The agent loop checked signal.aborted only at the top of each iteration,
but the LLM fetch() call (which takes seconds) never received the signal.
Now the signal is passed to fetch() and checked after LLM errors and
before the inter-step sleep, so aborting takes effect mid-step.
The UI agent had no memory of previous actions — each step was a fresh
single-shot LLM call. After typing and sending a message, the LLM saw
an empty text field and retyped the message in a loop.
- Add RECENT_ACTIONS (last 5 actions with text/result) to user prompt
- Add chat app completion detection rule to dynamic prompt
- Add send-success hints for WhatsApp and Messages apps
- Add git convention to CLAUDE.md (no co-author lines)
- Add empty goal guard in parser (returns done instead of passthrough)
- Replace `as any` casts in pipeline.ts with proper ActionDecision types
- Add runtime type guards for untrusted LLM output in classifier
- Add intent action to dynamic prompt so UI agent can fire intents
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
Server-side agent loop that adapts the CLI kernel to work over WebSocket.
Three new modules: stuck detection, LLM provider abstraction (OpenAI/Groq/
OpenRouter), and the main perception-reasoning-action loop. Also wires up
the goals route to start agent loops with duplicate-device protection.
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
