Agent 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.
Install this agent skill to your Project
npx add-skill https://github.com/tercumantanumut/selene/tree/main/lib/skills/catalog/bundled/transcribe
SKILL.md
Audio Transcribe
Transcribe audio using OpenAI, with optional speaker diarization when requested. Prefer the bundled CLI for deterministic, repeatable runs.
Workflow
- Collect inputs: audio file path(s), desired response format (text/json/diarized_json), optional language hint, and any known speaker references.
- Verify
OPENAI_API_KEYis set. If missing, ask the user to set it locally (do not ask them to paste the key). - Run the bundled
transcribe_diarize.pyCLI with sensible defaults (fast text transcription). - Validate the output: transcription quality, speaker labels, and segment boundaries; iterate with a single targeted change if needed.
- Save outputs under
output/transcribe/when working in this repo.
Decision rules
- Default to
gpt-4o-mini-transcribewith--response-format textfor fast transcription. - If the user wants speaker labels or diarization, use
--model gpt-4o-transcribe-diarize --response-format diarized_json. - If audio is longer than ~30 seconds, keep
--chunking-strategy auto. - Prompting is not supported for
gpt-4o-transcribe-diarize.
Output conventions
- Use
output/transcribe/<job-id>/for evaluation runs. - Use
--out-dirfor multiple files to avoid overwriting.
Dependencies (install if missing)
Prefer uv for dependency management.
uv pip install openai
If uv is unavailable:
python3 -m pip install openai
Environment
OPENAI_API_KEYmust be set for live API calls.- If the key is missing, instruct the user to create one in the OpenAI platform UI and export it in their shell.
- Never ask the user to paste the full key in chat.
Skill path (set once)
export TRANSCRIBE_CLI="${SELENE_SKILL_ROOT}/scripts/transcribe_diarize.py"
CLI quick start
Single file (fast text default):
python3 "$TRANSCRIBE_CLI" \
path/to/audio.wav \
--out transcript.txt
Diarization with known speakers (up to 4):
python3 "$TRANSCRIBE_CLI" \
meeting.m4a \
--model gpt-4o-transcribe-diarize \
--known-speaker "Alice=refs/alice.wav" \
--known-speaker "Bob=refs/bob.wav" \
--response-format diarized_json \
--out-dir output/transcribe/meeting
Plain text output (explicit):
python3 "$TRANSCRIBE_CLI" \
interview.mp3 \
--response-format text \
--out interview.txt
Reference map
${SELENE_SKILL_ROOT}/references/api.md: supported formats, limits, response formats, and known-speaker notes.
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