whisper

name	whisper
triggers	["transcribe","whisper","audio","voice","speech","dictation","recording","voice memo"]
description	Local audio transcription using faster-whisper (CPU, int8)
cli	true
file_types	["mp3","wav","ogg","flac","m4a","opus","webm","mp4","aac","wma"]
companion_skills	["untrusted_input"]
dependencies	["faster_whisper>=1.1.0"]

Audio Transcription with Whisper

Transcribe audio files locally using faster-whisper (CPU, int8 quantization). Supports all common audio formats (wav, mp3, m4a, flac, ogg, webm).

Usage

# Basic transcription (auto-selects model based on available RAM)
istota-skill whisper transcribe /path/to/audio.wav

# Specify model and language
istota-skill whisper transcribe /path/to/audio.wav --model small --language en

# Output as SRT subtitles and save to file
istota-skill whisper transcribe /path/to/audio.wav --output srt --save

# Output as WebVTT
istota-skill whisper transcribe /path/to/audio.wav --output vtt

# Plain text output
istota-skill whisper transcribe /path/to/audio.wav --output text

# List available models and RAM requirements
istota-skill whisper models

# Pre-download a model
istota-skill whisper download small

Output (JSON format)

{
  "status": "ok",
  "model": "small",
  "language": "en",
  "language_probability": 0.9876,
  "duration_seconds": 45.2,
  "processing_seconds": 12.3,
  "text": "Full transcription text...",
  "segments": [
    {
      "start": 0.0,
      "end": 3.5,
      "text": "Hello, this is a test.",
      "words": [
        {"start": 0.0, "end": 0.5, "word": "Hello,", "probability": 0.98},
        {"start": 0.6, "end": 0.9, "word": "this", "probability": 0.99}
      ]
    }
  ]
}

Models

Model	RAM (~GB)	Speed	Quality
tiny	1.0	Fastest	Basic
base	1.5	Fast	Good for clear audio
small	2.5	Moderate	Good general-purpose
medium	5.0	Slow	High quality
large-v3	10.0	Slowest	Best quality

With --model auto (default), the largest model that fits in available RAM is selected.

Guidelines

• Short recordings (< 5 min): Use default model auto-selection.
• Long recordings (> 10 min): Warn the user this may take a while. Processing is ~0.5-2x real-time depending on model and CPU.
• Language: Auto-detected by default. Specify --language if detection is unreliable or you know the language.
• Use --save when the user wants to keep the transcription as a file.
• SRT/VTT formats are useful when the user wants subtitles or time-aligned text.
• Voice memos: Commonly found in /Users/{user_id}/inbox/ or shared files.
• Models must be pre-downloaded before use inside sandboxed environments.

When to Use

• Voice memos and audio recordings shared by the user
• Dictation or speech-to-text requests
• Meeting recordings or interview transcripts
• Audio files in the user's inbox or shared folders
• Any audio-to-text conversion task