| name | audio-analysis |
| description | Analyze a local recording for speakers and label timestamped transcript segments without uploading audio |
| category | knowledge |
| requires | {"tools":["transcribe","analyze_local_audio"]} |
| contexts | ["heartbeat","chat"] |
| aliases | ["audio","recording","diarize","diarization","speakers","transcript","voice"] |
| bound_tools | ["transcribe","analyze_local_audio"] |
Local Audio Analysis
Use device-local speaker diarization when the user asks who spoke when in a recording.
For a plain speech-to-text request, use transcribe; it follows the local/cloud
choice in Settings and does not require a diarization job.
Method
- Confirm the exact local audio path and, when available, a Whisper JSON path with timestamped segments.
- Call
analyze_local_audio with action=start. The tool requires operator approval and never uploads audio.
- Report the returned cache directory and immediately explain that analysis continues in the background.
- Poll with
action=status and the same audio_path until the job completes or fails.
- On completion, use the returned diarized JSON or SRT artifact. Preserve
SPEAKER_* labels unless the user supplies identities.
- If the job fails, report its cause and exact next step from the status. Never present acoustic heuristics as a reliable reading of emotion.
Boundaries
- Do not enable autonomous audio analysis without the user's explicit choice.
- Do not copy generated artifacts into a source repository; they belong in the Hexis cache.
- Only request
emotion_heuristics when the user asks for them. Label the result as a coarse local acoustic estimate.
