/elevenlabs-transcribe

name: elevenlabs-transcribe
description: Transcribes audio/video files using ElevenLabs Scribe v2 API. Use when transcribing audio files, generating transcripts, or converting speech to text.
argument-hint: <audio-file> [--output transcript.txt] [--language eng] [--num-speakers 2] [--keyterms "term1" "term2"]

<objective> Transcribe audio or video files using the ElevenLabs Speech-to-Text API (Scribe v2). Accepts a file path and optional parameters, reads the API key from the project's .env file, and returns a formatted transcription with speaker diarization and audio event tagging. </objective>

<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` file
• `uv` installed (dependencies auto-install via PEP 723)

</quick_start>

<prerequisites> Before transcribing, verify:

1. **`uv` is available** (dependency installation is automatic via inline script metadata — no venv or manual pip install needed)

2. **API key configured** in the `.env` file where Claude is running:

   ELEVENLABS_API_KEY=your-key-here

3. **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. </prerequisites>

<process>

**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 identification
• `--no-audio-events` — disable audio event tagging
• `--json` — output full JSON response

**Step 2: Validate the audio file**

Confirm the file path exists. Expand `~` paths. The script handles validation automatically but check early for a clear error message.

**Step 3: Check for API key**

grep -q "ELEVENLABS_API_KEY=" .env 2>/dev/null && echo "API key configured" || echo "API key missing"

If missing, tell the user to add `ELEVENLABS_API_KEY=` to their `.env` file and **stop**.

**Step 4: Run transcription**

Dependencies are installed automatically by `uv` via inline script metadata (PEP 723). No venv or manual pip install needed.

Basic transcription (diarize + audio events + auto language):

uv run ~/.claude/skills/elevenlabs-transcribe/scripts/transcribe.py "<audio_file_path>"

With output file and options:

uv run ~/.claude/skills/elevenlabs-transcribe/scripts/transcribe.py "<audio_file_path>" --output transcript.txt --language eng --num-speakers 3

With key terms for better accuracy:

uv run ~/.claude/skills/elevenlabs-transcribe/scripts/transcribe.py "<audio_file_path>" --keyterms "technical term" "product name"

Full JSON response:

uv run ~/.claude/skills/elevenlabs-transcribe/scripts/transcribe.py "<audio_file_path>" --json --output result.json

**Step 5: Present results**

Format the transcription output cleanly for the user. If diarization is enabled, group text by speaker. Highlight any audio events detected. Example output:

[Speaker 0]: Hello, how are you doing today?
[Speaker 1]: I'm doing great, thanks for asking! (laughter)

</process>

<script_options> | Flag | Description | Default | |------|-------------|---------| | `<file>` | Path to audio/video file (required) | - | | `--output <path>`, `-o` | Save transcription to file | stdout | | `--language <code>` | ISO-639 code (eng, spa, fra, deu, jpn, zho) | auto-detect | | `--num-speakers <n>` | Max speakers in audio (1-32) | auto-detect | | `--keyterms "t1" "t2"` | Terms to bias transcription towards (max 100) | none | | `--timestamps <level>` | Granularity: none, word, character | word | | `--no-diarize` | Disable speaker identification | diarize enabled | | `--no-audio-events` | Disable audio event tagging | events enabled | | `--json` | Output full JSON response | formatted text | </script_options>

<supported_formats> All major audio and video formats: mp3, wav, mp4, m4a, ogg, flac, webm, aac, wma, mov, avi, mkv, and more. Maximum file size: 3GB. </supported_formats>

<api_details>

• **Endpoint:** POST /v1/speech-to-text
• **Model:** scribe_v2 (latest, most accurate)
• **Diarization:** Identifies and labels different speakers (up to 32)
• **Audio events:** Tags non-speech sounds like (laughter), (applause), (music)
• **Language:** Auto-detected or specified via ISO-639 code
• **Timestamps:** none, word-level, or character-level granularity
• **Key terms:** Bias transcription towards specific words/phrases for better accuracy

</api_details>

<error_handling> | Error | Resolution | |-------|------------| | `ELEVENLABS_API_KEY not found` | Add key to `.env` file in current directory | | `uv: command not found` | Install uv: `curl -LsSf https://astral.sh/uv/install.sh` pipe to `sh` | | `File not found` | Verify the file path and expand any `~` | | `422 Validation Error` | Check file format/size, ensure model_id is valid | | `401 Unauthorized` | API key is invalid or expired | </error_handling>

<success_criteria>

• Audio file exists and is accessible
• API key loaded from `.env` without exposure in chat
• Transcription completed successfully
• Output formatted with speaker labels (if diarized)
• Audio events shown inline (if enabled)
• If `--output` specified, file written to requested path
• User can see the full transcription text

</success_criteria>