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Install in OpenClaw
/install local-whisper
Description
Local speech-to-text using OpenAI Whisper. Runs fully offline after model download. High quality transcription with multiple model sizes.
Usage Guidance
Install only if you are comfortable installing ffmpeg, Python Whisper/Torch dependencies, and downloading a Whisper model on first use. After that, the described workflow is local transcription of audio files, but audio content may be sensitive, so choose files intentionally.
Capability Analysis
Type: OpenClaw Skill
Name: local-whisper
Version: 1.0.0
The skill bundle provides local speech-to-text functionality using OpenAI Whisper. The `SKILL.md` clearly outlines its purpose, usage, and setup, including legitimate dependencies like `ffmpeg` and Python libraries `openai-whisper` and `torch` from trusted sources (download.pytorch.org). The `scripts/transcribe.py` script correctly implements the transcription logic without any signs of data exfiltration, malicious execution, persistence, or prompt injection against the agent. The only network activity is the expected initial download of Whisper models by the `openai-whisper` library, which is consistent with the 'offline after model download' description.
Capability Assessment
Purpose & Capability
The described capability, local audio transcription with OpenAI Whisper, matches the supplied metadata and script behavior.
Instruction Scope
Runtime instructions appear focused on transcribing user-selected audio files and do not show prompt-injection, role override, unrelated automation, or broad local indexing behavior.
Install Mechanism
Setup uses expected dependencies for this purpose, including ffmpeg, openai-whisper, torch, and an initial Whisper model download; users should approve these installs and model downloads explicitly.
Credentials
Local file access to audio inputs and local model execution are proportionate to speech-to-text functionality, with no supplied evidence of uploads or credential/session use.
Persistence & Privilege
No evidence of background services, privilege escalation, startup persistence, destructive actions, or credential storage was supplied.
How to Use
- Make sure OpenClaw is installed (local or Docker)
- Run the install command in chat:
/install local-whisper - After installation, invoke the skill by name or use
/local-whisper - Provide required inputs per the skill's parameter spec and get structured output
Version History
v1.0.0
- Initial release of local-whisper: local speech-to-text using OpenAI Whisper, fully offline after model download.
- Supports multiple model sizes for different speed/quality needs: tiny, base (default), small, turbo, large-v3.
- Includes options for language selection, timestamps, JSON output, and quiet mode.
- Provides clear setup instructions using uv-managed Python virtual environment.
- Requires ffmpeg for audio processing.
Metadata
Frequently Asked Questions
What is Local Whisper?
Local speech-to-text using OpenAI Whisper. Runs fully offline after model download. High quality transcription with multiple model sizes. It is an AI Agent Skill for Claude Code / OpenClaw, with 13524 downloads so far.
How do I install Local Whisper?
Run "/install local-whisper" in the OpenClaw or Claude Code chat to install it in one step — no extra setup required.
Is Local Whisper free?
Yes, Local Whisper is completely free (open-source). You can download, install and use it at no cost.
Which platforms does Local Whisper support?
Local Whisper is cross-platform and runs anywhere OpenClaw / Claude Code is available (cross-platform).
Who created Local Whisper?
It is built and maintained by araa47 (@araa47); the current version is v1.0.0.
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