ruff (#169)

* polish: streamline nav, extract inline styles, improve tablet UX

- Restructure desktop nav from 8+ flat links + overflow dropdown into
  5 grouped dropdowns (Core, Agents, Intel, System, More) matching
  the mobile menu structure to reduce decision fatigue
- Extract all inline styles from mission_control.html and base.html
  notification elements into mission-control.css with semantic classes
- Replace JS-built innerHTML with secure DOM construction in
  notification loader and chat history
- Add CONNECTING state to connection indicator (amber) instead of
  showing OFFLINE before WebSocket connects
- Add tablet breakpoint (1024px) with larger touch targets for
  Apple Pencil / stylus use and safe-area padding for iPad toolbar
- Add active-link highlighting in desktop dropdown menus
- Rename "Mission Control" page title to "System Overview" to
  disambiguate from the chat home page
- Add "Home — Timmy Time" page title to index.html

https://claude.ai/code/session_015uPUoKyYa8M2UAcyk5Gt6h

* fix(security): move auth-gate credentials to environment variables

Hardcoded username, password, and HMAC secret in auth-gate.py replaced
with os.environ lookups. Startup now refuses to run if any variable is
unset. Added AUTH_GATE_SECRET/USER/PASS to .env.example.

https://claude.ai/code/session_015uPUoKyYa8M2UAcyk5Gt6h

* refactor(tooling): migrate from black+isort+bandit to ruff

Replace three separate linting/formatting tools with a single ruff
invocation. Updates tox.ini (lint, format, pre-push, pre-commit envs),
.pre-commit-config.yaml, and CI workflow. Fixes all ruff errors
including unused imports, missing raise-from, and undefined names.
Ruff config maps existing bandit skips to equivalent S-rules.

https://claude.ai/code/session_015uPUoKyYa8M2UAcyk5Gt6h

---------

Co-authored-by: Claude <noreply@anthropic.com>

src/timmy/memory/vector_store.py

@@ -8,9 +8,8 @@ import json
 import sqlite3
 import uuid
 from dataclasses import dataclass, field
-from datetime import datetime, timezone
+from datetime import UTC, datetime
 from pathlib import Path
-from typing import Optional
 
 DB_PATH = Path(__file__).parent.parent.parent.parent / "data" / "swarm.db"
 
@@ -97,13 +96,13 @@ class MemoryEntry:
     content: str = ""  # The actual text content
     source: str = ""  # Where it came from (agent, user, system)
     context_type: str = "conversation"  # conversation, document, fact, etc.
-    agent_id: Optional[str] = None
-    task_id: Optional[str] = None
-    session_id: Optional[str] = None
-    metadata: Optional[dict] = None
-    embedding: Optional[list[float]] = None
-    timestamp: str = field(default_factory=lambda: datetime.now(timezone.utc).isoformat())
-    relevance_score: Optional[float] = None  # Set during search
+    agent_id: str | None = None
+    task_id: str | None = None
+    session_id: str | None = None
+    metadata: dict | None = None
+    embedding: list[float] | None = None
+    timestamp: str = field(default_factory=lambda: datetime.now(UTC).isoformat())
+    relevance_score: float | None = None  # Set during search
 
 
 def _get_conn() -> sqlite3.Connection:
@@ -152,10 +151,10 @@ def store_memory(
     content: str,
     source: str,
     context_type: str = "conversation",
-    agent_id: Optional[str] = None,
-    task_id: Optional[str] = None,
-    session_id: Optional[str] = None,
-    metadata: Optional[dict] = None,
+    agent_id: str | None = None,
+    task_id: str | None = None,
+    session_id: str | None = None,
+    metadata: dict | None = None,
     compute_embedding: bool = True,
 ) -> MemoryEntry:
     """Store a memory entry with optional embedding.
@@ -218,9 +217,9 @@ def store_memory(
 def search_memories(
     query: str,
     limit: int = 10,
-    context_type: Optional[str] = None,
-    agent_id: Optional[str] = None,
-    session_id: Optional[str] = None,
+    context_type: str | None = None,
+    agent_id: str | None = None,
+    session_id: str | None = None,
     min_relevance: float = 0.0,
 ) -> list[MemoryEntry]:
     """Search for memories by semantic similarity.
@@ -305,7 +304,7 @@ def search_memories(
 
 def _cosine_similarity(a: list[float], b: list[float]) -> float:
     """Compute cosine similarity between two vectors."""
-    dot = sum(x * y for x, y in zip(a, b))
+    dot = sum(x * y for x, y in zip(a, b, strict=False))
     norm_a = sum(x * x for x in a) ** 0.5
     norm_b = sum(x * x for x in b) ** 0.5
     if norm_a == 0 or norm_b == 0:
@@ -353,7 +352,7 @@ def get_memory_context(query: str, max_tokens: int = 2000, **filters) -> str:
     return "Relevant context from memory:\n" + "\n\n".join(context_parts)
 
 
-def recall_personal_facts(agent_id: Optional[str] = None) -> list[str]:
+def recall_personal_facts(agent_id: str | None = None) -> list[str]:
     """Recall personal facts about the user or system.
 
     Args:
@@ -388,7 +387,7 @@ def recall_personal_facts(agent_id: Optional[str] = None) -> list[str]:
     return [r["content"] for r in rows]
 
 
-def recall_personal_facts_with_ids(agent_id: Optional[str] = None) -> list[dict]:
+def recall_personal_facts_with_ids(agent_id: str | None = None) -> list[dict]:
     """Recall personal facts with their IDs for edit/delete operations."""
     conn = _get_conn()
     if agent_id:
@@ -417,7 +416,7 @@ def update_personal_fact(memory_id: str, new_content: str) -> bool:
     return updated
 
 
-def store_personal_fact(fact: str, agent_id: Optional[str] = None) -> MemoryEntry:
+def store_personal_fact(fact: str, agent_id: str | None = None) -> MemoryEntry:
     """Store a personal fact about the user or system.
 
     Args:
@@ -496,7 +495,7 @@ def prune_memories(older_than_days: int = 90, keep_facts: bool = True) -> int:
     """
     from datetime import timedelta
 
-    cutoff = (datetime.now(timezone.utc) - timedelta(days=older_than_days)).isoformat()
+    cutoff = (datetime.now(UTC) - timedelta(days=older_than_days)).isoformat()
 
     conn = _get_conn()