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name: worklog description: Update the WORKLOG.md with session progress, architectural decisions, lessons learned, and next steps

Worklog Update Skill

Use this skill at the end of a work session to update the project worklog.

Instructions

1. Read the current WORKLOG.md to understand the format and recent entries

2. Review this session's work by examining:

   • Git diff to see what changed
   • Any beans tasks that were completed
   • Conversations and decisions made during the session

3. Create a new entry at the top of the log (after the header) with today's date and a brief title describing the session's focus

4. Fill in the sections:

   Achieved:

   • List concrete accomplishments
   • Reference specific files created or modified
   • Note any tasks completed

   Architectural Decisions: (if any were made)

   • DECISION: State what was decided
   • REASON: Explain the rationale
   • Only include significant design choices, not routine implementation details

   Lessons Learned: (if any)

   • Important insights discovered during the session
   • Clarifications from user conversations
   • Gotchas, edge cases, or non-obvious behaviors encountered
   • Things that should be remembered for future sessions
   • Corrections to earlier assumptions

   Next:

   • List immediate next steps for the following session
   • Be specific and actionable

5. Update beans tasks:

   • Run beans done <id> for completed tasks
   • Run beans add "..." for new tasks identified
   • Run beans list to verify current state

6. Commit the changes with message: "docs: update worklog for [date]"

Example Entry

Copy## [2025-01-15] WebSocket Audio Pipeline

**Achieved:**
- Implemented bidirectional WebSocket in `backend/src/honeysuckle/main.py`
- Created audio buffer management in `backend/src/honeysuckle/receptionist/audio.py`
- Added basic VAD detection hook

**Architectural Decisions:**
- DECISION: Use raw websockets library instead of FastAPI WebSocket
- REASON: Need lower-level control for audio streaming and buffer management

**Lessons Learned:**
- OpenAI Realtime API expects PCM 16-bit audio at 24kHz, not 16kHz like whisper
- The `response.cancel` event must be sent before clearing local buffers, otherwise audio continues playing
- User clarified: Bluetooth car mics are actually higher quality than expected, don't over-engineer noise handling

**Next:**
- Connect to OpenAI Realtime API
- Implement audio encoding/decoding (PCM 16-bit, 24kHz)
- Add connection health monitoring