* 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>
Inspired by OpenClaw-RL's multi-model orchestration, this adds four
features for custom model management:
1. Custom model registry (infrastructure/models/registry.py) — SQLite-backed
registry for GGUF, safetensors, HF checkpoint, and Ollama models with
role-based lookups (general, reward, teacher, judge).
2. Per-agent model assignment — each swarm persona can use a different model
instead of sharing the global default. Resolved via registry assignment >
persona default > global default.
3. Runtime model management API (/api/v1/models) — REST endpoints to register,
list, assign, enable/disable, and remove custom models without restart.
Includes a dashboard page at /models.
4. Reward model scoring (PRM-style) — majority-vote quality evaluation of
agent outputs using a configurable reward model. Scores persist in SQLite
and feed into the swarm learner.
New config settings: custom_weights_dir, reward_model_enabled,
reward_model_name, reward_model_votes.
54 new tests covering registry CRUD, API endpoints, agent assignments,
role lookups, and reward scoring.
https://claude.ai/code/session_01V4iTozMwcE2gjfnCJdCugC
