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在 OpenClaw 中安装
/install local-whisper
功能描述
Local speech-to-text using OpenAI Whisper. Runs fully offline after model download. High quality transcription with multiple model sizes.
安全使用建议
Install it as an unprivileged user, expect a large initial model/dependency download, and consider pinning or reviewing package versions if you need reproducible or tightly controlled installs.
功能分析
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.
能力评估
Credentials
The skill needs ffmpeg, local model files, and access to the chosen audio file, which is proportionate for offline transcription after the initial model download.
Install Mechanism
Setup uses a uv-managed .venv and installs click, openai-whisper, and torch from a documented HTTPS package index, but the dependencies are not pinned or hash-locked.
Instruction Scope
Runtime behavior is narrow and user-directed, but the usage examples reference scripts/local-whisper while the inspected artifact contains scripts/transcribe.py; this looks like a packaging/usability mismatch rather than hidden security behavior.
Persistence & Privilege
No services, startup hooks, credential access, memory writes, privilege escalation, destructive actions, or cross-session backdoors were found; persistence is limited to the skill files, virtual environment, and normal model cache behavior.
Purpose & Capability
The stated purpose is local Whisper speech-to-text, and the bundled script loads a selected Whisper model, transcribes a user-provided audio file, and prints text or JSON output.
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 local-whisper - 安装完成后，直接呼叫该 Skill 的名称或使用
/local-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 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.
元数据
常见问题
Local Whisper 是什么？
Local speech-to-text using OpenAI Whisper. Runs fully offline after model download. High quality transcription with multiple model sizes. 它是一个面向 Claude Code / OpenClaw 的 AI Agent Skill 插件，目前累计下载 13956 次。
如何安装 Local Whisper？
在 OpenClaw 或 Claude Code 对话框中运行命令「/install local-whisper」即可一键安装，无需额外配置。
Local Whisper 是免费的吗？
是的，Local Whisper 完全免费（开源免费），可自由下载、安装和使用。
Local Whisper 支持哪些平台？
Local 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 Local Whisper？
由 araa47（@araa47）开发并维护，当前版本 v1.0.0。
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