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在 OpenClaw 中安装
/install mlx-whisper
功能描述
Local speech-to-text with MLX Whisper (Apple Silicon optimized, no API key).
使用说明 (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
安全使用建议
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.
功能分析
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.
能力评估
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.
如何使用
- 确保已安装 OpenClaw（本地或 Docker 部署）
- 在对话框中输入安装命令：
/install mlx-whisper - 安装完成后，直接呼叫该 Skill 的名称或使用
/mlx-whisper触发 - 根据 Skill 的参数说明提供必要输入，即可获得结构化输出
版本历史
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.
元数据
常见问题
Mlx Whisper 是什么？
Local speech-to-text with MLX Whisper (Apple Silicon optimized, no API key). 它是一个面向 Claude Code / OpenClaw 的 AI Agent Skill 插件，目前累计下载 3702 次。
如何安装 Mlx Whisper？
在 OpenClaw 或 Claude Code 对话框中运行命令「/install mlx-whisper」即可一键安装，无需额外配置。
Mlx Whisper 是免费的吗？
是的，Mlx Whisper 完全免费（开源免费），可自由下载、安装和使用。
Mlx Whisper 支持哪些平台？
Mlx Whisper 跨平台运行，可在任意部署了 OpenClaw / Claude Code 的环境中使用（cross-platform）。
谁开发了 Mlx Whisper？
由 Kevin37Li（@kevin37li）开发并维护，当前版本 v1.0.0。
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