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Install in OpenClaw
/install mj-windows-faster-whisper
Description
Local speech-to-text with the faster-whisper backend (CTranslate2). Use when transcribing audio locally, setting up the faster-whisper model cache, or replac...
Usage Guidance
This skill appears to be what it says: a helper for running faster-whisper locally. Before installing or following the steps, consider that: (1) pip-installing packages and downloading models will fetch third-party code and files from the network — use a virtual environment and review packages if you are cautious; (2) model files can be large and require disk space; (3) if you need a private model you may need a Hugging Face token (the skill does not request any secrets by default); (4) the SKILL.md gives a Windows-style example path — adapt it to your OS and avoid hardcoding usernames; and (5) ensure you have permission to transcribe any audio you process. If those points are acceptable, the skill's instructions are proportionate to its purpose.
Capability Assessment
Purpose & Capability
The skill is described as a local faster-whisper (CTranslate2) transcription helper and its instructions request exactly the things needed for that: python/ffmpeg availability, installing faster-whisper/ctranslate2/huggingface_hub, and downloading a CTranslate2-style model folder from Hugging Face.
Instruction Scope
Instructions are scoped to setting up and using a local model (convert OGG/Opus to WAV, load a local model folder, transcribe). They explicitly reference GitHub and Hugging Face for downloads — this requires network access and may require authentication for private models. The example local path uses a specific Windows username (C:\Users\joshu...), which is just an example but could confuse non-Windows users; otherwise the runtime instructions do not ask to read unrelated files or secrets.
Install Mechanism
This is an instruction-only skill (no install spec). It tells the user/agent to pip-install packages (faster-whisper, ctranslate2, huggingface_hub) and to download a model from Hugging Face. Installing packages from PyPI and downloading models are expected for this use case but do involve running third-party code and transferring model files from the network — normal for local ML tooling but worth noting.
Credentials
The skill declares no required environment variables or credentials and its instructions do not demand unrelated secrets. The only possible credential scenario is an optional Hugging Face token if the chosen model is private or rate-limited, which is consistent with the stated workflow.
Persistence & Privilege
The skill does not request always:true, does not modify system-wide configs in its instructions, and is instruction-only (no code writing or autonomous persistence). Its requested level of presence is proportionate.
How to Use
- Make sure OpenClaw is installed (local or Docker)
- Run the install command in chat:
/install mj-windows-faster-whisper - After installation, invoke the skill by name or use
/mj-windows-faster-whisper - Provide required inputs per the skill's parameter spec and get structured output
Version History
v1.0.0
Windows-local faster-whisper setup with benchmark-cleaned workflow and local model paths.
Metadata
Frequently Asked Questions
What is MJ Windows Faster Whisper?
Local speech-to-text with the faster-whisper backend (CTranslate2). Use when transcribing audio locally, setting up the faster-whisper model cache, or replac... It is an AI Agent Skill for Claude Code / OpenClaw, with 71 downloads so far.
How do I install MJ Windows Faster Whisper?
Run "/install mj-windows-faster-whisper" in the OpenClaw or Claude Code chat to install it in one step — no extra setup required.
Is MJ Windows Faster Whisper free?
Yes, MJ Windows Faster Whisper is completely free, licensed under MIT-0. You can download, install and use it at no cost.
Which platforms does MJ Windows Faster Whisper support?
MJ Windows Faster Whisper is cross-platform and runs anywhere OpenClaw / Claude Code is available (cross-platform).
Who created MJ Windows Faster Whisper?
It is built and maintained by magejosh (@magejosh); the current version is v1.0.0.
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