fix: use word-boundary regex for sensitive pattern matching to avoid false positives on max_tokens

The _SENSITIVE_PATTERNS list used simple substring matching, so "token"
matched "max_tokens", causing the distillation pipeline to block facts
about max_tokens parameters. Replaced with compiled regexes using
lookaround assertions so compound terms like max_tokens and num_tokens
are no longer falsely flagged.

Fixes #625

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

scripts/cycle_retro.py

@@ -54,6 +54,7 @@ REPO_ROOT = Path(__file__).resolve().parent.parent
 RETRO_FILE = REPO_ROOT / ".loop" / "retro" / "cycles.jsonl"
 SUMMARY_FILE = REPO_ROOT / ".loop" / "retro" / "summary.json"
 EPOCH_COUNTER_FILE = REPO_ROOT / ".loop" / "retro" / ".epoch_counter"
+CYCLE_RESULT_FILE = REPO_ROOT / ".loop" / "cycle_result.json"
 
 # How many recent entries to include in rolling summary
 SUMMARY_WINDOW = 50
@@ -246,9 +247,37 @@ def update_summary() -> None:
     SUMMARY_FILE.write_text(json.dumps(summary, indent=2) + "\n")
 
 
+def _load_cycle_result() -> dict:
+    """Read .loop/cycle_result.json if it exists; return empty dict on failure."""
+    if not CYCLE_RESULT_FILE.exists():
+        return {}
+    try:
+        raw = CYCLE_RESULT_FILE.read_text().strip()
+        # Strip hermes fence markers (```json ... ```) if present
+        if raw.startswith("```"):
+            lines = raw.splitlines()
+            lines = [l for l in lines if not l.startswith("```")]
+            raw = "\n".join(lines)
+        return json.loads(raw)
+    except (json.JSONDecodeError, OSError):
+        return {}
+
+
 def main() -> None:
     args = parse_args()
 
+    # Backfill from cycle_result.json when CLI args have defaults
+    cr = _load_cycle_result()
+    if cr:
+        if args.issue is None and cr.get("issue"):
+            args.issue = int(cr["issue"])
+        if args.type == "unknown" and cr.get("type"):
+            args.type = cr["type"]
+        if args.tests_passed == 0 and cr.get("tests_passed"):
+            args.tests_passed = int(cr["tests_passed"])
+        if not args.notes and cr.get("notes"):
+            args.notes = cr["notes"]
+
     # Auto-detect issue from branch when not explicitly provided
     if args.issue is None:
         args.issue = detect_issue_from_branch()

src/dashboard/app.py

@@ -46,6 +46,7 @@ from dashboard.routes.tasks import router as tasks_router
 from dashboard.routes.telegram import router as telegram_router
 from dashboard.routes.thinking import router as thinking_router
 from dashboard.routes.tools import router as tools_router
+from dashboard.routes.tower import router as tower_router
 from dashboard.routes.voice import router as voice_router
 from dashboard.routes.work_orders import router as work_orders_router
 from dashboard.routes.world import router as world_router
@@ -583,6 +584,7 @@ app.include_router(system_router)
 app.include_router(experiments_router)
 app.include_router(db_explorer_router)
 app.include_router(world_router)
+app.include_router(tower_router)
 
 
 @app.websocket("/ws")

src/dashboard/routes/system.py

@@ -16,52 +16,11 @@ router = APIRouter(tags=["system"])
 
 @router.get("/lightning/ledger", response_class=HTMLResponse)
 async def lightning_ledger(request: Request):
-    """Ledger and balance page."""
-    # Mock data for now, as this seems to be a UI-first feature
-    balance = {
-        "available_sats": 1337,
-        "incoming_total_sats": 2000,
-        "outgoing_total_sats": 663,
-        "fees_paid_sats": 5,
-        "net_sats": 1337,
-        "pending_incoming_sats": 0,
-        "pending_outgoing_sats": 0,
-    }
+    """Ledger and balance page backed by the in-memory Lightning ledger."""
+    from lightning.ledger import get_balance, get_transactions
 
-    # Mock transactions
-    from collections import namedtuple
-    from enum import Enum
-
-    class TxType(Enum):
-        incoming = "incoming"
-        outgoing = "outgoing"
-
-    class TxStatus(Enum):
-        completed = "completed"
-        pending = "pending"
-
-    Tx = namedtuple(
-        "Tx", ["tx_type", "status", "amount_sats", "payment_hash", "memo", "created_at"]
-    )
-
-    transactions = [
-        Tx(
-            TxType.outgoing,
-            TxStatus.completed,
-            50,
-            "hash1",
-            "Model inference",
-            "2026-03-04 10:00:00",
-        ),
-        Tx(
-            TxType.incoming,
-            TxStatus.completed,
-            1000,
-            "hash2",
-            "Manual deposit",
-            "2026-03-03 15:00:00",
-        ),
-    ]
+    balance = get_balance()
+    transactions = get_transactions()
 
     return templates.TemplateResponse(
         request,
@@ -70,7 +29,7 @@ async def lightning_ledger(request: Request):
             "balance": balance,
             "transactions": transactions,
             "tx_types": ["incoming", "outgoing"],
-            "tx_statuses": ["completed", "pending"],
+            "tx_statuses": ["pending", "settled", "failed", "expired"],
             "filter_type": None,
             "filter_status": None,
             "stats": {},

src/dashboard/routes/tower.py

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

src/dashboard/templates/mission_control.html

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

src/dashboard/templates/tower.html

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

src/infrastructure/router/__init__.py

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

src/infrastructure/router/api.py

@@ -8,6 +8,7 @@ from fastapi import APIRouter, Depends, HTTPException
 from pydantic import BaseModel
 
 from .cascade import CascadeRouter, get_router
+from .history import HealthHistoryStore, get_history_store
 
 logger = logging.getLogger(__name__)
 router = APIRouter(prefix="/api/v1/router", tags=["router"])
@@ -199,6 +200,17 @@ async def reload_config(
         raise HTTPException(status_code=500, detail=f"Reload failed: {exc}") from exc
 
 
+@router.get("/history")
+async def get_history(
+    hours: int = 24,
+    store: Annotated[HealthHistoryStore, Depends(get_history_store)] = None,
+) -> list[dict[str, Any]]:
+    """Get provider health history for the last N hours."""
+    if store is None:
+        store = get_history_store()
+    return store.get_history(hours=hours)
+
+
 @router.get("/config")
 async def get_config(
     cascade: Annotated[CascadeRouter, Depends(get_cascade_router)],

src/infrastructure/router/cascade.py

@@ -564,6 +564,7 @@ class CascadeRouter:
                 messages=messages,
                 model=model or provider.get_default_model(),
                 temperature=temperature,
+                max_tokens=max_tokens,
                 content_type=content_type,
             )
         elif provider.type == "openai":
@@ -604,6 +605,7 @@ class CascadeRouter:
         messages: list[dict],
         model: str,
         temperature: float,
+        max_tokens: int | None = None,
         content_type: ContentType = ContentType.TEXT,
     ) -> dict:
         """Call Ollama API with multi-modal support."""
@@ -614,13 +616,15 @@ class CascadeRouter:
         # Transform messages for Ollama format (including images)
         transformed_messages = self._transform_messages_for_ollama(messages)
 
+        options = {"temperature": temperature}
+        if max_tokens:
+            options["num_predict"] = max_tokens
+
         payload = {
             "model": model,
             "messages": transformed_messages,
             "stream": False,
-            "options": {
-                "temperature": temperature,
-            },
+            "options": options,
         }
 
         timeout = aiohttp.ClientTimeout(total=self.config.timeout_seconds)

src/infrastructure/router/history.py

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

src/lightning/__init__.py

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

src/lightning/factory.py

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

src/lightning/ledger.py

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

src/timmy/thinking.py

@@ -39,19 +39,21 @@ _DEFAULT_DB = Path("data/thoughts.db")
 # qwen3 and other reasoning models wrap chain-of-thought in <think> tags
 _THINK_TAG_RE = re.compile(r"<think>.*?</think>\s*", re.DOTALL)
 
-# Sensitive patterns that must never be stored as facts
-_SENSITIVE_PATTERNS = [
-    "token",
-    "password",
-    "secret",
-    "api_key",
-    "apikey",
-    "credential",
-    ".config/",
-    "/token",
-    "access_token",
-    "private_key",
-    "ssh_key",
+# Sensitive patterns that must never be stored as facts.
+# Uses compiled regexes with word boundaries so that compound technical
+# terms like "max_tokens" or "num_tokens" are NOT falsely flagged.
+_SENSITIVE_RE = [
+    re.compile(r"(?<![a-z_])token(?![a-z_])", re.IGNORECASE),  # "token" but not "max_tokens"
+    re.compile(r"password", re.IGNORECASE),
+    re.compile(r"secret", re.IGNORECASE),
+    re.compile(r"api_key", re.IGNORECASE),
+    re.compile(r"apikey", re.IGNORECASE),
+    re.compile(r"credential", re.IGNORECASE),
+    re.compile(r"\.config/"),
+    re.compile(r"/token\b"),
+    re.compile(r"access_token", re.IGNORECASE),
+    re.compile(r"private_key", re.IGNORECASE),
+    re.compile(r"ssh_key", re.IGNORECASE),
 ]
 
 # Meta-observation phrases to filter out from distilled facts
@@ -548,7 +550,7 @@ class ThinkingEngine:
             fact_lower = fact.lower()
 
             # Block sensitive information
-            if any(pat in fact_lower for pat in _SENSITIVE_PATTERNS):
+            if any(pat.search(fact) for pat in _SENSITIVE_RE):
                 logger.warning("Distill: blocked sensitive fact: %s", fact[:60])
                 continue
 

static/css/mission-control.css

@@ -2493,3 +2493,57 @@
 .db-cell { max-width: 300px; overflow: hidden; text-overflow: ellipsis; white-space: nowrap; }
 .db-cell:hover { white-space: normal; word-break: break-all; }
 .db-truncated { font-size: 0.7rem; color: var(--amber); padding: 0.3rem 0; }
+
+/* ── Tower ────────────────────────────────────────────────────────────── */
+.tower-container { max-width: 1400px; margin: 0 auto; }
+.tower-header { margin-bottom: 1rem; }
+.tower-title { font-size: 1.6rem; font-weight: 700; color: var(--green); letter-spacing: 0.15em; }
+.tower-subtitle { font-size: 0.85rem; color: var(--text-dim); }
+
+.tower-conn-badge { font-size: 0.7rem; font-weight: 600; padding: 2px 8px; border-radius: 3px; letter-spacing: 0.08em; }
+.tower-conn-live { color: var(--green); border: 1px solid var(--green); }
+.tower-conn-offline { color: var(--red); border: 1px solid var(--red); }
+.tower-conn-connecting { color: var(--amber); border: 1px solid var(--amber); }
+
+.tower-phase-card { min-height: 300px; }
+.tower-phase-thinking { border-left: 3px solid var(--purple); }
+.tower-phase-predicting { border-left: 3px solid var(--orange); }
+.tower-phase-advising { border-left: 3px solid var(--green); }
+.tower-scroll { max-height: 50vh; overflow-y: auto; }
+.tower-empty { text-align: center; color: var(--text-dim); padding: 16px; font-size: 0.85rem; }
+
+.tower-stat-grid { display: grid; grid-template-columns: repeat(4, 1fr); gap: 0.5rem; text-align: center; }
+.tower-stat-label { display: block; font-size: 0.65rem; color: var(--text-dim); letter-spacing: 0.1em; }
+.tower-stat-value { display: block; font-size: 1.1rem; font-weight: 700; color: var(--text-bright); }
+
+.tower-event { padding: 8px; margin-bottom: 6px; border-left: 3px solid var(--border); border-radius: 3px; background: var(--bg-card); }
+.tower-etype-task_posted { border-left-color: var(--purple); }
+.tower-etype-bid_submitted { border-left-color: var(--orange); }
+.tower-etype-task_completed { border-left-color: var(--green); }
+.tower-etype-task_failed { border-left-color: var(--red); }
+.tower-etype-agent_joined { border-left-color: var(--purple); }
+.tower-etype-tool_executed { border-left-color: var(--amber); }
+.tower-ev-head { display: flex; justify-content: space-between; align-items: center; margin-bottom: 4px; }
+.tower-ev-badge { font-size: 0.65rem; font-weight: 600; color: var(--text-bright); letter-spacing: 0.08em; }
+.tower-ev-dots { font-size: 0.6rem; color: var(--amber); }
+.tower-ev-desc { font-size: 0.8rem; color: var(--text); }
+.tower-ev-time { font-size: 0.65rem; color: var(--text-dim); margin-top: 2px; }
+
+.tower-pred { padding: 8px; margin-bottom: 6px; border-radius: 3px; background: var(--bg-card); border-left: 3px solid var(--orange); }
+.tower-pred-done { border-left-color: var(--green); }
+.tower-pred-pending { border-left-color: var(--amber); }
+.tower-pred-head { display: flex; justify-content: space-between; align-items: center; }
+.tower-pred-task { font-size: 0.75rem; font-weight: 600; color: var(--text-bright); font-family: monospace; }
+.tower-pred-acc { font-size: 0.75rem; font-weight: 700; }
+.tower-pred-detail { font-size: 0.75rem; color: var(--text-dim); margin-top: 4px; }
+
+.tower-advisory { padding: 8px; margin-bottom: 6px; border-radius: 3px; background: var(--bg-card); border-left: 3px solid var(--border); }
+.tower-adv-high { border-left-color: var(--red); }
+.tower-adv-medium { border-left-color: var(--orange); }
+.tower-adv-low { border-left-color: var(--green); }
+.tower-adv-head { display: flex; justify-content: space-between; font-size: 0.65rem; margin-bottom: 4px; }
+.tower-adv-cat { font-weight: 600; color: var(--text-dim); letter-spacing: 0.08em; }
+.tower-adv-prio { font-weight: 700; color: var(--amber); }
+.tower-adv-title { font-size: 0.85rem; font-weight: 600; color: var(--text-bright); }
+.tower-adv-detail { font-size: 0.8rem; color: var(--text); margin-top: 2px; }
+.tower-adv-action { font-size: 0.75rem; color: var(--green); margin-top: 4px; font-style: italic; }

tests/dashboard/test_tower.py

@@ -0,0 +1,187 @@
+"""Tests for Tower dashboard route (/tower)."""
+
+from unittest.mock import MagicMock, patch
+
+
+def _mock_spark_engine():
+    """Return a mock spark_engine with realistic return values."""
+    engine = MagicMock()
+
+    engine.status.return_value = {
+        "enabled": True,
+        "events_captured": 5,
+        "memories_stored": 3,
+        "predictions": {"total": 2, "avg_accuracy": 0.85},
+        "event_types": {
+            "task_posted": 2,
+            "bid_submitted": 1,
+            "task_assigned": 1,
+            "task_completed": 1,
+            "task_failed": 0,
+            "agent_joined": 0,
+            "tool_executed": 0,
+            "creative_step": 0,
+        },
+    }
+
+    event = MagicMock()
+    event.event_type = "task_completed"
+    event.description = "Task finished"
+    event.importance = 0.8
+    event.created_at = "2026-01-01T00:00:00"
+    event.agent_id = "agent-1234-abcd"
+    event.task_id = "task-5678-efgh"
+    event.data = '{"result": "ok"}'
+    engine.get_timeline.return_value = [event]
+
+    pred = MagicMock()
+    pred.task_id = "task-5678-efgh"
+    pred.accuracy = 0.9
+    pred.evaluated_at = "2026-01-01T01:00:00"
+    pred.created_at = "2026-01-01T00:30:00"
+    pred.predicted_value = '{"outcome": "success"}'
+    engine.get_predictions.return_value = [pred]
+
+    advisory = MagicMock()
+    advisory.category = "performance"
+    advisory.priority = "high"
+    advisory.title = "Slow tasks"
+    advisory.detail = "Tasks taking longer than expected"
+    advisory.suggested_action = "Scale up workers"
+    engine.get_advisories.return_value = [advisory]
+
+    return engine
+
+
+class TestTowerUI:
+    """Tests for GET /tower endpoint."""
+
+    @patch("dashboard.routes.tower.spark_engine", new_callable=_mock_spark_engine)
+    def test_tower_returns_200(self, mock_engine, client):
+        response = client.get("/tower")
+        assert response.status_code == 200
+
+    @patch("dashboard.routes.tower.spark_engine", new_callable=_mock_spark_engine)
+    def test_tower_returns_html(self, mock_engine, client):
+        response = client.get("/tower")
+        assert "text/html" in response.headers["content-type"]
+
+    @patch("dashboard.routes.tower.spark_engine", new_callable=_mock_spark_engine)
+    def test_tower_contains_dashboard_content(self, mock_engine, client):
+        response = client.get("/tower")
+        body = response.text
+        assert "tower" in body.lower() or "spark" in body.lower()
+
+
+class TestSparkSnapshot:
+    """Tests for _spark_snapshot helper."""
+
+    @patch("dashboard.routes.tower.spark_engine", new_callable=_mock_spark_engine)
+    def test_snapshot_structure(self, mock_engine):
+        from dashboard.routes.tower import _spark_snapshot
+
+        snap = _spark_snapshot()
+        assert snap["type"] == "spark_state"
+        assert "status" in snap
+        assert "events" in snap
+        assert "predictions" in snap
+        assert "advisories" in snap
+
+    @patch("dashboard.routes.tower.spark_engine", new_callable=_mock_spark_engine)
+    def test_snapshot_events_parsed(self, mock_engine):
+        from dashboard.routes.tower import _spark_snapshot
+
+        snap = _spark_snapshot()
+        ev = snap["events"][0]
+        assert ev["event_type"] == "task_completed"
+        assert ev["importance"] == 0.8
+        assert ev["agent_id"] == "agent-12"
+        assert ev["task_id"] == "task-567"
+        assert ev["data"] == {"result": "ok"}
+
+    @patch("dashboard.routes.tower.spark_engine", new_callable=_mock_spark_engine)
+    def test_snapshot_predictions_parsed(self, mock_engine):
+        from dashboard.routes.tower import _spark_snapshot
+
+        snap = _spark_snapshot()
+        pred = snap["predictions"][0]
+        assert pred["task_id"] == "task-567"
+        assert pred["accuracy"] == 0.9
+        assert pred["evaluated"] is True
+        assert pred["predicted"] == {"outcome": "success"}
+
+    @patch("dashboard.routes.tower.spark_engine", new_callable=_mock_spark_engine)
+    def test_snapshot_advisories_parsed(self, mock_engine):
+        from dashboard.routes.tower import _spark_snapshot
+
+        snap = _spark_snapshot()
+        adv = snap["advisories"][0]
+        assert adv["category"] == "performance"
+        assert adv["priority"] == "high"
+        assert adv["title"] == "Slow tasks"
+        assert adv["suggested_action"] == "Scale up workers"
+
+    @patch("dashboard.routes.tower.spark_engine")
+    def test_snapshot_handles_empty_state(self, mock_engine):
+        mock_engine.status.return_value = {"enabled": False}
+        mock_engine.get_timeline.return_value = []
+        mock_engine.get_predictions.return_value = []
+        mock_engine.get_advisories.return_value = []
+
+        from dashboard.routes.tower import _spark_snapshot
+
+        snap = _spark_snapshot()
+        assert snap["events"] == []
+        assert snap["predictions"] == []
+        assert snap["advisories"] == []
+
+    @patch("dashboard.routes.tower.spark_engine")
+    def test_snapshot_handles_invalid_json_data(self, mock_engine):
+        mock_engine.status.return_value = {"enabled": True}
+
+        event = MagicMock()
+        event.event_type = "test"
+        event.description = "bad data"
+        event.importance = 0.5
+        event.created_at = "2026-01-01T00:00:00"
+        event.agent_id = None
+        event.task_id = None
+        event.data = "not-json{"
+        mock_engine.get_timeline.return_value = [event]
+
+        pred = MagicMock()
+        pred.task_id = None
+        pred.accuracy = None
+        pred.evaluated_at = None
+        pred.created_at = "2026-01-01T00:00:00"
+        pred.predicted_value = None
+        mock_engine.get_predictions.return_value = [pred]
+
+        mock_engine.get_advisories.return_value = []
+
+        from dashboard.routes.tower import _spark_snapshot
+
+        snap = _spark_snapshot()
+        ev = snap["events"][0]
+        assert ev["data"] == {}
+        assert "agent_id" not in ev
+        assert "task_id" not in ev
+
+        pred = snap["predictions"][0]
+        assert pred["task_id"] == "?"
+        assert pred["predicted"] == {}
+
+
+class TestTowerWebSocket:
+    """Tests for WS /tower/ws endpoint."""
+
+    @patch("dashboard.routes.tower.spark_engine", new_callable=_mock_spark_engine)
+    @patch("dashboard.routes.tower._PUSH_INTERVAL", 0)
+    def test_ws_sends_initial_snapshot(self, mock_engine, client):
+        import json
+
+        with client.websocket_connect("/tower/ws") as ws:
+            data = json.loads(ws.receive_text())
+            assert data["type"] == "spark_state"
+            assert "status" in data
+            assert "events" in data

tests/infrastructure/test_router_history.py

@@ -0,0 +1,149 @@
+"""Tests for provider health history store and API endpoint."""
+
+import time
+from datetime import UTC, datetime, timedelta
+from unittest.mock import MagicMock
+
+import pytest
+from src.infrastructure.router.history import HealthHistoryStore
+
+
+@pytest.fixture
+def store():
+    """In-memory history store for testing."""
+    s = HealthHistoryStore(db_path=":memory:")
+    yield s
+    s.close()
+
+
+@pytest.fixture
+def sample_providers():
+    return [
+        {
+            "name": "anthropic",
+            "status": "healthy",
+            "error_rate": 0.01,
+            "avg_latency_ms": 250.5,
+            "circuit_state": "closed",
+            "total_requests": 100,
+        },
+        {
+            "name": "local",
+            "status": "degraded",
+            "error_rate": 0.15,
+            "avg_latency_ms": 80.0,
+            "circuit_state": "closed",
+            "total_requests": 50,
+        },
+    ]
+
+
+def test_record_and_retrieve(store, sample_providers):
+    store.record_snapshot(sample_providers)
+    history = store.get_history(hours=1)
+    assert len(history) == 1
+    assert len(history[0]["providers"]) == 2
+    assert history[0]["providers"][0]["name"] == "anthropic"
+    assert history[0]["providers"][1]["name"] == "local"
+    assert "timestamp" in history[0]
+
+
+def test_multiple_snapshots(store, sample_providers):
+    store.record_snapshot(sample_providers)
+    time.sleep(0.01)
+    store.record_snapshot(sample_providers)
+    history = store.get_history(hours=1)
+    assert len(history) == 2
+
+
+def test_hours_filtering(store, sample_providers):
+    old_ts = (datetime.now(UTC) - timedelta(hours=48)).isoformat()
+    store._conn.execute(
+        """INSERT INTO snapshots
+           (timestamp, provider_name, status, error_rate,
+            avg_latency_ms, circuit_state, total_requests)
+           VALUES (?, ?, ?, ?, ?, ?, ?)""",
+        (old_ts, "anthropic", "healthy", 0.0, 100.0, "closed", 10),
+    )
+    store._conn.commit()
+    store.record_snapshot(sample_providers)
+
+    history = store.get_history(hours=24)
+    assert len(history) == 1
+
+    history = store.get_history(hours=72)
+    assert len(history) == 2
+
+
+def test_prune(store, sample_providers):
+    old_ts = (datetime.now(UTC) - timedelta(hours=200)).isoformat()
+    store._conn.execute(
+        """INSERT INTO snapshots
+           (timestamp, provider_name, status, error_rate,
+            avg_latency_ms, circuit_state, total_requests)
+           VALUES (?, ?, ?, ?, ?, ?, ?)""",
+        (old_ts, "anthropic", "healthy", 0.0, 100.0, "closed", 10),
+    )
+    store._conn.commit()
+    store.record_snapshot(sample_providers)
+
+    deleted = store.prune(keep_hours=168)
+    assert deleted == 1
+    history = store.get_history(hours=999)
+    assert len(history) == 1
+
+
+def test_empty_history(store):
+    assert store.get_history(hours=24) == []
+
+
+def test_capture_snapshot_from_router(store):
+    mock_metrics = MagicMock()
+    mock_metrics.error_rate = 0.05
+    mock_metrics.avg_latency_ms = 200.0
+    mock_metrics.total_requests = 42
+
+    mock_provider = MagicMock()
+    mock_provider.name = "test-provider"
+    mock_provider.status.value = "healthy"
+    mock_provider.metrics = mock_metrics
+    mock_provider.circuit_state.value = "closed"
+
+    mock_router = MagicMock()
+    mock_router.providers = [mock_provider]
+
+    store._capture_snapshot(mock_router)
+    history = store.get_history(hours=1)
+    assert len(history) == 1
+    p = history[0]["providers"][0]
+    assert p["name"] == "test-provider"
+    assert p["status"] == "healthy"
+    assert p["error_rate"] == 0.05
+    assert p["total_requests"] == 42
+
+
+def test_history_api_endpoint(store, sample_providers):
+    """GET /api/v1/router/history returns snapshot data."""
+    store.record_snapshot(sample_providers)
+
+    from fastapi import FastAPI
+    from fastapi.testclient import TestClient
+    from src.infrastructure.router.api import get_cascade_router
+    from src.infrastructure.router.api import router as api_router
+    from src.infrastructure.router.history import get_history_store
+
+    app = FastAPI()
+    app.include_router(api_router)
+
+    app.dependency_overrides[get_history_store] = lambda: store
+    app.dependency_overrides[get_cascade_router] = lambda: MagicMock()
+
+    client = TestClient(app)
+    resp = client.get("/api/v1/router/history?hours=1")
+    assert resp.status_code == 200
+    data = resp.json()
+    assert len(data) == 1
+    assert len(data[0]["providers"]) == 2
+    assert data[0]["providers"][0]["name"] == "anthropic"
+
+    app.dependency_overrides.clear()

tests/timmy/test_cli.py

@@ -56,7 +56,7 @@ def test_think_sends_topic_to_agent():
 
 
 def test_think_ignores_model_size_option():
-    """think --model-size is accepted but not forwarded to create_timmy."""
+    """think --model-size 70b must not forward model_size to create_timmy."""
     mock_timmy = MagicMock()
 
     with patch("timmy.cli.create_timmy", return_value=mock_timmy) as mock_create:

tests/timmy/test_thinking.py

@@ -1188,3 +1188,42 @@ def test_references_real_files_blocks_mixed(tmp_path):
     # Mix of real and fake files — should fail because of the fake one
     text = "Fix src/timmy/thinking.py and also src/timmy/nonexistent_module.py for the memory leak."
     assert ThinkingEngine._references_real_files(text) is False
+
+
+# ---------------------------------------------------------------------------
+# Sensitive-pattern regression: max_tokens must NOT be flagged (#625)
+# ---------------------------------------------------------------------------
+
+
+def test_sensitive_patterns_allow_max_tokens():
+    """_SENSITIVE_RE should not flag 'max_tokens' as sensitive (#625)."""
+    from timmy.thinking import _SENSITIVE_RE
+
+    safe_facts = [
+        "The cascade router passes max_tokens to Ollama provider.",
+        "max_tokens=request.max_tokens in the completion call.",
+        "num_tokens defaults to 2048.",
+        "total_prompt_tokens is tracked in stats.",
+    ]
+    for fact in safe_facts:
+        assert not any(pat.search(fact) for pat in _SENSITIVE_RE), (
+            f"False positive: {fact!r} was flagged as sensitive"
+        )
+
+
+def test_sensitive_patterns_still_block_real_secrets():
+    """_SENSITIVE_RE should still block actual secrets."""
+    from timmy.thinking import _SENSITIVE_RE
+
+    dangerous_facts = [
+        "The token is abc123def456.",
+        "Set password to hunter2.",
+        "api_key = sk-live-xyz",
+        "Found credential in .env file.",
+        "access_token expired yesterday.",
+        "private_key stored in vault.",
+    ]
+    for fact in dangerous_facts:
+        assert any(pat.search(fact) for pat in _SENSITIVE_RE), (
+            f"Missed secret: {fact!r} was NOT flagged as sensitive"
+        )

tests/unit/test_lightning.py

@@ -0,0 +1,109 @@
+"""Unit tests for the lightning package (factory + ledger)."""
+
+from __future__ import annotations
+
+import pytest
+
+from lightning.factory import Invoice, MockBackend, get_backend
+from lightning.ledger import (
+    TxStatus,
+    TxType,
+    clear,
+    create_invoice_entry,
+    get_balance,
+    get_transactions,
+    mark_settled,
+)
+
+
+@pytest.fixture(autouse=True)
+def _clean_ledger():
+    """Reset the in-memory ledger between tests."""
+    clear()
+    yield
+    clear()
+
+
+# ── Factory tests ────────────────────────────────────────────────────
+
+
+class TestMockBackend:
+    def test_create_invoice_returns_invoice(self):
+        backend = MockBackend()
+        inv = backend.create_invoice(100, "test memo")
+        assert isinstance(inv, Invoice)
+        assert inv.amount_sats == 100
+        assert inv.memo == "test memo"
+        assert len(inv.payment_hash) == 64  # SHA-256 hex
+        assert inv.payment_request.startswith("lnbc")
+
+    def test_invoices_have_unique_hashes(self):
+        backend = MockBackend()
+        a = backend.create_invoice(10)
+        b = backend.create_invoice(10)
+        assert a.payment_hash != b.payment_hash
+
+
+class TestGetBackend:
+    def test_returns_mock_backend(self):
+        backend = get_backend()
+        assert isinstance(backend, MockBackend)
+
+
+# ── Ledger tests ─────────────────────────────────────────────────────
+
+
+class TestLedger:
+    def test_create_invoice_entry(self):
+        entry = create_invoice_entry(
+            payment_hash="abc123",
+            amount_sats=500,
+            memo="test",
+            source="unit_test",
+        )
+        assert entry.tx_type == TxType.incoming
+        assert entry.status == TxStatus.pending
+        assert entry.amount_sats == 500
+
+    def test_mark_settled(self):
+        create_invoice_entry(payment_hash="hash1", amount_sats=100)
+        result = mark_settled("hash1", preimage="secret")
+        assert result is not None
+        assert result.status == TxStatus.settled
+        assert result.preimage == "secret"
+        assert result.settled_at != ""
+
+    def test_mark_settled_unknown_hash(self):
+        assert mark_settled("nonexistent") is None
+
+    def test_get_balance_empty(self):
+        bal = get_balance()
+        assert bal["net_sats"] == 0
+        assert bal["available_sats"] == 0
+
+    def test_get_balance_with_settled(self):
+        create_invoice_entry(payment_hash="h1", amount_sats=1000)
+        mark_settled("h1")
+        bal = get_balance()
+        assert bal["incoming_total_sats"] == 1000
+        assert bal["net_sats"] == 1000
+        assert bal["available_sats"] == 1000
+
+    def test_get_balance_pending_not_counted(self):
+        create_invoice_entry(payment_hash="h2", amount_sats=500)
+        bal = get_balance()
+        assert bal["incoming_total_sats"] == 0
+        assert bal["pending_incoming_sats"] == 500
+
+    def test_get_transactions_returns_entries(self):
+        create_invoice_entry(payment_hash="t1", amount_sats=10)
+        create_invoice_entry(payment_hash="t2", amount_sats=20)
+        txs = get_transactions()
+        assert len(txs) == 2
+
+    def test_get_transactions_filter_by_status(self):
+        create_invoice_entry(payment_hash="f1", amount_sats=10)
+        create_invoice_entry(payment_hash="f2", amount_sats=20)
+        mark_settled("f1")
+        assert len(get_transactions(status="settled")) == 1
+        assert len(get_transactions(status="pending")) == 1