audio-analysis

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

1. Confirm the exact local audio path and, when available, a Whisper JSON path with timestamped segments.
2. Call analyze_local_audio with action=start. The tool requires operator approval and never uploads audio.
3. Report the returned cache directory and immediately explain that analysis continues in the background.
4. Poll with action=status and the same audio_path until the job completes or fails.
5. On completion, use the returned diarized JSON or SRT artifact. Preserve SPEAKER_* labels unless the user supplies identities.
6. 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.