Openai Whisper logo

Openai Whisper

Community
coco-research
openai-whisper

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.

Overview

Publishercoco-research
Repositorycoco
Skill nameopenai-whisper
Stars
550
Forks
12
Bundled files
Instructions only
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • Self-contained

    Everything the model needs lives in the instructions — no extra files to sync.

  • Open source

    Published by coco-research on GitHub. Read the source before you install it.

Installation

Install the Openai Whisper AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/coco-research/coco/tree/main/skills/openai-whisper
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/coco-research/coco.git /tmp/coco
mkdir -p .claude/skills
cp -r /tmp/coco/skills/openai-whisper .claude/skills/openai-whisper
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Openai Whisper in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Openai Whisper on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Openai Whisper is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

OpenAI Whisper — Speech-to-Text

Transcribe audio files using OpenAI's Whisper model. Two modes available depending on your needs:

ModeLatencyCostPrivacySetup
Local CLISlower (on-device GPU/CPU)FreeAudio never leaves machineInstall whisper binary
Cloud APIFastPer-minute pricingAudio sent to OpenAIOPENAI_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

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

Common Commands

bash
# 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

ModelSpeedAccuracyVRAM
tinyFastestLowest~1 GB
baseFastLow~1 GB
smallMediumGood~2 GB
mediumSlowBetter~5 GB
largeSlowestBest~10 GB
turboFastGood (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

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

Defaults:

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

Common Commands

bash
# 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

bash
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:

json5
{
  skills: {
    "openai-whisper-api": {
      apiKey: "OPENAI_KEY_HERE"
    }
  }
}

Choosing Between Modes

ConsiderationLocal CLICloud API
Privacy-sensitive audioBestAudio sent to OpenAI
Large batch processingSlow without GPUFast and parallel
Offline usageWorks offlineRequires internet
CostFree (hardware cost)Per-minute pricing
Setup complexityInstall binary + modelsAPI key only
Audio format supportMost formatsMost formats

Frequently asked questions

What does the Openai Whisper AI skill do?

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.

Why use Openai Whisper on TypingMind?

Because you install it once and use it with any model. Openai Whisper is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Openai Whisper in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/coco-research/coco/tree/main/skills/openai-whisper. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Openai Whisper?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Openai Whisper?

As many as you like. As long as a model supports skills, you can use Openai Whisper with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Openai Whisper AI skill free?

It is published on GitHub by coco-research. Check the repository for licensing terms. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

View all

Set up your own AI workspace now

Get notified about new features and future giveaways by subscribing to our newsletter 👇