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在 OpenClaw 中安装
/install whisper-voice-transcription
功能描述
Build and use whisper.cpp for local speech-to-text workflows, with optional cloud fallback when local transcription is not practical.
安全使用建议
This is an operator guide for building and running whisper.cpp and is coherent with its stated purpose. Before installing or following the guide: (1) verify you are cloning the correct upstream repository and, when downloading model files, prefer official release artifacts and verify checksums; (2) be cautious implementing any automated "search cache" fallback — restrict searches to known application cache paths and avoid broad home-directory scans; (3) explicitly prompt the user before sending audio to any cloud provider and confirm which API/endpoint will be used; (4) note that building from source requires developer tools (git, cmake, compiler, ffmpeg) and network access to fetch models. If you need the skill to operate autonomously, consider adding strict path whitelists and user consent prompts to reduce accidental data exposure.
能力评估
Purpose & Capability
Name and description match the SKILL.md: instructions show how to clone, build, and run whisper.cpp locally and describe optional cloud fallback. No unrelated credentials, binaries, or config paths are requested.
Instruction Scope
Overall instructions stay within the stated purpose (build/run local STT, optional cloud fallback). The fallback guidance to "locate the exact cache or upload path used by that tool" is vague and could lead an agent to read user files if implemented broadly; the doc does warn to restrict searches to expected app cache directories, but an implementer should be explicit about which paths are safe to access.
Install Mechanism
Instruction-only skill (no install spec). Build instructions clone the official ggerganov/whisper.cpp repo and build locally with cmake — this is expected and proportionate. No downloads from unknown/shortened/personal URLs or archive extraction steps are included.
Credentials
No environment variables or credentials are requested. Network access is implied for cloning and model download (GitHub/Hugging Face) but that is appropriate for the described functionality. If using Hugging Face private models or certain cloud APIs, additional creds would be reasonable but none are declared here.
Persistence & Privilege
Skill does not request persistent/always-on presence and does not modify other skills or system-wide settings. It is user-invocable and uses normal agent autonomy settings.
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 whisper-voice-transcription - 安装完成后，直接呼叫该 Skill 的名称或使用
/whisper-voice-transcription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
v1.1.1
Translate the guide to English and tighten the instructions around official downloads and scoped audio-file discovery.
v1.1.0
安全修复：移除非官方镜像域名，改用官方GitHub/HuggingFace源；移除系统特定路径；添加安全建议章节
v1.0.0
Initial publish: whisper.cpp + large-v3 本地语音转录方案，支持中文语音转文字
元数据
常见问题
Whisper Voice Transcription (whisper.cpp) 是什么？
Build and use whisper.cpp for local speech-to-text workflows, with optional cloud fallback when local transcription is not practical. 它是一个面向 Claude Code / OpenClaw 的 AI Agent Skill 插件，目前累计下载 107 次。
如何安装 Whisper Voice Transcription (whisper.cpp)？
在 OpenClaw 或 Claude Code 对话框中运行命令「/install whisper-voice-transcription」即可一键安装，无需额外配置。
Whisper Voice Transcription (whisper.cpp) 是免费的吗？
是的，Whisper Voice Transcription (whisper.cpp) 完全免费，采用 MIT-0 许可证，可自由下载、安装和使用。
Whisper Voice Transcription (whisper.cpp) 支持哪些平台？
Whisper Voice Transcription (whisper.cpp) 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 Whisper Voice Transcription (whisper.cpp)？
由 XuXu（@xuxuclassmate）开发并维护，当前版本 v1.1.1。
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