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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). Use when the user needs to transcribe audio files, translate speech, or convert audio to text.

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$ npx -y skills add coco-research/coco --skill openai-whisper --agent claude-code

SKILL.md

openai-whisper.SKILL.md
name: openai-whisper
description: 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). Use when the user needs to transcribe audio files, translate speech, or convert audio to text.
homepage: https://openai.com/research/whisper
domain: engineering

OpenAI Whisper — Speech-to-Text

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 |

---

Mode 1: Local CLI

Run Whisper locally with no API key required. Models download to `~/.cache/whisper` on first run.

Quick Start

whisper /path/audio.mp3 --model medium --output_format txt --output_dir .

Common Commands

# 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 Selection

| Model | Speed | Accuracy | VRAM | |-------|-------|----------|------| | `tiny` | Fastest | Lowest | ~1 GB | | `base` | Fast | Low | ~1 GB | | `small` | Medium | Good | ~2 GB | | `medium` | Slow | Better | ~5 GB | | `large` | Slowest | Best | ~10 GB | | `turbo` | Fast | Good (default) | ~6 GB |

Output Formats

  • `txt` — Plain text transcript
  • `srt` — SubRip subtitle format with timestamps
  • `vtt` — WebVTT subtitle format
  • `json` — Detailed JSON with word-level timestamps
  • `tsv` — Tab-separated values

Notes

  • `--model` defaults to `turbo` on most installs
  • Use smaller models for speed, larger for accuracy
  • GPU acceleration used automatically when available

---

Mode 2: Cloud API

Transcribe via OpenAI's `/v1/audio/transcriptions` endpoint. Faster for large batches, no local GPU needed.

Quick Start

{baseDir}/scripts/transcribe.sh /path/to/audio.m4a

Defaults:

  • Model: `whisper-1`
  • Output: `<input>.txt`

Common Commands

# Basic transcription
{baseDir}/scripts/transcribe.sh /path/to/audio.m4a

# Specify model and output
{baseDir}/scripts/transcribe.sh /path/to/audio.ogg --model whisper-1 --out /tmp/transcript.txt

# With language hint
{baseDir}/scripts/transcribe.sh /path/to/audio.m4a --language en

# With speaker name hints (improves accuracy)
{baseDir}/scripts/transcribe.sh /path/to/audio.m4a --prompt "Speaker names: Peter, Daniel"

# JSON output with timestamps
{baseDir}/scripts/transcribe.sh /path/to/audio.m4a --json --out /tmp/transcript.json

Raw curl Example

curl https://api.openai.com/v1/audio/transcriptions \
  -H "Authorization: Bearer $OPENAI_API_KEY" \
  -H "Content-Type: multipart/form-data" \
  -F file="@/path/to/audio.m4a" \
  -F model="whisper-1" \
  -F response_format="text"

API Key Setup

Set `OPENAI_API_KEY` environment variable, or configure in `~/.clawdbot/clawdbot.json`:

{
  skills: {
    "openai-whisper-api": {
      apiKey: "OPENAI_KEY_HERE"
    }
  }
}

---

Choosing Between Modes

| Consideration | Local CLI | Cloud API | |---------------|-----------|-----------| | Privacy-sensitive audio | Best | Audio sent to OpenAI | | Large batch processing | Slow without GPU | Fast and parallel | | Offline usage | Works offline | Requires internet | | Cost | Free (hardware cost) | Per-minute pricing | | Setup complexity | Install binary + models | API key only | | Audio format support | Most formats | Most formats |

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Questions about openai-whisper.

Which coding agents can use openai-whisper?
openai-whisper installs in Claude Code, Codex, Cursor, Gemini CLI, GitHub Copilot, OpenCode and Windsurf with the skills CLI, using each agent's flag shown on this page. Flowy's auto-invocation, which fires a skill when your prompt matches, runs in Claude Code only.