Individual skill
transcribe
Transcribe audio files to text with optional diarization and known-speaker hints. Use when a user asks to transcribe speech from audio/video, extract text from recordings, or label speakers in interviews or meetings.
skills-imported/transcribe/SKILL.md
Source commit faf37c0859ebf627bfcb5225e8057d088691e0ae
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- Local scripts
- Last checked
- Nov 8, 2026
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- Repository last updated
- Oct 10, 2026
- License
- MIT
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LICENSE.txtdoc · 10,776 bytesSKILL.mdcore · 2,847 bytesSKILL.mdcore · 2,847 bytesSKILL.mdcore · 2,847 bytesSKILL.mdcore · 2,847 bytesSKILL.mdcore · 2,847 bytesassets/transcribe-small.svgasset · 750 bytesassets/transcribe.pngasset · 1,288 bytesreferences/api.mddoc · 457 bytesscripts/transcribe_diarize.pyruns · 8,684 bytes
Read excerpt
# Audio Transcribe
Transcribe audio using OpenAI, with optional speaker diarization when requested. Prefer the bundled CLI for deterministic, repeatable runs.
## Workflow
1. Collect inputs: audio file path(s), desired response format (text/json/diarized_json), optional language hint, and any known speaker references.
2. Verify `OPENAI_API_KEY` is set. If missing, ask the user to set it locally (do not ask them to paste the key).
3. Run the bundled `transcribe_diarize.py` CLI with sensible defaults (fast text transcription).
4. Validate the output: transcription quality, speaker labels, and segment boundaries; iterate with a single targeted change if needed.
5. Save outputs under `output/transcribe/` when working in this repo.
## Decision rules
- Default to `gpt-4o-mini-transcribe` with `--response-format text` for fast transcription.