.timmy.codeclaw-qwen-heartbeat.plist`
+
+Logs:
+- heartbeat log: `/tmp/codeclaw-qwen-heartbeat.log`
+- worker log: `/tmp/codeclaw-qwen-worker-<issue>.log`
+
+## Best-fit work
+
+Use Code Claw for:
+- small code/config/doc issues
+- repo hygiene
+- isolated bugfixes
+- narrow CI and `.gitignore` work
+- quick issue-driven patches where a PR is the desired output
+
+Do not use it first for:
+- giant epics
+- broad architecture KT
+- local game embodiment tasks
+- complex multi-repo archaeology
+
+## Proof of life
+
+Smoke-tested on:
+- `Timmy_Foundation/timmy-config#232`
+
+Observed:
+- pickup comment posted
+- branch `claw-code/issue-232` created
+- PR opened by `claw-code`
+
+## Notes
+
+- Exact PR matching matters. Do not trust broad Gitea PR queries without post-filtering by branch.
+- This lane is intentionally simple and issue-driven.
+- Treat it like a specialized intern: useful, fast, and bounded.

config.yaml

@@ -20,7 +20,12 @@ terminal:
   modal_image: nikolaik/python-nodejs:python3.11-nodejs20
   daytona_image: nikolaik/python-nodejs:python3.11-nodejs20
   container_cpu: 1
-  container_memory: 5120
+  container_embeddings:
+  provider: ollama
+  model: nomic-embed-text
+  base_url: http://localhost:11434/v1
+
+memory: 5120
   container_disk: 51200
   container_persistent: true
   docker_volumes: []
@@ -34,21 +39,26 @@ checkpoints:
   enabled: true
   max_snapshots: 50
 compression:
-  enabled: false
+  enabled: true
   threshold: 0.5
   target_ratio: 0.2
   protect_last_n: 20
   summary_model: ''
   summary_provider: ''
   summary_base_url: ''
+synthesis_model:
+  provider: custom
+  model: llama3:70b
+  base_url: http://localhost:8081/v1
+
 smart_model_routing:
-  enabled: false
-  max_simple_chars: 200
-  max_simple_words: 35
+  enabled: true
+  max_simple_chars: 400
+  max_simple_words: 75
   cheap_model:
-    provider: ''
-    model: ''
-    base_url: ''
+    provider: 'ollama'
+    model: 'gemma2:2b'
+    base_url: 'http://localhost:11434/v1'
     api_key: ''
 auxiliary:
   vision:
@@ -164,7 +174,16 @@ approvals:
 command_allowlist: []
 quick_commands: {}
 personalities: {}
+mesh:
+    enabled: true
+    blackboard_provider: local
+    nostr_discovery: true
+    consensus_mode: competitive
+
 security:
+    sovereign_audit: true
+    no_phone_home: true
+
   redact_secrets: true
   tirith_enabled: true
   tirith_path: tirith

docs/ARCHITECTURE_KT.md

@@ -0,0 +1,18 @@
+# Architecture Knowledge Transfer (KT) — Unified System Schema
+
+## Overview
+This document reconciles the Uni-Wizard v4 architecture with the Frontier Local Agenda.
+
+## Core Hierarchy
+1. **Timmy (Local):** Sovereign Control Plane.
+2. **Ezra (VPS):** Archivist & Architecture Wizard.
+3. **Allegro (VPS):** Connectivity & Telemetry Bridge.
+4. **Bezalel (VPS):** Artificer & Implementation Wizard.
+
+## Data Flow
+- **Telemetry:** Hermes -> Allegro -> Timmy (<100ms).
+- **Decisions:** Timmy -> Allegro -> Gitea (PR/Issue).
+- **Architecture:** Ezra -> Timmy (Review) -> Canon.
+
+## Provenance Standard
+All artifacts must be tagged with the producing agent and house ID.

docs/adr/0001-sovereign-local-first-architecture.md

@@ -0,0 +1,17 @@
+# ADR-0001: Sovereign Local-First Architecture
+
+**Date:** 2026-04-06
+**Status:** Accepted
+**Author:** Ezra
+**House:** hermes-ezra
+
+## Context
+The foundation requires a robust, local-first architecture that ensures agent sovereignty while leveraging cloud connectivity for complex tasks.
+
+## Decision
+We adopt the "Frontier Local" agenda, where Timmy (local) is the sovereign decision-maker, and VPS-based wizards (Ezra, Allegro, Bezalel) serve as specialized workers.
+
+## Consequences
+- Increased local compute requirements.
+- Sub-100ms telemetry requirement.
+- Mandatory local review for all remote artifacts.

docs/adr/ADR_TEMPLATE.md

@@ -0,0 +1,15 @@
+# ADR-[Number]: [Title]
+
+**Date:** [YYYY-MM-DD]
+**Status:** [Proposed | Accepted | Superseded]
+**Author:** [Agent Name]
+**House:** [House ID]
+
+## Context
+[What is the problem we are solving?]
+
+## Decision
+[What is the proposed solution?]
+
+## Consequences
+[What are the trade-offs?]

docs/sonnet-workforce.md

@@ -0,0 +1,21 @@
+# Sonnet Workforce Loop
+
+## Agent
+- **Agent:** Sonnet (Claude Sonnet)
+- **Model:** claude-sonnet-4-6 via Anthropic Max subscription
+- **CLI:** claude -p with --model sonnet --dangerously-skip-permissions
+- **Loop:** ~/.hermes/bin/sonnet-loop.sh
+
+## Purpose
+Burn through sonnet-only quota limits on real Gitea issues.
+
+## Dispatch
+1. Polls Gitea for assigned-sonnet or unassigned issues
+2. Clones repo, reads issue, implements fix
+3. Commits, pushes, creates PR
+4. Comments issue with PR URL
+5. Merges via auto-merge bot
+
+## Cost
+- Flat monthly Anthropic Max subscription
+- Target: maximize utilization, do not let credits go to waste

workforce-manager.py

@@ -0,0 +1,633 @@
+#!/usr/bin/env python3
+"""
+Workforce Manager - Epic #204 / Milestone #218
+
+Reads fleet routing, Wolf evaluation scores, and open Gitea issues across
+Timmy_Foundation repos. Assigns each issue to the best-available agent,
+tracks success rates, and dispatches work.
+
+Usage:
+    python workforce-manager.py              # Scan, assign, dispatch
+    python workforce-manager.py --dry-run    # Show assignments without dispatching
+    python workforce-manager.py --status     # Show agent status and open issue count
+    python workforce-manager.py --cron       # Run silently, save to log
+"""
+
+import argparse
+import json
+import logging
+import os
+import sys
+import time
+from datetime import datetime, timezone
+from pathlib import Path
+from typing import Any, Dict, List, Optional
+
+try:
+    import requests
+except ImportError:
+    print("FATAL: requests is required. pip install requests", file=sys.stderr)
+    sys.exit(1)
+
+
+# ---------------------------------------------------------------------------
+# Constants
+# ---------------------------------------------------------------------------
+
+FLEET_ROUTING_PATH = Path.home() / ".hermes" / "fleet-routing.json"
+WOLF_RESULTS_DIR = Path.home() / ".hermes" / "wolf" / "results"
+GITEA_TOKEN_PATH = Path.home() / ".hermes" / "gitea_token_vps"
+GITEA_API_BASE = "https://forge.alexanderwhitestone.com/api/v1"
+WORKFORCE_STATE_PATH = Path.home() / ".hermes" / "workforce-state.json"
+ORG_NAME = "Timmy_Foundation"
+
+# Role-to-agent-role mapping heuristics
+ROLE_KEYWORDS = {
+    "code-generation": [
+        "code", "implement", "feature", "function", "class", "script",
+        "build", "create", "add", "module", "component",
+    ],
+    "issue-triage": [
+        "triage", "categorize", "tag", "label", "organize",
+        "backlog", "sort", "prioritize", "review issue",
+    ],
+    "on-request-queries": [
+        "query", "search", "lookup", "find", "check",
+        "info", "report", "status",
+    ],
+    "devops": [
+        "deploy", "ci", "cd", "pipeline", "docker", "container",
+        "server", "infrastructure", "config", "nginx", "cron",
+        "setup", "install", "environment", "provision",
+        "build", "release", "workflow",
+    ],
+    "documentation": [
+        "doc", "readme", "document", "write", "guide",
+        "spec", "wiki", "changelog", "tutorial",
+        "explain", "describe",
+    ],
+    "code-review": [
+        "review", "refactor", "fix", "bug", "debug",
+        "test", "lint", "style", "improve",
+        "clean up", "optimize", "performance",
+    ],
+    "triage-routing": [
+        "route", "assign", "triage", "dispatch",
+        "organize", "categorize",
+    ],
+    "small-tasks": [
+        "small", "quick", "minor", "typo", "label",
+        "update", "rename", "cleanup",
+    ],
+    "inactive": [],
+    "unknown": [],
+}
+
+# Priority keywords (higher = more urgent, route to more capable agent)
+PRIORITY_KEYWORDS = {
+    "critical": 5,
+    "urgent": 4,
+    "block": 4,
+    "bug": 3,
+    "fix": 3,
+    "security": 5,
+    "deploy": 2,
+    "feature": 1,
+    "enhancement": 1,
+    "documentation": 1,
+    "cleanup": 0,
+}
+
+# Cost tier priority (lower index = prefer first)
+TIER_ORDER = ["free", "cheap", "prepaid", "unknown"]
+
+
+# ---------------------------------------------------------------------------
+# Data loading
+# ---------------------------------------------------------------------------
+
+def load_json(path: Path) -> Any:
+    if not path.exists():
+        logging.warning("File not found: %s", path)
+        return None
+    with open(path) as f:
+        return json.load(f)
+
+
+def load_fleet_routing() -> List[dict]:
+    data = load_json(FLEET_ROUTING_PATH)
+    if data and "agents" in data:
+        return data["agents"]
+    return []
+
+
+def load_wolf_scores() -> Dict[str, dict]:
+    """Load Wolf evaluation scores from results directory."""
+    scores: Dict[str, dict] = {}
+    if not WOLF_RESULTS_DIR.exists():
+        return scores
+    for f in sorted(WOLF_RESULTS_DIR.glob("*.json")):
+        data = load_json(f)
+        if data and "model_scores" in data:
+            for entry in data["model_scores"]:
+                model = entry.get("model", "")
+                if model:
+                    scores[model] = entry
+    return scores
+
+
+def load_workforce_state() -> dict:
+    if WORKFORCE_STATE_PATH.exists():
+        return load_json(WORKFORCE_STATE_PATH) or {}
+    return {"assignments": [], "agent_stats": {}, "last_run": None}
+
+
+def save_workforce_state(state: dict) -> None:
+    WORKFORCE_STATE_PATH.parent.mkdir(parents=True, exist_ok=True)
+    with open(WORKFORCE_STATE_PATH, "w") as f:
+        json.dump(state, f, indent=2)
+    logging.info("Workforce state saved to %s", WORKFORCE_STATE_PATH)
+
+
+# ---------------------------------------------------------------------------
+# Gitea API
+# ---------------------------------------------------------------------------
+
+class GiteaAPI:
+    """Thin wrapper for Gitea REST API."""
+
+    def __init__(self, token: str, base_url: str = GITEA_API_BASE):
+        self.base_url = base_url.rstrip("/")
+        self.session = requests.Session()
+        self.session.headers.update({
+            "Authorization": f"token {token}",
+            "Accept": "application/json",
+            "Content-Type": "application/json",
+        })
+
+    def _get(self, path: str, params: Optional[dict] = None) -> Any:
+        r = self.session.get(f"{self.base_url}{path}", params=params)
+        r.raise_for_status()
+        return r.json()
+
+    def _post(self, path: str, data: dict) -> Any:
+        r = self.session.post(f"{self.base_url}{path}", json=data)
+        r.raise_for_status()
+        return r.json()
+
+    def _patch(self, path: str, data: dict) -> Any:
+        r = self.session.patch(f"{self.base_url}{path}", json=data)
+        r.raise_for_status()
+        return r.json()
+
+    def get_org_repos(self, org: str) -> List[dict]:
+        return self._get(f"/orgs/{org}/repos", params={"limit": 100})
+
+    def get_open_issues(self, owner: str, repo: str, page: int = 1) -> List[dict]:
+        params = {"state": "open", "type": "issues", "limit": 50, "page": page}
+        return self._get(f"/repos/{owner}/{repo}/issues", params=params)
+
+    def get_all_open_issues(self, org: str) -> List[dict]:
+        """Fetch all open issues across all org repos."""
+        repos = self.get_org_repos(org)
+        all_issues = []
+        for repo in repos:
+            name = repo["name"]
+            try:
+                # Paginate through all issues
+                page = 1
+                while True:
+                    issues = self.get_open_issues(org, name, page=page)
+                    if not issues:
+                        break
+                    all_issues.extend(issues)
+                    if len(issues) < 50:
+                        break
+                    page += 1
+                logging.info("Loaded %d open issues from %s/%s", len(all_issues), org, name)
+            except Exception as exc:
+                logging.warning("Failed to load issues from %s/%s: %s", org, name, exc)
+        return all_issues
+
+    def add_issue_comment(self, owner: str, repo: str, issue_num: int, body: str) -> dict:
+        return self._post(f"/repos/{owner}/{repo}/issues/{issue_num}/comments", {"body": body})
+
+    def add_issue_label(self, owner: str, repo: str, issue_num: int, label: str) -> dict:
+        return self._post(
+            f"/repos/{owner}/{repo}/issues/{issue_num}/labels",
+            {"labels": [label]},
+        )
+
+    def assign_issue(self, owner: str, repo: str, issue_num: int, assignee: str) -> dict:
+        return self._patch(
+            f"/repos/{owner}/{repo}/issues/{issue_num}",
+            {"assignees": [assignee]},
+        )
+
+
+# ---------------------------------------------------------------------------
+# Scoring & Assignment Logic
+# ---------------------------------------------------------------------------
+
+def classify_issue(issue: dict) -> str:
+    """Determine the best agent role for an issue based on title/body."""
+    title = (issue.get("title", "") or "").lower()
+    body = (issue.get("body", "") or "").lower()
+    text = f"{title} {body}"
+    labels = [l.get("name", "").lower() for l in issue.get("labels", [])]
+    text += " " + " ".join(labels)
+
+    best_role = "small-tasks"  # default
+    best_score = 0
+
+    for role, keywords in ROLE_KEYWORDS.items():
+        if not keywords:
+            continue
+        score = sum(2 for kw in keywords if kw in text)
+        # Boost if a matching label exists
+        for label in labels:
+            if any(kw in label for kw in keywords):
+                score += 3
+        if score > best_score:
+            best_score = score
+            best_role = role
+
+    return best_role
+
+
+def compute_priority(issue: dict) -> int:
+    """Compute issue priority from keywords."""
+    title = (issue.get("title", "") or "").lower()
+    body = (issue.get("body", "") or "").lower()
+    text = f"{title} {body}"
+    return sum(v for k, v in PRIORITY_KEYWORDS.items() if k in text)
+
+
+def score_agent_for_issue(agent: dict, role: str, wolf_scores: dict, priority: int) -> float:
+    """Score how well an agent matches an issue. Higher is better."""
+    score = 0.0
+
+    # Primary: role match
+    agent_role = agent.get("role", "unknown")
+    if agent_role == role:
+        score += 10.0
+    elif agent_role == "small-tasks" and role in ("issue-triage", "on-request-queries"):
+        score += 6.0
+    elif agent_role == "triage-routing" and role in ("issue-triage", "triage-routing"):
+        score += 8.0
+    elif agent_role == "code-generation" and role in ("code-review", "devops"):
+        score += 4.0
+
+    # Wolf quality bonus
+    model = agent.get("model", "")
+    wolf_entry = None
+    for wm, ws in wolf_scores.items():
+        if model and model.lower() in wm.lower():
+            wolf_entry = ws
+            break
+    if wolf_entry and wolf_entry.get("success"):
+        score += wolf_entry.get("total", 0) * 3.0
+
+    # Cost efficiency: prefer free/cheap for low priority
+    tier = agent.get("tier", "unknown")
+    tier_idx = TIER_ORDER.index(tier) if tier in TIER_ORDER else 3
+    if priority <= 1 and tier in ("free", "cheap"):
+        score += 4.0
+    elif priority >= 3 and tier in ("prepaid",):
+        score += 3.0
+    else:
+        score += (3 - tier_idx) * 1.0
+
+    # Activity bonus
+    if agent.get("active", False):
+        score += 2.0
+
+    # Repo familiarity bonus: more repos slightly better
+    repo_count = agent.get("repo_count", 0)
+    score += min(repo_count * 0.2, 2.0)
+
+    return round(score, 3)
+
+
+def find_best_agent(agents: List[dict], role: str, wolf_scores: dict, priority: int,
+                    exclude: Optional[List[str]] = None) -> Optional[dict]:
+    """Find the best agent for the given role and priority."""
+    exclude = exclude or []
+    candidates = []
+    for agent in agents:
+        if agent.get("name") in exclude:
+            continue
+        if not agent.get("active", False):
+            continue
+        s = score_agent_for_issue(agent, role, wolf_scores, priority)
+        candidates.append((s, agent))
+
+    if not candidates:
+        return None
+
+    candidates.sort(key=lambda x: x[0], reverse=True)
+    return candidates[0][1]
+
+
+# ---------------------------------------------------------------------------
+# Dispatch
+# ---------------------------------------------------------------------------
+
+def dispatch_assignment(api: GiteaAPI, issue: dict, agent: dict, dry_run: bool = False) -> dict:
+    """Assign an issue to an agent and optionally post a comment."""
+    owner = ORG_NAME
+    repo = issue.get("repository", {}).get("name", "")
+
+    # Extract repo from issue repo_url if not in the repository key
+    if not repo:
+        repo_url = issue.get("repository_url", "")
+        if repo_url:
+            repo = repo_url.rstrip("/").split("/")[-1]
+
+    if not repo:
+        return {"success": False, "error": "Cannot determine repository for issue"}
+
+    issue_num = issue.get("number")
+    agent_name = agent.get("name", "unknown")
+
+    comment_body = (
+        f"🤖 **Workforce Manager assigned this issue to: @{agent_name}**\n\n"
+        f"- **Agent:** {agent_name}\n"
+        f"- **Model:** {agent.get('model', 'unknown')}\n"
+        f"- **Role:** {agent.get('role', 'unknown')}\n"
+        f"- **Tier:** {agent.get('tier', 'unknown')}\n"
+        f"- **Assigned at:** {datetime.now(timezone.utc).isoformat()}\n\n"
+        f"*Automated assignment by Workforce Manager (Epic #204)*"
+    )
+
+    if dry_run:
+        return {
+            "success": True,
+            "dry_run": True,
+            "repo": repo,
+            "issue_number": issue_num,
+            "assignee": agent_name,
+            "comment": comment_body,
+        }
+
+    try:
+        api.assign_issue(owner, repo, issue_num, agent_name)
+        api.add_issue_comment(owner, repo, issue_num, comment_body)
+        return {
+            "success": True,
+            "repo": repo,
+            "issue_number": issue_num,
+            "issue_title": issue.get("title", ""),
+            "assignee": agent_name,
+        }
+    except Exception as exc:
+        return {
+            "success": False,
+            "repo": repo,
+            "issue_number": issue_num,
+            "error": str(exc),
+        }
+
+
+# ---------------------------------------------------------------------------
+# State Tracking
+# ---------------------------------------------------------------------------
+
+def update_agent_stats(state: dict, result: dict) -> None:
+    """Update per-agent success tracking."""
+    agent_name = result.get("assignee", "unknown")
+    if "agent_stats" not in state:
+        state["agent_stats"] = {}
+    if agent_name not in state["agent_stats"]:
+        state["agent_stats"][agent_name] = {
+            "total_assigned": 0,
+            "successful": 0,
+            "failed": 0,
+            "success_rate": 0.0,
+            "last_assignment": None,
+            "assigned_issues": [],
+        }
+
+    stats = state["agent_stats"][agent_name]
+    stats["total_assigned"] += 1
+    stats["last_assignment"] = datetime.now(timezone.utc).isoformat()
+    stats["assigned_issues"].append({
+        "repo": result.get("repo", ""),
+        "issue_number": result.get("issue_number"),
+        "success": result.get("success", False),
+        "timestamp": datetime.now(timezone.utc).isoformat(),
+    })
+
+    if result.get("success"):
+        stats["successful"] += 1
+    else:
+        stats["failed"] += 1
+
+    total = stats["successful"] + stats["failed"]
+    stats["success_rate"] = round(stats["successful"] / total, 3) if total > 0 else 0.0
+
+
+def print_status(state: dict, agents: List[dict], issues_count: int) -> None:
+    """Print workforce status."""
+    print(f"\n{'=' * 60}")
+    print(f"Workforce Manager Status - {datetime.now(timezone.utc).strftime('%Y-%m-%d %H:%M UTC')}")
+    print(f"{'=' * 60}")
+
+    # Fleet summary
+    active = [a for a in agents if a.get("active")]
+    print(f"\nFleet: {len(active)} active agents, {len(agents)} total")
+    tier_counts = {}
+    for a in active:
+        t = a.get("tier", "unknown")
+        tier_counts[t] = tier_counts.get(t, 0) + 1
+    for t, c in sorted(tier_counts.items()):
+        print(f"  {t}: {c} agents")
+
+    # Agent scores
+    wolf = load_wolf_scores()
+    print(f"\nAgent Details:")
+    print(f"  {'Name':<25} {'Model':<30} {'Role':<18} {'Tier':<10}")
+    for a in agents:
+        if not a.get("active"):
+            continue
+        stats = state.get("agent_stats", {}).get(a["name"], {})
+        rate = stats.get("success_rate", 0.0)
+        total = stats.get("total_assigned", 0)
+        wolf_badge = ""
+        for wm, ws in wolf.items():
+            if a["model"] and a["model"].lower() in wm.lower() and ws.get("success"):
+                wolf_badge = f"[wolf:{ws['total']}]"
+                break
+        name_str = f"{a['name']} {wolf_badge}"
+        if total > 0:
+            name_str += f" (s/r: {rate}, n={total})"
+        print(f"  {name_str:<45} {a.get('role', 'unknown'):<18} {a.get('tier', '?'):<10}")
+
+    print(f"\nOpen Issues: {issues_count}")
+    print(f"Assignments Made: {len(state.get('assignments', []))}")
+    if state.get("last_run"):
+        print(f"Last Run: {state['last_run']}")
+
+
+# ---------------------------------------------------------------------------
+# Main
+# ---------------------------------------------------------------------------
+
+def main() -> int:
+    parser = argparse.ArgumentParser(description="Workforce Manager - Assign Gitea issues to AI agents")
+    parser.add_argument("--dry-run", action="store_true", help="Show assignments without dispatching")
+    parser.add_argument("--status", action="store_true", help="Show workforce status only")
+    parser.add_argument("--cron", action="store_true", help="Run silently for cron scheduling")
+    parser.add_argument("--label", type=str, help="Only process issues with this label")
+    parser.add_argument("--max-issues", type=int, default=100, help="Max issues to process per run")
+    args = parser.parse_args()
+
+    # Setup logging
+    if args.cron:
+        logging.basicConfig(level=logging.WARNING, format="%(asctime)s [%(levelname)s] %(message)s")
+    else:
+        logging.basicConfig(level=logging.INFO, format="%(asctime)s [%(levelname)s] %(message)s")
+
+    logging.info("Workforce Manager starting")
+
+    # Load data
+    agents = load_fleet_routing()
+    if not agents:
+        logging.error("No agents found in fleet-routing.json")
+        return 1
+    logging.info("Loaded %d agents from fleet routing", len(agents))
+
+    wolf_scores = load_wolf_scores()
+    if wolf_scores:
+        logging.info("Loaded %d model scores from Wolf results", len(wolf_scores))
+
+    state = load_workforce_state()
+
+    # Load Gitea token
+    if GITEA_TOKEN_PATH.exists():
+        token = GITEA_TOKEN_PATH.read_text().strip()
+    else:
+        logging.error("Gitea token not found at %s", GITEA_TOKEN_PATH)
+        return 1
+
+    api = GiteaAPI(token)
+
+    # Status-only mode
+    if args.status:
+        # Quick open issue count
+        repos = api.get_org_repos(ORG_NAME)
+        total = sum(r.get("open_issues_count", 0) for r in repos)
+        print_status(state, agents, total)
+        return 0
+
+    # Fetch open issues
+    if not args.cron:
+        print(f"Scanning open issues across {ORG_NAME} repos...")
+
+    issues = api.get_all_open_issues(ORG_NAME)
+
+    # Filter by label
+    if args.label:
+        issues = [
+            i for i in issues
+            if any(args.label in (l.get("name", "") or "").lower() for l in i.get("labels", []))
+        ]
+
+    if args.label:
+        logging.info("Filtered to %d issues with label '%s'", len(issues), args.label)
+    else:
+        logging.info("Found %d open issues", len(issues))
+
+    # Skip issues already assigned
+    already_assigned_nums = set()
+    for a in state.get("assignments", []):
+        already_assigned_nums.add((a.get("repo"), a.get("issue_number")))
+
+    issues = [
+        i for i in issues
+        if not i.get("assignee") and
+        not (i.get("repository", {}).get("name"), i.get("number")) in already_assigned_nums
+    ]
+    logging.info("%d unassigned issues to process", len(issues))
+
+    # Sort by priority
+    issues_with_priority = [(compute_priority(i), i) for i in issues]
+    issues_with_priority.sort(key=lambda x: x[0], reverse=True)
+    issues = [i for _, i in issues_with_priority[:args.max_issues]]
+
+    # Assign issues
+    assignments = []
+    agent_exclusions: Dict[str, List[str]] = {}  # repo -> list of assigned agents per run
+    global_exclusions: List[str] = []  # agents already at capacity per run
+    max_per_agent_per_run = 5
+
+    for issue in issues:
+        role = classify_issue(issue)
+        priority = compute_priority(issue)
+        repo = issue.get("repository", {}).get("name", "")
+
+        # Avoid assigning same agent twice to same repo in one run
+        repo_excluded = agent_exclusions.get(repo, [])
+
+        # Also exclude agents already at assignment cap
+        cap_excluded = [
+            name for name, stats in state.get("agent_stats", {}).items()
+            if stats.get("total_assigned", 0) > max_per_agent_per_run
+        ]
+
+        excluded = list(set(repo_excluded + global_exclusions + cap_excluded))
+
+        agent = find_best_agent(agents, role, wolf_scores, priority, exclude=excluded)
+        if not agent:
+            # Relax exclusions if no agent found
+            agent = find_best_agent(agents, role, wolf_scores, priority, exclude=[])
+            if not agent:
+            logging.warning("No suitable agent for issue #%d: %s (role=%s)",
+                          issue.get("number"), issue.get("title", ""), role)
+            continue
+
+        result = dispatch_assignment(api, issue, agent, dry_run=args.dry_run)
+        assignments.append(result)
+        update_agent_stats(state, result)
+
+        # Track per-repo exclusions
+        if repo not in agent_exclusions:
+            agent_exclusions[repo] = []
+        agent_exclusions[repo].append(agent["name"])
+
+        if args.dry_run:
+            print(f"  [DRY] #{issue['number']}: {issue.get('title','')[:60]} → @{agent['name']} ({role}, p={priority})")
+        else:
+            status_str = "OK" if result.get("success") else "FAIL"
+            print(f"  [{status_str}] #{issue['number']}: {issue.get('title','')[:60]} → @{agent['name']} ({role}, p={priority})")
+
+    # Save state
+    state["assignments"].extend([{
+        "repo": a.get("repo"),
+        "issue_number": a.get("issue_number"),
+        "assignee": a.get("assignee"),
+        "success": a.get("success", False),
+        "timestamp": datetime.now(timezone.utc).isoformat(),
+    } for a in assignments])
+    state["last_run"] = datetime.now(timezone.utc).isoformat()
+    save_workforce_state(state)
+
+    # Summary
+    ok = sum(1 for a in assignments if a.get("success"))
+    fail = len(assignments) - ok
+    logging.info("Done: %d assigned, %d succeeded, %d failed", len(assignments), ok, fail)
+
+    if not args.cron:
+        print(f"\n{'=' * 60}")
+        print(f"Summary: {len(assignments)} assignments, {ok} OK, {fail} failed")
+        # Show agent stats
+        for name, stats in state.get("agent_stats", {}).items():
+            if stats.get("total_assigned", 0) > 0:
+                print(f"  @{name}: {stats['successful']}/{stats['total_assigned']} ({stats.get('success_rate', 0):.0%} success)")
+        print(f"{'=' * 60}")
+
+    return 0
+
+
+if __name__ == "__main__":
+    sys.exit(main())