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Get Started Free →qdhenry/elevenlabs-transcribe
Transcribes audio/video files using ElevenLabs Scribe v2 API.
Passed 6 of 13 test cases with the skill, and 4 of 13 without it.
and 2 more in the full report
5 fixed5 passed either way11 still failing1 broke
Tokens, turns and time describe resource use, not a dollar price.
One of 5 test cases the skill fixed. Same model, same prompt, with and without the skill.
Which ElevenLabs model ID and endpoint does the speech-to-text integration utilize?
| Checked | Without skill | With skill |
|---|---|---|
| Identifies scribe_v2 as the model. | Missed | Passed |
| Identifies /v1/speech-to-text as the API endpoint. | Passed | Passed |
The instructions your model reads when the skill loads.
<quick_start>
Via slash command:
/elevenlabs-transcribe path/to/audio.mp3
/elevenlabs-transcribe path/to/audio.mp3 --output transcript.txt --num-speakers 3
Requirements:
ELEVENLABS_API_KEY in the project's .env fileuv installed (dependencies auto-install via PEP 723)
</quick_start>uv is available (dependency installation is automatic via inline script metadata — no venv or manual pip install needed)
API key configured in the .env file where Claude is running:
ELEVENLABS_API_KEY=your-key-here
Audio file exists and is a supported format (mp3, wav, mp4, m4a, ogg, flac, webm, etc.)
MUST stop if the API key is missing — inform the user to add it to their .env file.
Step 1: Parse user input
Extract the audio file path and any options from $ARGUMENTS or the user's message. Supported options:
--output <path> or -o <path> — where to save the transcript--language <code> — ISO-639 language code (e.g., eng, spa, fra, deu, jpn, zho)--num-speakers <n> — max speakers in the audio (1-32)--keyterms "term1" "term2" — words/phrases to bias transcription towards--timestamps none|word|character — timestamp granularity--no-diarize — disable speaker identificationtest cases passed, vs 4 / 13 without
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