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Speech-to-text transcription via OpenAI Whisper. Supports two modes — Local CLI (no API key, runs on-device) and Cloud API (fast, scalable, requires OPENAI_API_KEY).
Passed 22 of 23 test cases with the skill, and 17 of 23 without it.
and 6 more in the full report
6 fixed16 passed either way0 still failing1 broke
Tokens, turns and time describe resource use, not a dollar price.
One of 6 test cases the skill fixed. Same model, same prompt, with and without the skill.
If I run the standard local transcription command on audio.wav without passing a model parameter, which model variant is loaded by default on most modern installations?
| Checked | Without skill | With skill |
|---|---|---|
| Identifies turbo as the default local model variant. | Missed | Passed |
The instructions your model reads when the skill loads.
Transcribe audio files using OpenAI's Whisper model. Two modes available depending on your needs:
| Mode | Latency | Cost | Privacy | Setup |
|---|---|---|---|---|
| Local CLI | Slower (on-device GPU/CPU) | Free | Audio never leaves machine | Install whisper binary |
| Cloud API | Fast | Per-minute pricing | Audio sent to OpenAI | OPENAI_API_KEY required |
Run Whisper locally with no API key required. Models download to ~/.cache/whisper on first run.
whisper /path/audio.mp3 --model medium --output_format txt --output_dir .
# Transcribe to text file
whisper /path/audio.mp3 --model medium --output_format txt --output_dir .
# Transcribe with translation to English
whisper /path/audio.m4a --task translate --output_format srt
# Transcribe with specific language
whisper /path/audio.wav --model large --language en --output_format json
| Model | Speed | Accuracy | VRAM |
|---|---|---|---|
tiny | Fastest | Lowest | ~1 GB |
base | Fast | Low | ~1 GB |
test cases passed, vs 17 / 23 without
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