fix: task intent classifier, Hermes brain, rolling run log

- Intent classifier: task phrases now checked before query to prevent
  "add task X" mis-routing; "job item"/"job ticket"/"work order" added
  to TASK_PHRASES; "please add + project keyword" fallback added;
  substring match bug fixed ("in" inside "incident" triggered query)
- brain.py: routes planning fallback to Hermes cloud (claude-sonnet-4-6)
  via HERMES_URL/HERMES_API_KEY env vars; falls back to local Ollama
  if Hermes is unavailable
- main.py: rolling 50-run log written to logs/jon-snow/runs.jsonl

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

app/intent.py

@@ -10,6 +10,7 @@ TASK_PHRASES = {
     "create task", "add task", "add issue", "create issue", "log task",
     "log this", "new task", "new issue", "add to plane", "add to backlog",
     "schedule", "remind", "track", "todo", "to do",
+    "job item", "job ticket", "work order",
 }
 
 # "plan" removed from TASK_PHRASES — it substring-matches "plane" (the tool name)
@@ -83,14 +84,21 @@ def classify_intent(message: str) -> str:
     if any(v in msg for v in EXECUTE_VERBS) and any(s in msg for s in STACK_NAMES):
         return "execute"
 
+    # Explicit task phrases — check before query to prevent "add task X" → query mis-route
+    if any(p in msg for p in TASK_PHRASES):
+        return "task"
+    if words & TASK_WORDS:
+        return "task"
+
     # Plane query — list/show projects or issues (check before task to avoid "plan" ⊂ "plane" bug)
     if ("project" in msg or "projects" in msg) and any(p in msg for p in QUERY_PHRASES):
         return "query"
     if "plane" in words and any(p in msg for p in QUERY_PHRASES):
         return "query"
     # Issue list query — "show issues in X", "list tasks for X", "work items for X"
+    # Use word-boundary check (words set) to avoid "in" matching inside "incident" etc.
     has_issue_word = bool(words & ISSUE_KEYWORDS) or any(p in msg for p in ISSUE_PHRASES)
-    if has_issue_word and any(p in msg for p in {"show", "list", "get", "what", "give", "in", "for"}):
+    if has_issue_word and words & {"show", "list", "get", "what", "give", "in", "for"}:
         return "query"
 
     # Agent name + status word → status
@@ -98,15 +106,12 @@ def classify_intent(message: str) -> str:
         if any(p in msg for p in STATUS_PHRASES) or words & {"status", "check", "output", "run"}:
             return "status"
 
-    # Explicit task phrases → task
-    if any(p in msg for p in TASK_PHRASES):
-        return "task"
-    # Word-boundary match for single-word task terms (avoids "plan" matching "plane")
-    if words & TASK_WORDS:
-        return "task"
     # Natural task creation: "add X to [project]"
     if msg.startswith("add ") and " to " in msg:
         return "task"
+    # "please add" / "add" anywhere + known project keyword → task
+    if "add" in words and any(kw in msg for kw in PROJECT_KEYWORDS):
+        return "task"
 
     # Generic status signal words
     if any(p in msg for p in STATUS_PHRASES) and words & AGENT_NAMES:
@@ -195,6 +200,7 @@ def is_issue_query(message: str) -> bool:
 
 def extract_task_title(message: str) -> str:
     """Extract clean task title from natural phrasing like 'add buy milk to General'."""
+    import re as _re
     msg = message.strip()
     lower = msg.lower()
     if lower.startswith("add ") and " to " in lower:
@@ -204,6 +210,15 @@ def extract_task_title(message: str) -> str:
     for prefix in ("create task:", "add task:", "log task:", "new task:", "log this:"):
         if lower.startswith(prefix):
             return msg[len(prefix):].strip()
+    # "add [who] a job item [description]" — extract description after "job item"
+    m = _re.search(r'\bjob item\b\s*(.*)', lower)
+    if m:
+        remainder = msg[m.start(1):].strip()
+        for filler in ("that we need to ", "that is ", "which is ", "to "):
+            if remainder.lower().startswith(filler):
+                remainder = remainder[len(filler):]
+        if remainder.strip():
+            return remainder.strip()
     return msg