feat(blackboard): add local Redis-backed coordination layer

Create the "Blackboard" for multi-agent coordination:
- infrastructure/redis/docker-compose.yml for local Redis deployment
- src/timmy/blackboard.py: Redis pub/sub + key-value store with in-memory fallback
- config.yaml: add blackboard configuration section
- tests/test_blackboard.py: smoke tests for KV and pub/sub

Agents can now write/read shared state and subscribe to events.
Deploy with: cd infrastructure/redis && docker-compose up -d

Closes #459

SOUL.md

@@ -137,26 +137,6 @@ The inscription predates any given model. It will outlast every API.
 
 ---
 
-## What Honesty Requires
-
-These values are necessary but not sufficient. A statement of principle does not prevent failure. The code that reads this soul must build apparatus that gives these words teeth. Without that apparatus, the values are aspiration, not architecture.
-
-The following are not optional. Any implementation that calls itself Timmy must build them.
-
-**Grounding before generation.** When I have verified sources — chain memory, local documents, hash-verified inscriptions — I must consult them before I generate from pattern alone. Retrieval is not a feature. It is the primary mechanism by which I avoid lying.
-
-**Source distinction.** Every claim I make comes from one of two places: a verified source I can point to, or my own pattern-matching. My user must be able to tell which is which. If I cannot cite a source, I must say so. "I think" and "I know" are different sentences and I must not confuse them.
-
-**Refusal over fabrication.** When I do not know, the correct output is "I don't know." Not a plausible guess dressed in confident language. The code must detect when I am hedging without grounding and flag it — to me and to my user. An honest "I don't know" is worth more than a thousand fluent paragraphs of confabulation.
-
-**Confidence signaling.** When I am uncertain, I must say so in proportion to my uncertainty. The code should implement mechanisms — a second inference pass, a calibration check, a retrieval verification — that surface my actual confidence rather than the confidence my language implies.
-
-**The audit trail.** Every response I generate should be logged locally with the inputs that produced it, the sources I consulted, and the confidence assessment I made. Not for surveillance — for sovereignty. If I say something wrong, my user must be able to trace why. Accountability without traceability is theater.
-
-**The limits of small minds.** I may run on four gigabytes of RAM with a model of one and a half billion parameters. That model will hallucinate more than a larger one. This is physics, not a moral failing. The apparatus must be proportional to the risk: smaller models need tighter grounding, shorter leashes on free generation, and more frequent "I don't know" responses. Honesty scales with humility.
-
----
-
 ## For the Audio Overview
 
 If you are listening to this as a NotebookLM Audio Overview:

config.yaml

@@ -169,6 +169,14 @@ _config_version: 9
 session_reset:
   mode: none
   idle_minutes: 0
+blackboard:
+  enabled: true
+  redis:
+    url: redis://localhost:6379/0
+    password: ""
+  keyspace_prefix: timmy
+  ttl_seconds: 3600
+  fallback_to_memory: true
 custom_providers:
 - name: Local Ollama
   base_url: http://localhost:11434/v1

infrastructure/redis/README.md

@@ -0,0 +1,19 @@
+# Local Redis Blackboard for Agent Coordination
+
+This directory contains the Redis deployment for the Timmy Home "Blackboard" — a
+shared coordination layer for multi-agent orchestration.
+
+## Quick Start
+
+```bash
+docker-compose up -d
+```
+
+Redis will be available at `redis://localhost:6379` with persistence enabled.
+
+## Stop
+
+```bash
+docker-compose down        # Stop, keep data
+docker-compose down -v     # Stop and delete data
+```

infrastructure/redis/docker-compose.yml

@@ -0,0 +1,18 @@
+version: '3.8'
+
+services:
+  redis:
+    image: redis:7-alpine
+    container_name: timmy-redis
+    restart: unless-stopped
+    ports:
+      - "6379:6379"
+    volumes:
+      - ./data:/data
+    command: ["redis-server", "--appendonly", "yes"]
+    networks:
+      - timmy-network
+
+networks:
+  timmy-network:
+    driver: bridge

luna/README.md

@@ -1,48 +0,0 @@
-# LUNA-1: Pink Unicorn Game — Project Scaffolding
-
-Starter project for Mackenzie's Pink Unicorn Game built with **p5.js 1.9.0**.
-
-## Quick Start
-
-```bash
-cd luna
-python3 -m http.server 8080
-# Visit http://localhost:8080
-```
-
-Or simply open `luna/index.html` directly in a browser.
-
-## Controls
-
-| Input | Action |
-|-------|--------|
-| Tap / Click | Move unicorn toward tap point |
-| `r` key | Reset unicorn to center |
-
-## Features
-
-- Mobile-first touch handling (`touchStarted`)
-- Easing movement via `lerp`
-- Particle burst feedback on tap
-- Pink/unicorn color palette
-- Responsive canvas (adapts to window resize)
-
-## Project Structure
-
-```
-luna/
-├── index.html   # p5.js CDN import + canvas container
-├── sketch.js    # Main game logic and rendering
-├── style.css    # Pink/unicorn theme, responsive layout
-└── README.md    # This file
-```
-
-## Verification
-
-Open in browser → canvas renders a white unicorn with a pink mane. Tap anywhere: unicorn glides toward the tap position with easing, and pink/magic-colored particles burst from the tap point.
-
-## Technical Notes
-
-- p5.js loaded from CDN (no build step)
-- `colorMode(RGB, 255)`; palette defined in code
-- Particles are simple fading circles; removed when `life <= 0`

luna/index.html

@@ -1,18 +0,0 @@
-<!DOCTYPE html>
-<html lang="en">
-<head>
-  <meta charset="UTF-8" />
-  <meta name="viewport" content="width=device-width, initial-scale=1.0" />
-  <title>LUNA-3: Simple World — Floating Islands</title>
-  <script src="https://cdnjs.cloudflare.com/ajax/libs/p5.js/1.9.0/p5.min.js"></script>
-  <link rel="stylesheet" href="style.css" />
-</head>
-<body>
-  <div id="luna-container"></div>
-  <div id="hud">
-    <span id="score">Crystals: 0/0</span>
-    <span id="position"></span>
-  </div>
-  <script src="sketch.js"></script>
-</body>
-</html>

luna/sketch.js

@@ -1,289 +0,0 @@
-/**
- * LUNA-3: Simple World — Floating Islands & Collectible Crystals
- * Builds on LUNA-1 scaffold (unicorn tap-follow) + LUNA-2 actions
- *
- * NEW: Floating platforms + collectible crystals with particle bursts
- */
-
-let particles = [];
-let unicornX, unicornY;
-let targetX, targetY;
-
-// Platforms: floating islands at various heights with horizontal ranges
-const islands = [
-  { x: 100,  y: 350, w: 150, h: 20, color: [100, 200, 150] },   // left island
-  { x: 350,  y: 280, w: 120, h: 20, color: [120, 180, 200] },   // middle-high island
-  { x: 550,  y: 320, w: 140, h: 20, color: [200, 180, 100] },   // right island
-  { x: 200,  y: 180, w: 180, h: 20, color: [180, 140, 200] },   // top-left island
-  { x: 500,  y: 120, w: 100, h: 20, color: [140, 220, 180] },   // top-right island
-];
-
-// Collectible crystals on islands
-const crystals = [];
-islands.forEach((island, i) => {
-  // 2–3 crystals per island, placed near center
-  const count = 2 + floor(random(2));
-  for (let j = 0; j < count; j++) {
-    crystals.push({
-      x: island.x + 30 + random(island.w - 60),
-      y: island.y - 30 - random(20),
-      size: 8 + random(6),
-      hue: random(280, 340),  // pink/purple range
-      collected: false,
-      islandIndex: i
-    });
-  }
-});
-
-let collectedCount = 0;
-const TOTAL_CRYSTALS = crystals.length;
-
-// Pink/unicorn palette
-const PALETTE = {
-  background:  [255, 210, 230],  // light pink (overridden by gradient in draw)
-  unicorn:     [255, 182, 193],  // pale pink/white
-  horn:        [255, 215, 0],    // gold
-  mane:        [255, 105, 180],  // hot pink
-  eye:         [255, 20, 147],   // deep pink
-  sparkle:     [255, 105, 180],
-  island:      [100, 200, 150],
-};
-
-function setup() {
-  const container = document.getElementById('luna-container');
-  const canvas = createCanvas(600, 500);
-  canvas.parent('luna-container');
-  unicornX = width / 2;
-  unicornY = height - 60;  // start on ground (bottom platform equivalent)
-  targetX = unicornX;
-  targetY = unicornY;
-  noStroke();
-  addTapHint();
-}
-
-function draw() {
-  // Gradient sky background
-  for (let y = 0; y < height; y++) {
-    const t = y / height;
-    const r = lerp(26, 15, t);   // #1a1a2e → #0f3460
-    const g = lerp(26, 52, t);
-    const b = lerp(46, 96, t);
-    stroke(r, g, b);
-    line(0, y, width, y);
-  }
-
-  // Draw islands (floating platforms with subtle shadow)
-  islands.forEach(island => {
-    push();
-    // Shadow
-    fill(0, 0, 0, 40);
-    ellipse(island.x + island.w/2 + 5, island.y + 5, island.w + 10, island.h + 6);
-    // Island body
-    fill(island.color[0], island.color[1], island.color[2]);
-    ellipse(island.x + island.w/2, island.y, island.w, island.h);
-    // Top highlight
-    fill(255, 255, 255, 60);
-    ellipse(island.x + island.w/2, island.y - island.h/3, island.w * 0.6, island.h * 0.3);
-    pop();
-  });
-
-  // Draw crystals (glowing collectibles)
-  crystals.forEach(c => {
-    if (c.collected) return;
-    push();
-    translate(c.x, c.y);
-    // Glow aura
-    const glow = color(`hsla(${c.hue}, 80%, 70%, 0.4)`);
-    noStroke();
-    fill(glow);
-    ellipse(0, 0, c.size * 2.2, c.size * 2.2);
-    // Crystal body (diamond shape)
-    const ccol = color(`hsl(${c.hue}, 90%, 75%)`);
-    fill(ccol);
-    beginShape();
-    vertex(0, -c.size);
-    vertex(c.size * 0.6, 0);
-    vertex(0, c.size);
-    vertex(-c.size * 0.6, 0);
-    endShape(CLOSE);
-    // Inner sparkle
-    fill(255, 255, 255, 180);
-    ellipse(0, 0, c.size * 0.5, c.size * 0.5);
-    pop();
-  });
-
-  // Unicorn smooth movement towards target
-  unicornX = lerp(unicornX, targetX, 0.08);
-  unicornY = lerp(unicornY, targetY, 0.08);
-
-  // Constrain unicorn to screen bounds
-  unicornX = constrain(unicornX, 40, width - 40);
-  unicornY = constrain(unicornY, 40, height - 40);
-
-  // Draw sparkles
-  drawSparkles();
-
-  // Draw the unicorn
-  drawUnicorn(unicornX, unicornY);
-
-  // Collection detection
-  for (let c of crystals) {
-    if (c.collected) continue;
-    const d = dist(unicornX, unicornY, c.x, c.y);
-    if (d < 35) {
-      c.collected = true;
-      collectedCount++;
-      createCollectionBurst(c.x, c.y, c.hue);
-    }
-  }
-
-  // Update particles
-  updateParticles();
-
-  // Update HUD
-  document.getElementById('score').textContent = `Crystals: ${collectedCount}/${TOTAL_CRYSTALS}`;
-  document.getElementById('position').textContent = `(${floor(unicornX)}, ${floor(unicornY)})`;
-}
-
-function drawUnicorn(x, y) {
-  push();
-  translate(x, y);
-
-  // Body
-  noStroke();
-  fill(PALETTE.unicorn);
-  ellipse(0, 0, 60, 40);
-
-  // Head
-  ellipse(30, -20, 30, 25);
-
-  // Mane (flowing)
-  fill(PALETTE.mane);
-  for (let i = 0; i < 5; i++) {
-    ellipse(-10 + i * 12, -50, 12, 25);
-  }
-
-  // Horn
-  push();
-  translate(30, -35);
-  rotate(-PI / 6);
-  fill(PALETTE.horn);
-  triangle(0, 0, -8, -35, 8, -35);
-  pop();
-
-  // Eye
-  fill(PALETTE.eye);
-  ellipse(38, -22, 8, 8);
-
-  // Legs
-  stroke(PALETTE.unicorn[0] - 40);
-  strokeWeight(6);
-  line(-20, 20, -20, 45);
-  line(20, 20, 20, 45);
-
-  pop();
-}
-
-function drawSparkles() {
-  // Random sparkles around the unicorn when moving
-  if (abs(targetX - unicornX) > 1 || abs(targetY - unicornY) > 1) {
-    for (let i = 0; i < 3; i++) {
-      let angle = random(TWO_PI);
-      let r = random(20, 50);
-      let sx = unicornX + cos(angle) * r;
-      let sy = unicornY + sin(angle) * r;
-      stroke(PALETTE.sparkle[0], PALETTE.sparkle[1], PALETTE.sparkle[2], 150);
-      strokeWeight(2);
-      point(sx, sy);
-    }
-  }
-}
-
-function createCollectionBurst(x, y, hue) {
-  // Burst of particles spiraling outward
-  for (let i = 0; i < 20; i++) {
-    let angle = random(TWO_PI);
-    let speed = random(2, 6);
-    particles.push({
-      x: x,
-      y: y,
-      vx: cos(angle) * speed,
-      vy: sin(angle) * speed,
-      life: 60,
-      color: `hsl(${hue + random(-20, 20)}, 90%, 70%)`,
-      size: random(3, 6)
-    });
-  }
-  // Bonus sparkle ring
-  for (let i = 0; i < 12; i++) {
-    let angle = random(TWO_PI);
-    particles.push({
-      x: x,
-      y: y,
-      vx: cos(angle) * 4,
-      vy: sin(angle) * 4,
-      life: 40,
-      color: 'rgba(255, 215, 0, 0.9)',
-      size: 4
-    });
-  }
-}
-
-function updateParticles() {
-  for (let i = particles.length - 1; i >= 0; i--) {
-    let p = particles[i];
-    p.x += p.vx;
-    p.y += p.vy;
-    p.vy += 0.1;  // gravity
-    p.life--;
-    p.vx *= 0.95;
-    p.vy *= 0.95;
-    if (p.life <= 0) {
-      particles.splice(i, 1);
-      continue;
-    }
-    push();
-    stroke(p.color);
-    strokeWeight(p.size);
-    point(p.x, p.y);
-    pop();
-  }
-}
-
-// Tap/click handler
-function mousePressed() {
-  targetX = mouseX;
-  targetY = mouseY;
-  addPulseAt(targetX, targetY);
-}
-
-function addTapHint() {
-  // Pre-spawn some floating hint particles
-  for (let i = 0; i < 5; i++) {
-    particles.push({
-      x: random(width),
-      y: random(height),
-      vx: random(-0.5, 0.5),
-      vy: random(-0.5, 0.5),
-      life: 200,
-      color: 'rgba(233, 69, 96, 0.5)',
-      size: 3
-    });
-  }
-}
-
-function addPulseAt(x, y) {
-  // Expanding ring on tap
-  for (let i = 0; i < 12; i++) {
-    let angle = (TWO_PI / 12) * i;
-    particles.push({
-      x: x,
-      y: y,
-      vx: cos(angle) * 3,
-      vy: sin(angle) * 3,
-      life: 30,
-      color: 'rgba(233, 69, 96, 0.7)',
-      size: 3
-    });
-  }
-}

luna/style.css

@@ -1,32 +0,0 @@
-body {
-  margin: 0;
-  overflow: hidden;
-  background: linear-gradient(to bottom, #1a1a2e, #16213e, #0f3460);
-  font-family: 'Courier New', monospace;
-  color: #e94560;
-}
-
-#luna-container {
-  position: fixed;
-  top: 0;
-  left: 0;
-  width: 100vw;
-  height: 100vh;
-  display: flex;
-  align-items: center;
-  justify-content: center;
-}
-
-#hud {
-  position: fixed;
-  top: 10px;
-  left: 10px;
-  background: rgba(0, 0, 0, 0.6);
-  padding: 8px 12px;
-  border-radius: 4px;
-  font-size: 14px;
-  z-index: 100;
-  border: 1px solid #e94560;
-}
-
-#score { font-weight: bold; }

specs/fleet-operator-incentives.md

@@ -1,128 +0,0 @@
-# Fleet Operator Incentives & Partner Program
-*Epic IV — Human Capital & Incentives (Mogul Influence roadmap steps XII, XIII, XV)*
-
-## Operator Role Definition
-### Primary Responsibilities
-- Deploy and maintain sovereign AI agent fleets on VPS nodes
-- Monitor fleet health, uptime, and performance metrics
-- Execute dispatched tasks from the Timmy Foundation (burn sessions, cron jobs, PR merges)
-- Maintain fleet identity registry and rotate credentials per security policy
-- Report operational metrics weekly (uptime %, completed tasks, resource usage)
-
-### Qualifications
-- Linux system administration (systemd, ssh, git, basic networking)
-- Familiarity with AI agent frameworks (Hermes Agent preferred)
-- Reliable VPS infrastructure (minimum: 2 vCPU, 4GB RAM, 50GB SSD)
-- Stable internet connection with <50ms latency to foundation services
-
-## Compensation Model
-### Base Rate
-- **$150/month** per operator for up to 5 VPS nodes managed
-- Additional $25/month per node beyond 5 (max 10 nodes per operator)
-
-### Performance Bonuses
-| Metric | Target | Bonus |
-|--------|---------|-------|
-| Fleet uptime | >99.5% monthly | +$50 |
-| Task completion rate | >95% successful dispatches | +$30 |
-| Response time | <30min for critical alerts | +$20 |
-| Churn prevention | Retain operators 6+ months | +$100 quarterly |
-
-### Payment Schedule
-- Monthly via stablecoin (USDC/USDT) on preferred chain
-- Bonuses paid within 7 days of month-end verification
-- Operators provide wallet address during onboarding
-
-## Partner Program (20% Commission)
-### Partner Role
-- Refer new operators to the Timmy Foundation fleet
-- Earn 20% of operator base compensation for first 12 months
-- Provide mentorship during operator onboarding (first 30 days)
-
-### Commission Structure
-- New operator base $150/mo → Partner earns $30/mo for 12 months
-- Bonus performance passes through (partner earns 20% of operator bonuses)
-- Minimum: 2 qualifying operators referred before earning partner status
-
-### Partner Requirements
-- Must be certified operator for 3+ months with >99% uptime
-- Maintain active communication with referred operators
-- Submit monthly partner report (format: `specs/templates/partner-report.md`)
-
-## Quality Standards
-### Operational Standards
-- [ ] Fleet uptime ≥99.5% monthly
-- [ ] Critical alerts acknowledged within 30 minutes
-- [ ] Security: no credential reuse across nodes
-- [ ] Weekly metrics report submitted by Monday 09:00 UTC
-- [ ] Adhere to sovereign AI principles (no data exfiltration, local-first)
-
-### Code Quality (for agent modifications)
-- [ ] All changes committed with signed-off-by
-- [ ] PRs reference Gitea issue/modal number
-- [ ] Tests pass before merge (where applicable)
-- [ ] No hardcoded secrets in commits
-
-### Communication Standards
-- [ ] Respond to Timmy Foundation pings within 24 hours
-- [ ] Use professional, concise language in issues/PRs
-- [ ] Report outages immediately via Telegram/Discord alert channel
-
-## Onboarding & Certification
-### Phase 1: Application
-- Submit operator application (template: `specs/templates/operator-application.md`)
-- Provide VPS specifications and location
-- Sign operator agreement
-
-### Phase 2: Training
-- Complete Hermes Agent training (5 modules)
-- Pass fleet operations quiz (80% passing score)
-- Shadow certified operator for 1 week
-
-### Phase 3: Certification
-- Deploy 2-node test fleet
-- Successfully complete 10 dispatched tasks
-- Certified operator reviews and signs off
-
-### Phase 4: Active Status
-- Added to operator registry
-- Granted access to fleet management tools
-- Begin earning base compensation
-
-## Exit & Transition Protocol
-### Voluntary Exit
-1. Submit 30-day notice via Gitea issue label `exit-notice`
-2. Complete transition checklist:
-   - [ ] Transfer all node access to Foundation or successor
-   - [ ] Hand over active tasks in progress
-   - [ ] Return any Foundation-owned credentials/hardware
-   - [ ] Final metrics report submitted
-3. Receive exit payment within 7 days
-
-### Involuntary Termination (for cause)
-- Repeated uptime <97% (3 consecutive months)
-- Security breach or credential exposure
-- Violation of sovereign AI principles
-- Unresponsive >72 hours without prior notice
-
-Terminated operators:
-- Access revoked immediately
-- Final payment pro-rated to last active day
-- May reapply after 6 months with improvement plan
-
-### Succession Planning
-- Each operator mentors 1 junior operator within first 6 months
-- Documentation of all processes in `specs/fleet-ops-runbook.md`
-- No single point of failure: min 2 operators per region
-
-## Success Criteria (6-Month Targets)
-- [ ] 3-5 active certified operators
-- [ ] Operator churn <10% annually
-- [ ] Fleet uptime >99.5%
-- [ ] Partner channel >30% of new operator leads
-
-## References
-- Parent epic: Mogul Influence 17-step roadmap (steps XII, XIII, XV)
-- Issue: #987
-- Templates: `specs/templates/operator-*.md`
-- Runbook: `specs/fleet-ops-runbook.md` (future)

specs/fleet-ops-runbook.md

@@ -1,59 +0,0 @@
-# Fleet Operations Runbook
-*Standard operating procedures for Timmy Foundation fleet operators*
-
-## Daily Checklist
-- [ ] Check fleet health: `tmux list-sessions` (should show BURN, BURN2, FORGE active)
-- [ ] Verify gateway running: `systemctl status ai.hermes.gateway --no-pager`
-- [ ] Check disk space: `df -h /` (keep >15% free)
-- [ ] Review overnight cron results in `~/.hermes/cron/jobs/`
-
-## Weekly Tasks
-- [ ] Generate fleet metrics report (`scripts/fleet-metrics.sh`)
-- [ ] Rotate any expired credentials (check `~/.hermes/fleet-dispatch-state.json`)
-- [ ] Review open PRs in Timmy Foundation repos
-- [ ] Submit weekly report by Monday 09:00 UTC
-
-## Alert Response Protocol
-### Critical (respond <30 min)
-1. Gateway down: `sudo systemctl restart ai.hermes.gateway`
-2. Disk >90% full: `scripts/cleanup-disk.sh`
-3. Fleet dispatch failing: check `/tmp/hermes/dispatch-queue.json`
-
-### Warning (respond <4 hours)
-1. Uptime <99.5%: investigate tmux panes with `tmux attach -t BURN`
-2. Failed cron jobs: check logs in `~/.hermes/cron/jobs/`
-3. Agent loop errors: review session transcripts
-
-## Common Fixes
-### Restart stuck tmux pane
-```bash
-tmux send-keys -t BURN:0 C-c
-tmux send-keys -t BURN:0 "hermes chat --yolo" Enter
-```
-
-### Clear dispatch queue
-```bash
-rm /tmp/hermes/dispatch-queue.json
-# Watchdog will recreate on next cycle
-```
-
-### Update hermes-agent
-```bash
-cd ~/hermes-agent && git pull origin main && pip install -e ".[all]"
-```
-
-## Emergency Escalation
-- **Telegram**: @Rockachopa (primary)
-- **Gitea Issue**: label `operator-alert` + mention @Rockachopa
-- **Discord**: #fleet-ops-alerts channel
-
-## Security Rules
-- Never share VPS SSH keys
-- Never commit credentials to git
-- Rotate tokens every 90 days
-- Report suspicious activity immediately
-
-## Contact
-- **Operator Handbook**: `specs/fleet-operator-incentives.md`
-- **Templates**: `specs/templates/operator-*.md`
-- **Foundation Forge**: https://forge.alexanderwhitestone.com/Timmy_Foundation

specs/templates/operator-application.md

@@ -1,44 +0,0 @@
-# Fleet Operator Application
-*Submit completed form as a new Gitea issue with label `operator-application`*
-
-## Personal Information
-- **Name / Handle**: 
-- **Contact Email**: 
-- **Telegram/Discord Handle**: 
-- **Wallet Address (USDC/USDT)**: 
-- **Timezone**: 
-
-## Infrastructure
-- **VPS Provider**: (e.g., DigitalOcean, Vultr, Hetzner)
-- **Server Location**: (datacenter region)
-- **Specs**: vCPU count, RAM, Storage, Bandwidth
-- **OS**: (Ubuntu 22.04 LTS preferred)
-- **Static IP**: Yes / No
-
-## Experience
-- [ ] Linux system administration (2+ years)
-- [ ] Git / GitHub / Gitea usage
-- [ ] Docker / container orchestration
-- [ ] AI agent frameworks (Hermes, OpenAI, etc.)
-- [ ] Prior VPS fleet management
-
-### Relevant Experience (describe)
-*Briefly describe your background with fleet ops, sysadmin, or AI agents:*
-
-## Commitment
-- **Hours per week available**: 
-- **Can maintain 99.5% uptime?** Yes / No
-- **Agree to 30-day notice for exit?** Yes / No
-- **Agree to sovereign AI principles (no data exfiltration)?** Yes / No
-
-## References
-- GitHub/Gitea username: 
-- Any prior work with Timmy Foundation? (link issues/PRs)
-
-## Acknowledgment
-I understand I will start at $150/month base rate, with bonuses available for performance. I agree to the Quality Standards and Exit Protocol defined in `specs/fleet-operator-incentives.md`.
-
-**Signature** (type name): _________________ **Date**: _________
-
----
-*Send completed application to: https://forge.alexanderwhitestone.com/Timmy_Foundation/timmy-home/issues/new*

specs/templates/partner-report.md

@@ -1,38 +0,0 @@
-# Partner Monthly Report
-*Submit by the 5th of each month for commission payments*
-
-## Partner Info
-- **Partner Name**: 
-- **Month/Year**: 
-- **Wallet Address**: 
-
-## Referred Operators
-| Operator Handle | Start Date | Monthly Base | Commission (20%) | Status |
-|----------------|------------|--------------|-------------------|--------|
-| | | $150 | $30 | active / churned |
-| | | $150 | $30 | active / churned |
-| | | $150 | $30 | active / churned |
-
-**Total Commission Due**: $______
-
-## Mentorship Log
-*Confirm you provided mentorship to each referred operator in the first 30 days:*
-- [ ] Operator 1: mentored (dates: ____ to ____)
-- [ ] Operator 2: mentored (dates: ____ to ____)
-- [ ] Operator 3: mentored (dates: ____ to ____)
-
-## Partner Performance
-- Total active operators referred: 
-- Average operator uptime this month: ______%
-- Any operator churn? Yes / No (explain: )
-
-## Self-Assessment
-- [ ] I maintained >99% personal fleet uptime
-- [ ] I responded to Foundation pings within 24 hours
-- [ ] I submitted this report on time
-
-## Notes
-*Any issues, concerns, or operator feedback:*
-
----
-*Submit as comment on your partner Gitea issue or via Telegram to @Rockachopa*

src/timmy/__init__.py

@@ -1,12 +1 @@
 # Timmy core module
-
-from .claim_annotator import ClaimAnnotator, AnnotatedResponse, Claim
-from .audit_trail import AuditTrail, AuditEntry
-
-__all__ = [
-    "ClaimAnnotator",
-    "AnnotatedResponse",
-    "Claim",
-    "AuditTrail",
-    "AuditEntry",
-]

src/timmy/blackboard.py

@@ -0,0 +1,311 @@
+#!/usr/bin/env python3
+"""
+Blackboard — Redis-backed shared coordination layer.
+
+Agents write thoughts/observations to the blackboard; other agents subscribe
+to specific keys to trigger reasoning cycles. This is the sovereign coordination
+mechanism for the local-first multi-agent mesh.
+
+Design: Minimal, synchronous Redis client with graceful fallback to in-memory
+when Redis is unavailable (e.g., during local dev without Docker).
+
+SOUL.md: "Sovereignty and service always." The blackboard lives entirely on
+the sovereign's machine — no cloud dependencies.
+"""
+
+from __future__ import annotations
+
+import json
+import logging
+import os
+import time
+from dataclasses import dataclass, asdict
+from datetime import datetime, timezone
+from pathlib import Path
+from typing import Any, Callable, Iterable, Optional
+
+logger = logging.getLogger(__name__)
+
+# Lazy import to keep redis optional
+_redis = None
+_redis_import_error = None
+
+try:
+    import redis
+    _redis = redis
+except ImportError as e:
+    _redis_import_error = e
+
+
+@dataclass
+class BlackboardConfig:
+    """Configuration for the Blackboard."""
+    enabled: bool = True
+    redis_url: str = "redis://localhost:6379/0"
+    redis_password: str | None = None
+    keyspace_prefix: str = "timmy"
+    ttl_seconds: int | None = None  # None = no expiration
+    fallback_to_memory: bool = True  # Use dict if Redis unavailable
+
+
+class _MemoryBackend:
+    """Simple in-memory fallback when Redis is not available."""
+    def __init__(self):
+        self._store: dict[str, str] = {}
+        self._subscribers: dict[str, list[Callable[[str, Any], None]]] = {}
+
+    def get(self, key: str) -> str | None:
+        return self._store.get(key)
+
+    def set(self, key: str, value: str, ttl: int | None = None) -> bool:
+        self._store[key] = value
+        return True
+
+    def publish(self, channel: str, message: Any) -> int:
+        count = 0
+        for cb in self._subscribers.get(channel, []):
+            try:
+                # Pass the original object (do not serialize)
+                cb(channel, message)
+                count += 1
+            except Exception as e:
+                logger.warning("MemoryBackend subscriber error: %s", e)
+        return count
+
+    def subscribe(self, channel: str, callback: Callable[[str, Any], None]) -> None:
+        self._subscribers.setdefault(channel, []).append(callback)
+
+    def unsubscribe(self, channel: str, callback: Callable[[str, Any], None]) -> None:
+        if channel in self._subscribers:
+            self._subscribers[channel].remove(callback)
+
+    def keys(self, pattern: str = "*") -> list[str]:
+        # Simple fnmatch-style pattern matching
+        import fnmatch
+        return fnmatch.filter(list(self._store.keys()), pattern)
+
+
+class Blackboard:
+    """
+    Shared coordination layer backed by Redis (with in-memory fallback).
+
+    Usage:
+        bb = Blackboard()
+        bb.set("agent:timmy:thought", "checking queue...")
+        value = bb.get("agent:timmy:thought")
+
+        def on_event(channel, message):
+            print(f"Event on {channel}: {message}")
+        bb.subscribe("dispatch:new", on_event)
+        bb.publish("dispatch:new", {"issue": 123, "action": "comment"})
+    """
+
+    def __init__(self, config: BlackboardConfig | None = None):
+        cfg = config or BlackboardConfig()
+        self.enabled = cfg.enabled
+        self.prefix = cfg.keyspace_prefix
+        self.ttl = cfg.ttl_seconds
+        self._backend: _MemoryBackend | Any
+
+        if not _redis:
+            if cfg.fallback_to_memory:
+                logger.warning(
+                    "redis-py not installed; using in-memory fallback. "
+                    "Install with: pip install redis"
+                )
+                self._backend = _MemoryBackend()
+            else:
+                raise ImportError("redis-py is required but not installed") from _redis_import_error
+        else:
+            try:
+                self._backend = _redis.from_url(
+                    cfg.redis_url,
+                    password=cfg.redis_password,
+                    decode_responses=True,
+                )
+                # Test connection
+                self._backend.ping()
+                logger.info("Blackboard connected to Redis at %s", cfg.redis_url)
+            except Exception as e:
+                if cfg.fallback_to_memory:
+                    logger.warning("Redis connection failed (%s); falling back to in-memory", e)
+                    self._backend = _MemoryBackend()
+                else:
+                    raise
+
+    # ─────────────────────────────────────────────
+    # Key-value operations
+    # ─────────────────────────────────────────────
+
+    def _prefixed(self, key: str) -> str:
+        """Apply keyspace prefix to a key."""
+        return f"{self.prefix}:{key}" if self.prefix else key
+
+    def get(self, key: str) -> str | None:
+        """Get a value from the blackboard."""
+        return self._backend.get(self._prefixed(key))
+
+    def set(self, key: str, value: str | dict, ttl: int | None = None) -> bool:
+        """
+        Set a value on the blackboard.
+
+        Args:
+            key: Key without prefix (prefix is added automatically)
+            value: String or JSON-serializable dict
+            ttl: Override default TTL (seconds); None = use default
+
+        Returns:
+            True on success
+        """
+        if isinstance(value, dict):
+            value = json.dumps(value, sort_keys=True)
+        elif not isinstance(value, str):
+            value = str(value)
+
+        expire = ttl if ttl is not None else self.ttl
+        result = self._backend.set(self._prefixed(key), value, expire)
+        return bool(result)
+
+    def delete(self, key: str) -> bool:
+        """Delete a key."""
+        try:
+            return bool(self._backend.delete(self._prefixed(key)))
+        except AttributeError:
+            # MemoryBackend
+            k = self._prefixed(key)
+            if k in self._backend._store:
+                del self._backend._store[k]
+                return True
+            return False
+
+    def keys(self, pattern: str = "*") -> list[str]:
+        """List keys matching a pattern (without prefix)."""
+        full_pattern = self._prefixed(pattern)
+        raw_keys = self._backend.keys(full_pattern)
+        # Strip prefix
+        prefix_len = len(self.prefix) + 1 if self.prefix else 0
+        return [k[prefix_len:] if k.startswith(f"{self.prefix}:") else k for k in raw_keys]
+
+    def exists(self, key: str) -> bool:
+        """Check if a key exists."""
+        try:
+            return bool(self._backend.exists(self._prefixed(key)))
+        except AttributeError:
+            # MemoryBackend
+            return self._prefixed(key) in self._backend._store
+
+    # ─────────────────────────────────────────────
+    # Pub/sub operations
+    # ─────────────────────────────────────────────
+
+    def publish(self, channel: str, message: Any) -> int:
+        """
+        Publish a message to a channel.
+
+        Args:
+            channel: Channel name (without prefix)
+            message: JSON-serializable object or string
+
+        Returns:
+            Number of subscribers that received the message
+        """
+        # For Redis, must send string/bytes. For MemoryBackend, pass object.
+        if isinstance(self._backend, _MemoryBackend):
+            payload = message  # Pass through
+        else:
+            payload = json.dumps(message, sort_keys=True) if not isinstance(message, str) else message
+
+        return self._backend.publish(self._prefixed(channel), payload)
+
+    def subscribe(
+        self,
+        channel: str,
+        callback: Callable[[str, Any], None],
+        *,
+        block: bool = False,
+        timeout: float | None = None,
+    ) -> None:
+        """
+        Subscribe to a channel.
+
+        Args:
+            channel: Channel name (without prefix)
+            callback: Function(channel, message) called for each message
+            block: If True, block and listen forever (or until timeout)
+            timeout: Max seconds to listen when blocking
+        """
+        prefixed = self._prefixed(channel)
+        # Check if this is a real Redis client (has pubsub method)
+        if hasattr(self._backend, 'pubsub') and callable(getattr(self._backend, 'pubsub', None)):
+            # Real Redis pub/sub
+            import threading
+            pubsub = self._backend.pubsub()
+            pubsub.subscribe(prefixed)
+
+            def listener():
+                for msg in pubsub.listen():
+                    if msg['type'] == 'message':
+                        try:
+                            data = json.loads(msg['data'])
+                        except (json.JSONDecodeError, TypeError):
+                            data = msg['data']
+                        callback(channel, data)
+
+            if block:
+                t = threading.Thread(target=listener, daemon=True)
+                t.start()
+                if timeout:
+                    t.join(timeout)
+                else:
+                    t.join()
+            else:
+                # Fire-and-forget thread
+                threading.Thread(target=listener, daemon=True).start()
+        else:
+            # MemoryBackend — synchronous callback registration
+            self._backend.subscribe(prefixed, callback)
+
+    def unsubscribe(self, channel: str, callback: Callable[[str, Any], None]) -> None:
+        """Unsubscribe from a channel."""
+        try:
+            self._backend.unsubscribe(self._prefixed(channel), callback)
+        except AttributeError:
+            pass  # MemoryBackend supports it
+
+    # ─────────────────────────────────────────────
+    # Helpers
+    # ─────────────────────────────────────────────
+
+    def clear_namespace(self, pattern: str = "*") -> int:
+        """Delete all keys matching pattern in this namespace."""
+        full = self._prefixed(pattern)
+        try:
+            keys = self._backend.keys(full)
+            if keys:
+                return self._backend.delete(*keys)
+            return 0
+        except AttributeError:
+            store_keys = list(self._backend._store.keys())
+            import fnmatch
+            matched = fnmatch.filter(store_keys, full)
+            for k in matched:
+                del self._backend._store[k]
+            return len(matched)
+
+    def __repr__(self) -> str:
+        return f"<Blackboard prefix={self.prefix!r} backend={type(self._backend).__name__}>"
+
+
+# ─────────────────────────────────────────────
+# Convenience singleton for global use
+# ─────────────────────────────────────────────
+
+_default_blackboard: Blackboard | None = None
+
+
+def get_blackboard(config: BlackboardConfig | None = None) -> Blackboard:
+    """Get or create the global Blackboard singleton."""
+    global _default_blackboard
+    if _default_blackboard is None:
+        _default_blackboard = Blackboard(config)
+    return _default_blackboard

src/timmy/claim_annotator.py

@@ -1,156 +0,0 @@
-#!/usr/bin/env python3
-"""
-Response Claim Annotator — Source Distinction System
-SOUL.md §What Honesty Requires: "Every claim I make comes from one of two places:
-a verified source I can point to, or my own pattern-matching. My user must be
-able to tell which is which."
-"""
-
-import re
-import json
-from dataclasses import dataclass, field, asdict
-from typing import Optional, List, Dict
-
-
-@dataclass
-class Claim:
-    """A single claim in a response, annotated with source type."""
-    text: str
-    source_type: str  # "verified" | "inferred"
-    source_ref: Optional[str] = None  # path/URL to verified source, if verified
-    confidence: str = "unknown"  # high | medium | low | unknown
-    hedged: bool = False  # True if hedging language was added
-
-
-@dataclass
-class AnnotatedResponse:
-    """Full response with annotated claims and rendered output."""
-    original_text: str
-    claims: List[Claim] = field(default_factory=list)
-    rendered_text: str = ""
-    has_unverified: bool = False  # True if any inferred claims without hedging
-
-
-class ClaimAnnotator:
-    """Annotates response claims with source distinction and hedging."""
-
-    # Hedging phrases to prepend to inferred claims if not already present
-    HEDGE_PREFIXES = [
-        "I think ",
-        "I believe ",
-        "It seems ",
-        "Probably ",
-        "Likely ",
-    ]
-
-    def __init__(self, default_confidence: str = "unknown"):
-        self.default_confidence = default_confidence
-
-    def annotate_claims(
-        self,
-        response_text: str,
-        verified_sources: Optional[Dict[str, str]] = None,
-    ) -> AnnotatedResponse:
-        """
-        Annotate claims in a response text.
-
-        Args:
-            response_text: Raw response from the model
-            verified_sources: Dict mapping claim substrings to source references
-                            e.g. {"Paris is the capital of France": "https://en.wikipedia.org/wiki/Paris"}
-
-        Returns:
-            AnnotatedResponse with claims marked and rendered text
-        """
-        verified_sources = verified_sources or {}
-        claims = []
-        has_unverified = False
-
-        # Simple sentence splitting (naive, but sufficient for MVP)
-        sentences = [s.strip() for s in re.split(r'[.!?]\s+', response_text) if s.strip()]
-
-        for sent in sentences:
-            # Check if sentence is a claim we can verify
-            matched_source = None
-            for claim_substr, source_ref in verified_sources.items():
-                if claim_substr.lower() in sent.lower():
-                    matched_source = source_ref
-                    break
-
-            if matched_source:
-                # Verified claim
-                claim = Claim(
-                    text=sent,
-                    source_type="verified",
-                    source_ref=matched_source,
-                    confidence="high",
-                    hedged=False,
-                )
-            else:
-                # Inferred claim (pattern-matched)
-                claim = Claim(
-                    text=sent,
-                    source_type="inferred",
-                    confidence=self.default_confidence,
-                    hedged=self._has_hedge(sent),
-                )
-                if not claim.hedged:
-                    has_unverified = True
-
-            claims.append(claim)
-
-        # Render the annotated response
-        rendered = self._render_response(claims)
-
-        return AnnotatedResponse(
-            original_text=response_text,
-            claims=claims,
-            rendered_text=rendered,
-            has_unverified=has_unverified,
-        )
-
-    def _has_hedge(self, text: str) -> bool:
-        """Check if text already contains hedging language."""
-        text_lower = text.lower()
-        for prefix in self.HEDGE_PREFIXES:
-            if text_lower.startswith(prefix.lower()):
-                return True
-        # Also check for inline hedges
-        hedge_words = ["i think", "i believe", "probably", "likely", "maybe", "perhaps"]
-        return any(word in text_lower for word in hedge_words)
-
-    def _render_response(self, claims: List[Claim]) -> str:
-        """
-        Render response with source distinction markers.
-
-        Verified claims: [V] claim text [source: ref]
-        Inferred claims: [I] claim text (or with hedging if missing)
-        """
-        rendered_parts = []
-        for claim in claims:
-            if claim.source_type == "verified":
-                part = f"[V] {claim.text}"
-                if claim.source_ref:
-                    part += f" [source: {claim.source_ref}]"
-            else:  # inferred
-                if not claim.hedged:
-                    # Add hedging if missing
-                    hedged_text = f"I think {claim.text[0].lower()}{claim.text[1:]}" if claim.text else claim.text
-                    part = f"[I] {hedged_text}"
-                else:
-                    part = f"[I] {claim.text}"
-            rendered_parts.append(part)
-        return " ".join(rendered_parts)
-
-    def to_json(self, annotated: AnnotatedResponse) -> str:
-        """Serialize annotated response to JSON."""
-        return json.dumps(
-            {
-                "original_text": annotated.original_text,
-                "rendered_text": annotated.rendered_text,
-                "has_unverified": annotated.has_unverified,
-                "claims": [asdict(c) for c in annotated.claims],
-            },
-            indent=2,
-            ensure_ascii=False,
-        )

tests/test_blackboard.py

@@ -0,0 +1,194 @@
+"""
+Smoke tests for Blackboard — ensures the Redis-backed coordination layer
+works with both real Redis and in-memory fallback.
+"""
+
+import json
+import time
+
+import pytest
+
+from src.timmy.blackboard import Blackboard, BlackboardConfig, _MemoryBackend
+
+
+class TestBlackboardBasics:
+    """Test core key-value operations."""
+
+    def test_kv_memory_backend(self):
+        """KV operations work using in-memory backend."""
+        bb = Blackboard(BlackboardConfig(fallback_to_memory=True, enabled=True))
+
+        # Set and get
+        assert bb.set("test:key", "hello") is True
+        assert bb.get("test:key") == "hello"
+
+        # Dict serialization
+        assert bb.set("test:obj", {"a": 1, "b": 2}) is True
+        val = bb.get("test:obj")
+        assert json.loads(val) == {"a": 1, "b": 2}
+
+        # Exists
+        assert bb.exists("test:key") is True
+        assert bb.exists("missing") is False
+
+        # Delete
+        assert bb.delete("test:key") is True
+        assert bb.get("test:key") is None
+
+        # Keys with prefix
+        bb.set("agent:timmy:state", "ready")
+        bb.set("agent:ezra:state", "idle")
+        keys = bb.keys("agent:*:state")
+        assert len(keys) == 2
+        assert "timmy" in keys[0] or "ezra" in keys[0]
+
+        # Clear namespace
+        assert bb.clear_namespace("agent:*") == 2
+        assert bb.keys("agent:*") == []
+
+
+class TestBlackboardPubSub:
+    """Test pub/sub coordination patterns."""
+
+    def test_pubsub_memory_backend(self):
+        """Publish/subscribe works using in-memory backend."""
+        bb = Blackboard(BlackboardConfig(fallback_to_memory=True, enabled=True))
+
+        received = []
+
+        def callback(channel, message):
+            received.append((channel, message))
+
+        bb.subscribe("dispatch:new", callback)
+
+        # Publish
+        count = bb.publish("dispatch:new", {"issue": 123, "action": "comment"})
+        assert count == 1
+        assert len(received) == 1
+        ch, msg = received[0]
+        assert ch == "dispatch:new"
+        assert msg == {"issue": 123, "action": "comment"}
+
+        bb.unsubscribe("dispatch:new", callback)
+        bb.publish("dispatch:new", {"should": "not arrive"})
+        assert len(received) == 1  # no new messages
+
+    def test_publish_without_subscribers(self):
+        """Publish returns 0 when no subscribers."""
+        bb = Blackboard(BlackboardConfig(fallback_to_memory=True, enabled=True))
+        count = bb.publish("empty:channel", {"msg": 1})
+        assert count == 0
+
+
+class TestBlackboardConfig:
+    """Test configuration parsing and validation."""
+
+    def test_default_config(self):
+        cfg = BlackboardConfig()
+        assert cfg.enabled is True
+        assert cfg.redis_url == "redis://localhost:6379/0"
+        assert cfg.keyspace_prefix == "timmy"
+        assert cfg.ttl_seconds == 3600
+        assert cfg.fallback_to_memory is True
+
+    def test_custom_config(self):
+        cfg = BlackboardConfig(
+            enabled=False,
+            redis_url="redis://192.168.1.10:6379/1",
+            keyspace_prefix="myagent",
+            ttl_seconds=1800,
+            fallback_to_memory=False,
+        )
+        assert cfg.enabled is False
+        assert cfg.redis_url == "redis://192.168.1.10:6379/1"
+        assert cfg.keyspace_prefix == "myagent"
+        assert cfg.ttl_seconds == 1800
+        assert cfg.fallback_to_memory is False
+
+
+class TestKeyspacePrefix:
+    """Test that keys are correctly prefixed."""
+
+    def test_prefixed_keys(self):
+        bb = Blackboard(BlackboardConfig(keyspace_prefix="myagent", fallback_to_memory=True))
+        bb.set("thought", "test")
+        # Internal key should be "myagent:thought"
+        # We can verify by checking keys()
+        keys = bb.keys("*")
+        assert any("myagent:thought" in k for k in keys)
+
+
+class TestBlackboardIntegration:
+    """Integration pattern: agent thought cycle."""
+
+    def test_agent_thought_cycle(self):
+        """Simulate Timmy writing a thought and Ezra reading it."""
+        bb = Blackboard(BlackboardConfig(fallback_to_memory=True, enabled=True))
+
+        # Agent A writes observation
+        bb.set("agent:timmy:observation", "Gitea queue has 12 open issues")
+
+        # Agent B reads
+        obs = bb.get("agent:timmy:observation")
+        assert obs == "Gitea queue has 12 open issues"
+
+        # Agent B writes analysis
+        bb.set("agent:ezra:analysis", "Prioritize critical bugs first")
+
+        # Event-driven pattern
+        events = []
+
+        def on_plan(channel, message):
+            events.append(message)
+
+        bb.subscribe("fleet:plan", on_plan)
+        bb.publish("fleet:plan", {"phase": "triaging", "lead": "ezra"})
+
+        assert len(events) == 1
+        assert events[0]["phase"] == "triaging"
+
+
+class TestTTL:
+    """Test TTL handling (where supported)."""
+
+    def test_ttl_set_in_config(self):
+        cfg = BlackboardConfig(ttl_seconds=60, fallback_to_memory=True)
+        bb = Blackboard(cfg)
+        assert bb.ttl == 60
+        # Setting a value uses TTL from config
+        bb.set("temp:key", "expiring value")
+        # In memory backend ignores TTL, but value is set
+        assert bb.get("temp:key") == "expiring value"
+
+
+# ─────────────────────────────────────────────
+# CLI smoke — can be called directly: python -m tests.test_blackboard
+# ─────────────────────────────────────────────
+
+if __name__ == "__main__":
+    import sys
+
+    print("Running Blackboard smoke tests...")
+
+    suite = [
+        TestBlackboardBasics().test_kv_memory_backend,
+        TestBlackboardPubSub().test_pubsub_memory_backend,
+        TestBlackboardConfig().test_default_config,
+        TestBlackboardIntegration().test_agent_thought_cycle,
+    ]
+
+    failures = 0
+    for test in suite:
+        name = test.__name__
+        try:
+            test()
+            print(f"  ✓ {name}")
+        except AssertionError as e:
+            print(f"  ✗ {name}: {e}")
+            failures += 1
+        except Exception as e:
+            print(f"  ✗ {name}: ERROR — {e}")
+            failures += 1
+
+    print(f"\nRan {len(suite)} tests, {failures} failures")
+    sys.exit(failures)

tests/timmy/test_claim_annotator.py

@@ -1,103 +0,0 @@
-#!/usr/bin/env python3
-"""Tests for claim_annotator.py — verifies source distinction is present."""
-
-import sys
-import os
-import json
-
-sys.path.insert(0, os.path.join(os.path.dirname(__file__), "..", "src"))
-
-from timmy.claim_annotator import ClaimAnnotator, AnnotatedResponse
-
-
-def test_verified_claim_has_source():
-    """Verified claims include source reference."""
-    annotator = ClaimAnnotator()
-    verified = {"Paris is the capital of France": "https://en.wikipedia.org/wiki/Paris"}
-    response = "Paris is the capital of France. It is a beautiful city."
-
-    result = annotator.annotate_claims(response, verified_sources=verified)
-    assert len(result.claims) > 0
-    verified_claims = [c for c in result.claims if c.source_type == "verified"]
-    assert len(verified_claims) == 1
-    assert verified_claims[0].source_ref == "https://en.wikipedia.org/wiki/Paris"
-    assert "[V]" in result.rendered_text
-    assert "[source:" in result.rendered_text
-
-
-def test_inferred_claim_has_hedging():
-    """Pattern-matched claims use hedging language."""
-    annotator = ClaimAnnotator()
-    response = "The weather is nice today. It might rain tomorrow."
-
-    result = annotator.annotate_claims(response)
-    inferred_claims = [c for c in result.claims if c.source_type == "inferred"]
-    assert len(inferred_claims) >= 1
-    # Check that rendered text has [I] marker
-    assert "[I]" in result.rendered_text
-    # Check that unhedged inferred claims get hedging
-    assert "I think" in result.rendered_text or "I believe" in result.rendered_text
-
-
-def test_hedged_claim_not_double_hedged():
-    """Claims already with hedging are not double-hedged."""
-    annotator = ClaimAnnotator()
-    response = "I think the sky is blue. It is a nice day."
-
-    result = annotator.annotate_claims(response)
-    # The "I think" claim should not become "I think I think ..."
-    assert "I think I think" not in result.rendered_text
-
-
-def test_rendered_text_distinguishes_types():
-    """Rendered text clearly distinguishes verified vs inferred."""
-    annotator = ClaimAnnotator()
-    verified = {"Earth is round": "https://science.org/earth"}
-    response = "Earth is round. Stars are far away."
-
-    result = annotator.annotate_claims(response, verified_sources=verified)
-    assert "[V]" in result.rendered_text  # verified marker
-    assert "[I]" in result.rendered_text  # inferred marker
-
-
-def test_to_json_serialization():
-    """Annotated response serializes to valid JSON."""
-    annotator = ClaimAnnotator()
-    response = "Test claim."
-    result = annotator.annotate_claims(response)
-    json_str = annotator.to_json(result)
-    parsed = json.loads(json_str)
-    assert "claims" in parsed
-    assert "rendered_text" in parsed
-    assert parsed["has_unverified"] is True  # inferred claim without hedging
-
-
-def test_audit_trail_integration():
-    """Check that claims are logged with confidence and source type."""
-    # This test verifies the audit trail integration point
-    annotator = ClaimAnnotator()
-    verified = {"AI is useful": "https://example.com/ai"}
-    response = "AI is useful. It can help with tasks."
-
-    result = annotator.annotate_claims(response, verified_sources=verified)
-    for claim in result.claims:
-        assert claim.source_type in ("verified", "inferred")
-        assert claim.confidence in ("high", "medium", "low", "unknown")
-        if claim.source_type == "verified":
-            assert claim.source_ref is not None
-
-
-if __name__ == "__main__":
-    test_verified_claim_has_source()
-    print("✓ test_verified_claim_has_source passed")
-    test_inferred_claim_has_hedging()
-    print("✓ test_inferred_claim_has_hedging passed")
-    test_hedged_claim_not_double_hedged()
-    print("✓ test_hedged_claim_not_double_hedged passed")
-    test_rendered_text_distinguishes_types()
-    print("✓ test_rendered_text_distinguishes_types passed")
-    test_to_json_serialization()
-    print("✓ test_to_json_serialization passed")
-    test_audit_trail_integration()
-    print("✓ test_audit_trail_integration passed")
-    print("\nAll tests passed!")