executing-plans
executing-plans
Use when executing an implementation plan in the current session as the implementer yourself — your human partner chose inline execution, or no subagent tool is available
TranscribeConvert audio files (M4A, WAV, MP3) to Markdown transcripts. USE WHEN transcribe, audio to text, meeting recording, voice memo.
Independent GitHub snapshot · Automated classification · Original documentation governs
Convert audio files to clean Markdown transcripts. Auto-selects best backend.
/transcribe <audio-file>
/transcribe <audio-file> --azure # Force Azure gpt-4o-mini-transcribe (best quality)
/transcribe <audio-file> --groq # Force Groq whisper-large-v3-turbo (fastest)
/transcribe <audio-file> --local # Force local whisper.cpp (free)
AZURE_OPENAI_KEY + AZURE_OPENAI_ENDPOINT set (gpt-4o-mini-transcribe, lowest WER)GROQ_API_KEY set (216x realtime, cheapest API)When invoked, run:
~/.claude/skills/Transcribe/Tools/Transcribe.sh "<audio-file>" [--groq|--azure|--local]
Output saved to same directory as source: {name}-transcript.md
| Component | Path / Config |
|---|---|
| Transcribe.sh | ~/.claude/skills/Transcribe/Tools/Transcribe.sh |
| Azure API | AZURE_OPENAI_KEY, AZURE_OPENAI_ENDPOINT, deployment: gpt-4o-mini-transcribe (default) with whisper fallback |
| Groq API | GROQ_API_KEY env var, model: whisper-large-v3-turbo |
| whisper-cli | ~/tools/whisper.cpp/build/bin/whisper-cli |
| large-v3 model | ~/tools/whisper.cpp/models/ggml-large-v3.bin |
| Method | Cost | Speed | Quality | Best For |
|---|---|---|---|---|
| Azure (gpt-4o-mini-transcribe) | ~$0.30/hr | Fast | Best (lowest WER) | Default — best quality |
| Groq (turbo) | $0.04/hr | 216x realtime | Good | Bulk/fast transcription |
| Azure (whisper) | ~$0.36/hr | Fast | Good | Fallback |
| Local (large-v3) | FREE | ~1x realtime | Good | Offline, full privacy |
| Local (small.en) | FREE | ~3x faster | OK | Quick English drafts |
Set AZURE_TRANSCRIBE_DEPLOYMENT env var to use a different Azure deployment (e.g., whisper for old behavior).