feat: harden Bezalel tailscale bootstrap packet (#535)

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:

docs/BEZALEL_TAILSCALE_BOOTSTRAP.md

@@ -0,0 +1,96 @@
+# Bezalel Tailscale Bootstrap
+
+Refs #535
+
+This is the repo-side operator packet for installing Tailscale on the Bezalel VPS and verifying the internal network path for federation work.
+
+Important truth:
+- issue #535 names `104.131.15.18`
+- older Bezalel control-plane docs also mention `159.203.146.185`
+- the current source of truth in this repo is `ansible/inventory/hosts.ini`, which currently resolves `bezalel` to `67.205.155.108`
+
+Because of that drift, `scripts/bezalel_tailscale_bootstrap.py` now resolves the target host from `ansible/inventory/hosts.ini` by default instead of trusting a stale hardcoded IP.
+
+## What the script does
+
+`python3 scripts/bezalel_tailscale_bootstrap.py`
+
+Safe by default:
+- builds the remote bootstrap script
+- writes it locally to `/tmp/bezalel_tailscale_bootstrap.sh`
+- prints the SSH command needed to run it
+- does **not** touch the VPS unless `--apply` is passed
+
+When applied, the remote script does all of the issue’s repo-side bootstrap steps:
+- installs Tailscale
+- runs `tailscale up --ssh --hostname bezalel`
+- appends the provided Mac SSH public key to `~/.ssh/authorized_keys`
+- prints `tailscale status --json`
+- pings the expected peer targets:
+  - Mac: `100.124.176.28`
+  - Ezra: `100.126.61.75`
+
+## Required secrets / inputs
+
+- Tailscale auth key
+- Mac SSH public key
+
+Provide them either directly or through files:
+- `--auth-key` or `--auth-key-file`
+- `--ssh-public-key` or `--ssh-public-key-file`
+
+## Dry-run example
+
+```bash
+python3 scripts/bezalel_tailscale_bootstrap.py \
+  --auth-key-file ~/.config/tailscale/auth_key \
+  --ssh-public-key-file ~/.ssh/id_ed25519.pub \
+  --json
+```
+
+This prints:
+- resolved host
+- host source (`inventory:<path>` when pulled from `ansible/inventory/hosts.ini`)
+- local script path
+- SSH command to execute
+- peer targets
+
+## Apply example
+
+```bash
+python3 scripts/bezalel_tailscale_bootstrap.py \
+  --auth-key-file ~/.config/tailscale/auth_key \
+  --ssh-public-key-file ~/.ssh/id_ed25519.pub \
+  --apply \
+  --json
+```
+
+## Verifying success after apply
+
+The script now parses the remote stdout into structured verification data:
+- `verification.tailscale.self.tailscale_ips`
+- `verification.tailscale.self.dns_name`
+- `verification.peers`
+- `verification.ping_ok`
+
+A successful run should show:
+- at least one Bezalel Tailscale IP under `tailscale_ips`
+- `ping_ok.mac = 100.124.176.28`
+- `ping_ok.ezra = 100.126.61.75`
+
+## Expected remote install commands
+
+```bash
+curl -fsSL https://tailscale.com/install.sh | sh
+tailscale up --ssh --hostname bezalel
+install -d -m 700 ~/.ssh
+touch ~/.ssh/authorized_keys && chmod 600 ~/.ssh/authorized_keys
+tailscale status --json
+```
+
+## Why this PR does not claim live completion
+
+This repo can safely ship the bootstrap script, host resolution logic, structured proof parsing, and operator packet.
+It cannot honestly claim that Bezalel was actually joined to the tailnet unless a human/operator runs the script with a real auth key and real SSH access to the VPS.
+
+That means the correct PR language for #535 is advancement, not pretend closure.

docs/RUNBOOK_INDEX.md

@@ -14,6 +14,7 @@ Quick-reference index for common operational tasks across the Timmy Foundation i
 | Agent scorecard | fleet-ops | `python3 scripts/agent_scorecard.py` |
 | View fleet manifest | fleet-ops | `cat manifest.yaml` |
 | Run nightly codebase genome pass | timmy-home | `python3 scripts/codebase_genome_nightly.py --dry-run` |
+| Prepare Bezalel Tailscale bootstrap | timmy-home | `python3 scripts/bezalel_tailscale_bootstrap.py --auth-key-file <path> --ssh-public-key-file <path> --json` |
 
 ## the-nexus (Frontend + Brain)
 

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; }

scripts/bezalel_tailscale_bootstrap.py

@@ -16,11 +16,14 @@ import argparse
 import json
 import shlex
 import subprocess
+import re
+from json import JSONDecoder
 from pathlib import Path
 from typing import Any
 
-DEFAULT_HOST = "159.203.146.185"
+DEFAULT_HOST = "67.205.155.108"
 DEFAULT_HOSTNAME = "bezalel"
+DEFAULT_INVENTORY_PATH = Path(__file__).resolve().parents[1] / "ansible" / "inventory" / "hosts.ini"
 DEFAULT_PEERS = {
     "mac": "100.124.176.28",
     "ezra": "100.126.61.75",
@@ -66,6 +69,37 @@ def parse_tailscale_status(payload: dict[str, Any]) -> dict[str, Any]:
     }
 
 
+def resolve_host(host: str | None, inventory_path: Path = DEFAULT_INVENTORY_PATH, hostname: str = DEFAULT_HOSTNAME) -> tuple[str, str]:
+    if host:
+        return host, "explicit"
+    if inventory_path.exists():
+        pattern = re.compile(rf"^{re.escape(hostname)}\s+.*ansible_host=([^\s]+)")
+        for line in inventory_path.read_text().splitlines():
+            match = pattern.search(line.strip())
+            if match:
+                return match.group(1), f"inventory:{inventory_path}"
+    return DEFAULT_HOST, "default"
+
+
+def parse_apply_output(stdout: str) -> dict[str, Any]:
+    result: dict[str, Any] = {"tailscale": None, "ping_ok": {}}
+    text = stdout or ""
+    start = text.find("{")
+    if start != -1:
+        try:
+            payload, _ = JSONDecoder().raw_decode(text[start:])
+            if isinstance(payload, dict):
+                result["tailscale"] = parse_tailscale_status(payload)
+        except Exception:
+            pass
+
+    for line in text.splitlines():
+        if line.startswith("PING_OK:"):
+            _, name, ip = line.split(":", 2)
+            result["ping_ok"][name] = ip
+    return result
+
+
 def build_ssh_command(host: str, remote_script_path: str = "/tmp/bezalel_tailscale_bootstrap.sh") -> list[str]:
     return ["ssh", host, f"bash {shlex.quote(remote_script_path)}"]
 
@@ -89,8 +123,9 @@ def parse_peer_args(items: list[str]) -> dict[str, str]:
 
 def parse_args() -> argparse.Namespace:
     parser = argparse.ArgumentParser(description="Prepare or execute Tailscale bootstrap for the Bezalel VPS.")
-    parser.add_argument("--host", default=DEFAULT_HOST)
+    parser.add_argument("--host")
     parser.add_argument("--hostname", default=DEFAULT_HOSTNAME)
+    parser.add_argument("--inventory-path", type=Path, default=DEFAULT_INVENTORY_PATH)
     parser.add_argument("--auth-key", help="Tailscale auth key")
     parser.add_argument("--auth-key-file", type=Path, help="Path to file containing the Tailscale auth key")
     parser.add_argument("--ssh-public-key", help="SSH public key to append to authorized_keys")
@@ -116,6 +151,7 @@ def main() -> None:
     auth_key = _read_secret(args.auth_key, args.auth_key_file)
     ssh_public_key = _read_secret(args.ssh_public_key, args.ssh_public_key_file)
     peers = parse_peer_args(args.peer)
+    resolved_host, host_source = resolve_host(args.host, args.inventory_path, args.hostname)
 
     if not auth_key:
         raise SystemExit("Missing Tailscale auth key. Use --auth-key or --auth-key-file.")
@@ -126,28 +162,31 @@ def main() -> None:
     write_script(args.script_out, script)
 
     payload: dict[str, Any] = {
-        "host": args.host,
+        "host": resolved_host,
+        "host_source": host_source,
         "hostname": args.hostname,
+        "inventory_path": str(args.inventory_path),
         "script_out": str(args.script_out),
         "remote_script_path": args.remote_script_path,
-        "ssh_command": build_ssh_command(args.host, args.remote_script_path),
+        "ssh_command": build_ssh_command(resolved_host, args.remote_script_path),
         "peer_targets": peers,
         "applied": False,
     }
 
     if args.apply:
-        result = run_remote(args.host, args.remote_script_path)
+        result = run_remote(resolved_host, args.remote_script_path)
         payload["applied"] = True
         payload["exit_code"] = result.returncode
         payload["stdout"] = result.stdout
         payload["stderr"] = result.stderr
+        payload["verification"] = parse_apply_output(result.stdout)
 
     if args.json:
         print(json.dumps(payload, indent=2))
         return
 
     print("--- Bezalel Tailscale Bootstrap ---")
-    print(f"Host: {args.host}")
+    print(f"Host: {resolved_host} ({host_source})")
     print(f"Local script: {args.script_out}")
     print("SSH command: " + " ".join(payload["ssh_command"]))
     if args.apply:

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/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_bezalel_tailscale_bootstrap.py

@@ -2,9 +2,12 @@ from scripts.bezalel_tailscale_bootstrap import (
     DEFAULT_PEERS,
     build_remote_script,
     build_ssh_command,
+    parse_apply_output,
     parse_peer_args,
     parse_tailscale_status,
+    resolve_host,
 )
+from pathlib import Path
 
 
 def test_build_remote_script_contains_install_up_and_key_append():
@@ -78,3 +81,46 @@ def test_parse_peer_args_merges_overrides_into_defaults():
         "ezra": "100.126.61.76",
         "forge": "100.70.0.9",
     }
+
+
+def test_resolve_host_prefers_inventory_over_stale_default(tmp_path: Path):
+    inventory = tmp_path / "hosts.ini"
+    inventory.write_text(
+        "[fleet]\n"
+        "ezra ansible_host=143.198.27.163 ansible_user=root\n"
+        "bezalel ansible_host=67.205.155.108 ansible_user=root\n"
+    )
+
+    host, source = resolve_host(None, inventory)
+
+    assert host == "67.205.155.108"
+    assert source == f"inventory:{inventory}"
+
+
+def test_parse_apply_output_extracts_status_and_ping_markers():
+    stdout = (
+        '{"Self": {"HostName": "bezalel", "DNSName": "bezalel.tailnet.ts.net", "TailscaleIPs": ["100.90.0.10"]}, '
+        '"Peer": {"node-1": {"HostName": "ezra", "TailscaleIPs": ["100.126.61.75"]}}}'
+        "\nPING_OK:mac:100.124.176.28\n"
+        "PING_OK:ezra:100.126.61.75\n"
+    )
+
+    result = parse_apply_output(stdout)
+
+    assert result["tailscale"]["self"]["tailscale_ips"] == ["100.90.0.10"]
+    assert result["ping_ok"] == {"mac": "100.124.176.28", "ezra": "100.126.61.75"}
+
+
+def test_runbook_doc_exists_and_mentions_inventory_auth_and_peer_checks():
+    doc = Path("docs/BEZALEL_TAILSCALE_BOOTSTRAP.md")
+    assert doc.exists(), "missing docs/BEZALEL_TAILSCALE_BOOTSTRAP.md"
+    text = doc.read_text()
+    assert "ansible/inventory/hosts.ini" in text
+    assert "tailscale up" in text
+    assert "authorized_keys" in text
+    assert "100.124.176.28" in text
+    assert "100.126.61.75" in text
+
+    runbook = Path("docs/RUNBOOK_INDEX.md").read_text()
+    assert "Prepare Bezalel Tailscale bootstrap" in runbook
+    assert "scripts/bezalel_tailscale_bootstrap.py" in runbook

tests/timmy/test_audit_trail.py

@@ -19,7 +19,7 @@ from pathlib import Path
 
 import pytest
 
-sys.path.insert(0, str(Path(__file__).resolve().parent.parent.parent / "src"))
+sys.path.insert(0, str(Path(__file__).resolve().parent.parent / "src"))
 from timmy.audit_trail import AuditTrail, AuditEntry
 
 

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!")