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hebertzhuhebertzhu/agent-foundry/skills/transcribe/SKILL.md

transcribe

Skill0 starsChanged 8 months agoMITView on GitHub

Use when the user wants to transcribe audio or video, extract speech to text, or label speakers with optional diarization; prefer the bundled `scripts/transcribe_diarize.py` and require `OPENAI_API_KEY`.

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47 other projects use a version of this.

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Used with

Projects with it also use think, done and 7 more.

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Files found in the same public projects as a version of this one, more often than they turn up anywhere else. Each project counts once, large collections count for less, and this file's own repository is left out.
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The file

We split this skill into the rules it gives an agent

5 rules. 0 are common, 4 are distinctive, and 1 is very specific to this project.

  • 0

    Common

    Most of the 40 edited versions we read keep these.

  • 4

    Distinctive

    This author's own choices. Worth a look.

  • 1

    Very specific

    Tied to their project's names, files or tools. Probably skip.

  • Common
  • Distinctive
  • Very specific
  1. Distinctive:

    Use for converting recordings into text, optional speaker diarization, and structured transcript output for meetings, interviews, or media …

    line 9
  2. Very specific:

    Prefer the bundled scripts/transcribe_diarize.py so the workflow remains deterministic and reusable.

    line 14
  3. Distinctive:

    Start with the simplest successful output, then add diarization or richer structure only when the user actually needs it.

    line 15
  4. Distinctive:

    Do not ask the user to paste the API key into chat.

    line 26
  5. Distinctive:

    Do not overstate diarization confidence if the speaker separation is ambiguous.

    line 27

“Common” is measured: kept by at least 6 in 10 of the 40 edited versions of this file we could read. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.

Keep what fits and drop the rest. Your version, ready for your agents.
Files
SKILL.md

Transcribe

Intent

  • Use for converting recordings into text, optional speaker diarization, and structured transcript output for meetings, interviews, or media assets.

Default operating pattern

  1. Confirm the audio source, expected output format, and whether the user needs plain text or diarized output.
  2. Collect any hints that materially improve recognition quality: language, known speaker names, or reference audio.
  3. Prefer the bundled scripts/transcribe_diarize.py so the workflow remains deterministic and reusable.
  4. Start with the simplest successful output, then add diarization or richer structure only when the user actually needs it.
  5. Validate transcript quality, speaker labels, and segment boundaries before calling it done.

Bundled helper

  • scripts/transcribe_diarize.py supports transcription plus optional diarization with OpenAI audio models.

Pack fit

  • Included in: docs-media
  • Best for turning audio or video into reusable text artifacts.

Boundary

  • Do not ask the user to paste the API key into chat.
  • Do not overstate diarization confidence if the speaker separation is ambiguous.

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