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Install in OpenClaw
/install mlx-whisper
Description
Local speech-to-text with MLX Whisper (Apple Silicon optimized, no API key).
README (SKILL.md)
MLX Whisper
Local speech-to-text using Apple MLX, optimized for Apple Silicon Macs.
Quick Start
mlx_whisper /path/to/audio.mp3 --model mlx-community/whisper-large-v3-turbo
Common Usage
# Transcribe to text file
mlx_whisper audio.m4a -f txt -o ./output
# Transcribe with language hint
mlx_whisper audio.mp3 --language en --model mlx-community/whisper-large-v3-turbo
# Generate subtitles (SRT)
mlx_whisper video.mp4 -f srt -o ./subs
# Translate to English
mlx_whisper foreign.mp3 --task translate
Models (download on first use)
| Model | Size | Speed | Quality |
|---|---|---|---|
| mlx-community/whisper-tiny | ~75MB | Fastest | Basic |
| mlx-community/whisper-base | ~140MB | Fast | Good |
| mlx-community/whisper-small | ~470MB | Medium | Better |
| mlx-community/whisper-medium | ~1.5GB | Slower | Great |
| mlx-community/whisper-large-v3 | ~3GB | Slowest | Best |
| mlx-community/whisper-large-v3-turbo | ~1.6GB | Fast | Excellent (Recommended) |
Notes
- Requires Apple Silicon Mac (M1/M2/M3/M4)
- Models cache to
~/.cache/huggingface/ - Default model is
mlx-community/whisper-tiny; use--model mlx-community/whisper-large-v3-turbofor best results
Usage Guidance
This skill is coherent for local speech-to-text on Apple Silicon, but before installing: (1) confirm you trust the 'mlx-whisper' PyPI package and its maintainer, (2) expect large model downloads (~100MB–3GB) to ~/.cache/huggingface/ (ensure disk space), and (3) run installs in a virtualenv or isolated environment if you want to limit risk. Network activity to download models is expected; if you require offline-only operation, verify models are pre-downloaded and trusted. If you need stronger assurances, review the upstream project source (the GitHub link) before installing/running the binary.
Capability Analysis
Type: OpenClaw Skill
Name: mlx-whisper
Version: 1.0.0
The skill bundle is benign. The `SKILL.md` file defines a standard `pip` installation for the `mlx-whisper` package, which is a legitimate tool for local speech-to-text on Apple Silicon. The instructions and usage examples provided are clear, directly related to the skill's stated purpose, and do not contain any prompt injection attempts, malicious commands, data exfiltration, or other high-risk behaviors. The `homepage` link points to a legitimate MLX project on GitHub.
Capability Assessment
Purpose & Capability
Name/description say local MLX Whisper for Apple Silicon; SKILL.md requires the mlx_whisper binary and documents usage and models. The declared install hint (pip package 'mlx-whisper') matches the stated capability. No unrelated credentials, binaries, or config paths are requested.
Instruction Scope
Instructions are simple command examples invoking the local mlx_whisper binary on audio/video files, and note where models cache (~/.cache/huggingface/). They do not instruct reading unrelated system files, exfiltrating data, or accessing unrelated env vars.
Install Mechanism
The SKILL.md contains an install metadata entry recommending 'pip install mlx-whisper'. This is a normal distribution mechanism for Python CLIs, but it means code will be installed from PyPI (moderate trust requirement) and the binary will run locally. Model files are downloaded on first use (network activity) — expected but worth noting.
Credentials
No environment variables, credentials, or config paths are required by the skill beyond the documented model cache path. That is proportionate to a local transcription tool that downloads public models.
Persistence & Privilege
Skill is not always-enabled and is user-invocable; it does not request persistent system-level changes or modify other skills' configurations. Autonomous invocation is allowed (platform default) but there are no additional privilege escalations requested.
How to Use
- Make sure OpenClaw is installed (local or Docker)
- Run the install command in chat:
/install mlx-whisper - After installation, invoke the skill by name or use
/mlx-whisper - Provide required inputs per the skill's parameter spec and get structured output
Version History
v1.0.0
- Initial release of mlx-whisper: Local speech-to-text using MLX Whisper, optimized for Apple Silicon Macs.
- No API key required; models are downloaded and cached on demand.
- Supports transcription, translation, and subtitle generation (SRT).
- Multiple models available with trade-offs in speed and quality.
- Simple command-line interface for quick audio transcription and subtitle creation.
Metadata
Frequently Asked Questions
What is Mlx Whisper?
Local speech-to-text with MLX Whisper (Apple Silicon optimized, no API key). It is an AI Agent Skill for Claude Code / OpenClaw, with 3702 downloads so far.
How do I install Mlx Whisper?
Run "/install mlx-whisper" in the OpenClaw or Claude Code chat to install it in one step — no extra setup required.
Is Mlx Whisper free?
Yes, Mlx Whisper is completely free (open-source). You can download, install and use it at no cost.
Which platforms does Mlx Whisper support?
Mlx Whisper is cross-platform and runs anywhere OpenClaw / Claude Code is available (cross-platform).
Who created Mlx Whisper?
It is built and maintained by Kevin37Li (@kevin37li); the current version is v1.0.0.
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