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在 OpenClaw 中安装
/install wechat-voice-decode
功能描述
专为微信 clawbot 设计的微信语音解析技能 / WeChat voice parsing skill for clawbot. 识别微信 SILK 语音，解码为 WAV，并用本地 Whisper 转写后回复。适用于微信语音、语音转文字、语音附件解析、‘这段语音说了什么’等场景。
安全使用建议
This skill appears to do what it says: read a provided audio file, decode SILK audio, and transcribe locally. Before installing or running it, consider: (1) Dependencies — you need python3, ffmpeg, and pip-installed packages (silk-python/pysilk and faster-whisper) which will be downloaded from the network; (2) Model weights — the Whisper model (base) will likely be downloaded the first time it runs and can be large and CPU/disk intensive; (3) Resource use — transcription runs locally and may be slow on CPU; (4) File access — the script reads the supplied audio path and writes a temporary WAV (default /tmp/wechat-voice-decoded.wav); ensure you only pass audio files you trust. If you want tighter control, preinstall packages and the model offline or run the skill in a sandboxed environment with restricted network access and disk quotas.
能力评估
Purpose & Capability
Name/description (WeChat SILK decode + local Whisper transcription) align with the included script and runtime notes. The script inspects file headers, decodes SILK via pysilk, falls back to ffmpeg, and transcribes with faster-whisper — all coherent with the declared purpose and expected local dependencies.
Instruction Scope
Instructions correctly limit actions to inspecting and decoding a provided audio file and transcribing it. They require access to the local attachment path (explicitly). One important operational note: faster-whisper/WhisperModel('base') will typically fetch model weights from the network on first run (and pip installs will download packages), so the skill may perform large external downloads and use significant local CPU/disk when invoked.
Install Mechanism
There is no automated install spec (instruction-only). The SKILL.md recommends pip user installs ('silk-python', 'faster-whisper') and expects ffmpeg and python3. This is low technical risk, but these steps involve network downloads from PyPI and (implicitly) model weight fetches — not written code from an arbitrary URL and no archive extraction in the install flow.
Credentials
The skill does not request environment variables, credentials, or unusual config paths. It only needs read access to the provided audio file and permission to write a temporary WAV (default /tmp/wechat-voice-decoded.wav), which is proportionate to its function.
Persistence & Privilege
always is false, the skill is user-invocable and not forced into every agent run. It does not modify other skills or request system-wide privileges.
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 wechat-voice-decode - 安装完成后，直接呼叫该 Skill 的名称或使用
/wechat-voice-decode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
v0.1.0
Initial release.
- Skill to identify, decode, and transcribe WeChat SILK voice messages to text using local Python tools.
- Reports whether the audio contains speech, is blank, too short, or unclear.
- Designed for Clawbot; integrates with local files and responds based on recognized content.
- Provides troubleshooting steps and installation guidance for required runtimes and Python packages.
v1.0.2
- 介绍精简更新，方便搜索
v1.0.1
- Added multilingual (Chinese + English) descriptions to increase usability for Chinese speakers.
- Expanded the introduction and usage scenarios to explicitly mention more WeChat-related cases in both Chinese and English.
- Core technical instructions and workflow remain unchanged.
- No code or file changes in this release; documentation update only.
v1.0.0
v1.0.0
通过silk-python实现解码微信语音，用faster-whisper进行语音转写
https://github.com/jozhn/wechat-voice-decode-skill
元数据
常见问题
Wechat Voice 是什么？
专为微信 clawbot 设计的微信语音解析技能 / WeChat voice parsing skill for clawbot. 识别微信 SILK 语音，解码为 WAV，并用本地 Whisper 转写后回复。适用于微信语音、语音转文字、语音附件解析、‘这段语音说了什么’等场景。 它是一个面向 Claude Code / OpenClaw 的 AI Agent Skill 插件，目前累计下载 176 次。
如何安装 Wechat Voice？
在 OpenClaw 或 Claude Code 对话框中运行命令「/install wechat-voice-decode」即可一键安装，无需额外配置。
Wechat Voice 是免费的吗？
是的，Wechat Voice 完全免费，采用 MIT-0 许可证，可自由下载、安装和使用。
Wechat Voice 支持哪些平台？
Wechat Voice 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 Wechat Voice？
由 jozhn（@jozhn）开发并维护，当前版本 v0.1.0。
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