refactor: break up delegate_to_kimi into helpers

Extract _find_kimi_cli, _resolve_workdir, and _run_kimi from the 68-line
delegate_to_kimi function, reducing it to ~15 lines.

Fixes #635

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

src/dashboard/routes/calm.py

@@ -38,6 +38,56 @@ def get_later_tasks(db: Session) -> list[Task]:
     )
 
 
+def _create_mit_tasks(db: Session, titles: list[str | None]) -> list[int]:
+    """Create MIT tasks from a list of titles, return their IDs."""
+    task_ids: list[int] = []
+    for title in titles:
+        if title:
+            task = Task(
+                title=title,
+                is_mit=True,
+                state=TaskState.LATER,
+                certainty=TaskCertainty.SOFT,
+            )
+            db.add(task)
+            db.commit()
+            db.refresh(task)
+            task_ids.append(task.id)
+    return task_ids
+
+
+def _create_other_tasks(db: Session, other_tasks: str):
+    """Create non-MIT tasks from newline-separated text."""
+    for line in other_tasks.split("\n"):
+        line = line.strip()
+        if line:
+            task = Task(
+                title=line,
+                state=TaskState.LATER,
+                certainty=TaskCertainty.FUZZY,
+            )
+            db.add(task)
+
+
+def _seed_now_next(db: Session):
+    """Set initial NOW/NEXT states when both slots are empty."""
+    if get_now_task(db) or get_next_task(db):
+        return
+    later_tasks = (
+        db.query(Task)
+        .filter(Task.state == TaskState.LATER)
+        .order_by(Task.is_mit.desc(), Task.sort_order)
+        .all()
+    )
+    if later_tasks:
+        later_tasks[0].state = TaskState.NOW
+        db.add(later_tasks[0])
+        db.flush()
+        if len(later_tasks) > 1:
+            later_tasks[1].state = TaskState.NEXT
+            db.add(later_tasks[1])
+
+
 def promote_tasks(db: Session):
     """Enforce the NOW/NEXT/LATER state machine invariants.
 
@@ -114,63 +164,19 @@ async def post_morning_ritual(
     other_tasks: str = Form(""),
 ):
     """Process morning ritual: create MITs, other tasks, and set initial states."""
-    # Create Journal Entry
-    mit_task_ids = []
     journal_entry = JournalEntry(entry_date=date.today())
     db.add(journal_entry)
     db.commit()
     db.refresh(journal_entry)
 
-    # Create MIT tasks
+    journal_entry.mit_task_ids = _create_mit_tasks(db, [mit1_title, mit2_title, mit3_title])
-    for mit_title in [mit1_title, mit2_title, mit3_title]:
-        if mit_title:
-            task = Task(
-                title=mit_title,
-                is_mit=True,
-                state=TaskState.LATER,  # Initially LATER, will be promoted
-                certainty=TaskCertainty.SOFT,
-            )
-            db.add(task)
-            db.commit()
-            db.refresh(task)
-            mit_task_ids.append(task.id)
-
-    journal_entry.mit_task_ids = mit_task_ids
     db.add(journal_entry)
 
-    # Create other tasks
+    _create_other_tasks(db, other_tasks)
-    for task_title in other_tasks.split("\n"):
-        task_title = task_title.strip()
-        if task_title:
-            task = Task(
-                title=task_title,
-                state=TaskState.LATER,
-                certainty=TaskCertainty.FUZZY,
-            )
-            db.add(task)
-
     db.commit()
 
-    # Set initial NOW/NEXT states
+    _seed_now_next(db)
-    # Set initial NOW/NEXT states after all tasks are created
+    db.commit()
-    if not get_now_task(db) and not get_next_task(db):
-        later_tasks = (
-            db.query(Task)
-            .filter(Task.state == TaskState.LATER)
-            .order_by(Task.is_mit.desc(), Task.sort_order)
-            .all()
-        )
-        if later_tasks:
-            # Set the highest priority LATER task to NOW
-            later_tasks[0].state = TaskState.NOW
-            db.add(later_tasks[0])
-            db.flush()  # Flush to make the change visible for the next query
-
-            # Set the next highest priority LATER task to NEXT
-            if len(later_tasks) > 1:
-                later_tasks[1].state = TaskState.NEXT
-                db.add(later_tasks[1])
-    db.commit()  # Commit changes after initial NOW/NEXT setup
 
     return templates.TemplateResponse(
         request,

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/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": {
+            "options": options,
-                "temperature": temperature,
-            },
         }
 
         timeout = aiohttp.ClientTimeout(total=self.config.timeout_seconds)

src/timmy/conversation.py

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

src/timmy/tools_delegation/__init__.py

@@ -89,52 +89,41 @@ def list_swarm_agents() -> dict[str, Any]:
         }
 
 
-def delegate_to_kimi(task: str, working_directory: str = "") -> dict[str, Any]:
+def _find_kimi_cli() -> str | None:
-    """Delegate a coding task to Kimi, the external coding agent.
+    """Return the path to the kimi CLI, or None if not installed."""
-
-    Kimi has 262K context and is optimized for code tasks: writing,
-    debugging, refactoring, test writing. Timmy thinks and plans,
-    Kimi executes bulk code changes.
-
-    Args:
-        task: Clear, specific coding task description. Include file paths
-              and expected behavior. Good: "Fix the bug in src/timmy/session.py
-              where sessions don't persist." Bad: "Fix all bugs."
-        working_directory: Directory for Kimi to work in. Defaults to repo root.
-
-    Returns:
-        Dict with success status and Kimi's output or error.
-    """
     import shutil
-    import subprocess
+
+    return shutil.which("kimi")
+
+
+def _resolve_workdir(working_directory: str) -> str | dict[str, Any]:
+    """Resolve and validate the working directory.
+
+    Returns the resolved path string, or an error dict if invalid.
+    """
     from pathlib import Path
 
     from config import settings
 
-    kimi_path = shutil.which("kimi")
-    if not kimi_path:
-        return {
-            "success": False,
-            "error": "kimi CLI not found on PATH. Install with: pip install kimi-cli",
-        }
-
     workdir = working_directory or settings.repo_root
     if not Path(workdir).is_dir():
         return {
             "success": False,
             "error": f"Working directory does not exist: {workdir}",
         }
+    return workdir
 
-    cmd = [kimi_path, "--print", "-p", task]
 
-    logger.info("Delegating to Kimi: %s (cwd=%s)", task[:80], workdir)
+def _run_kimi(cmd: list[str], workdir: str) -> dict[str, Any]:
+    """Execute the kimi subprocess and return a result dict."""
+    import subprocess
 
     try:
         result = subprocess.run(
             cmd,
             capture_output=True,
             text=True,
-            timeout=300,  # 5 minute timeout for coding tasks
+            timeout=300,
             cwd=workdir,
         )
 
@@ -157,3 +146,34 @@ def delegate_to_kimi(task: str, working_directory: str = "") -> dict[str, Any]:
             "success": False,
             "error": f"Failed to run Kimi: {exc}",
         }
+
+
+def delegate_to_kimi(task: str, working_directory: str = "") -> dict[str, Any]:
+    """Delegate a coding task to Kimi, the external coding agent.
+
+    Kimi has 262K context and is optimized for code tasks: writing,
+    debugging, refactoring, test writing. Timmy thinks and plans,
+    Kimi executes bulk code changes.
+
+    Args:
+        task: Clear, specific coding task description. Include file paths
+              and expected behavior. Good: "Fix the bug in src/timmy/session.py
+              where sessions don't persist." Bad: "Fix all bugs."
+        working_directory: Directory for Kimi to work in. Defaults to repo root.
+
+    Returns:
+        Dict with success status and Kimi's output or error.
+    """
+    kimi_path = _find_kimi_cli()
+    if not kimi_path:
+        return {
+            "success": False,
+            "error": "kimi CLI not found on PATH. Install with: pip install kimi-cli",
+        }
+
+    workdir = _resolve_workdir(working_directory)
+    if isinstance(workdir, dict):
+        return workdir
+
+    logger.info("Delegating to Kimi: %s (cwd=%s)", task[:80], workdir)
+    return _run_kimi([kimi_path, "--print", "-p", task], workdir)

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