openai-whisper

Transcribe audio files locally into text and subtitle outputs using the Whisper CLI.

Updated May 8, 2026
One-click install
npx skills add https://github.com/freire19/Mythos --skill openai-whisper-freire19
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: openai-whisper
Source: https://github.com/freire19/Mythos/tree/main/skills/openai-whisper
Command: npx skills add https://github.com/freire19/Mythos --skill openai-whisper-freire19

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

It removes the need for API-based speech-to-text by enabling local transcription of audio files on your machine.

Core Features & Use Cases

  • Local Whisper CLI transcription: Convert audio into readable text without using an external API key.
  • Multiple output formats: Generate text outputs such as .txt or subtitle formats such as .srt depending on task and flags.
  • Model selection for speed vs. accuracy: Choose smaller models for faster results or larger models for better transcription quality, with first-run model downloads cached locally.

Quick Start

Run whisper on your audio file with the desired model and output format, for example: transcribe /path/audio.mp3 using the medium model and save the result as a .txt file in the current directory.

Frequently Asked Questions about openai-whisper

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I transcribe audio files locally without using an API?▼

Local speech-to-text transcription can be performed directly on your machine using the Whisper CLI, converting audio files into text outputs without requiring an external API key.

Can I generate SRT subtitles from audio files using Whisper?▼

Yes, Whisper CLI supports generating subtitle formats such as .srt from audio files, alongside standard text outputs like .txt, depending on the selected task and command flags.

Do I need an external API key for local audio transcription?▼

No, local audio transcription with Whisper CLI removes the need for API-based speech-to-text services by processing audio files entirely on your own machine.

How do I choose a Whisper model for faster transcription speed?▼

You can select smaller Whisper models for faster transcription results or larger models for better accuracy, with first-run model downloads automatically cached locally for future use.

What are the limitations of using local CLI for speech-to-text transcription?▼

Local CLI speech-to-text transcription requires a local whisper binary installed from the openai-whisper package, meaning processing speed and accuracy depend heavily on your machine's hardware resources.