Openai Whisper

Local speech-to-text with the Whisper CLI (no API key).

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AI & Machine Learning

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Last updated: April 23, 2026

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Quick Start

Manual Installation

No automatic installation available. Please visit the source repository for installation instructions.

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3-5hrs/WK

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Key Features

Fully local processing with no cloud dependency, API keys, or recurring costs — all transcription happens on your machine
Multiple model sizes from tiny to large, allowing you to trade off between speed and accuracy based on your needs (turbo is the default)
Flexible output formats including plain text, SRT subtitles, VTT, and other standard caption formats
Translation capability that can translate audio from other languages directly into English text
Automatic model caching in
```
~/.cache/whisper
```
so models only download once and are reused across sessions

Use Cases

Transcribing meeting recordings, interviews, or voice memos as part of an agent workflow
Generating subtitles for video content without sending audio to external services
Processing sensitive or confidential audio where cloud-based transcription is not permitted
Building local audio-to-text pipelines for content creation, note-taking, or accessibility

How It Works

The skill wraps OpenAI's open-source Whisper command-line tool. Users provide audio file paths and specify parameters like model size and output format. On first use, the selected model downloads and caches locally. Subsequent runs use the cached model for fast startup. The turbo model provides the best balance of speed and accuracy for most use cases.

Getting Started

Install the Whisper binary via Homebrew with

brew install openai-whisper

. The skill will then be ready to use — simply provide an audio file path and your preferred output format. No API keys or external service configuration is needed. Models cache locally in

~/.cache/whisper

and require several GB of disk space depending on the model size selected.

Openai Whisper

AI Skill Market Insights

Quick Start

Manual Installation

TEAR & SHARE

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