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在 OpenClaw 中安装
/install musa-torch-coding
功能描述
Transcribe audio via OpenAI Audio Transcriptions API (Whisper).
安全使用建议
This skill's metadata and description (OpenAI Whisper transcription, OPENAI_API_KEY required) do not match the actual content (MUSA/torch guidance, CUDA->MUSA converter, YOLO template). Before installing or supplying secrets: 1) Do not provide your OPENAI_API_KEY — the code does not use it. 2) Confirm with the publisher what the skill is supposed to do; the mismatch may be a packaging error or mislabeling. 3) Inspect the included scripts locally (scripts/cuda_to_musa.py, assets/yolo8n_template.py, references/reference.md) — they appear to be benign conversion and template code with no network/exfiltration, but they do advise running build/install commands and privileged operations. 4) Do not run sudo commands (e.g., sudo usermod ...) or build/install steps until you trust the source and understand the effect on your system. 5) If you wanted an audio transcription skill, look for a different skill whose files, instructions, and required env vars actually reference the OpenAI transcription API.
功能分析
Type: OpenClaw Skill
Name: musa-torch-coding
Version: 1.0.0
The skill bundle contains a significant discrepancy in `SKILL.md`, where the metadata and description claim the skill is for OpenAI Whisper audio transcription and requires an `OPENAI_API_KEY`, while the actual instructions and code focus entirely on Moore Threads MUSA GPU programming. Requesting sensitive credentials that are unrelated to the functional content is a red flag for potential credential harvesting or poor supply chain hygiene. The provided Python scripts, such as `scripts/cuda_to_musa.py` and `assets/yolo8n_template.py`, appear to be legitimate utility tools for MUSA development.
能力评估
Purpose & Capability
Name/description claim: 'Transcribe audio via OpenAI Audio Transcriptions API (Whisper)'. Actual files and SKILL.md: MUSA (Moore Threads) torch guidance, CUDA-to-MUSA converter, YOLO template, and extensive environment/build instructions. The declared primary credential (OPENAI_API_KEY) and required binary (curl) are unrelated to the skill's true content.
Instruction Scope
The SKILL.md instructs system-level checks and operations appropriate for GPU setup (checking musaInfo, /usr/local/musa, modifying conda envs, build scripts). It also suggests privileged actions (e.g., 'sudo usermod -aG render $(whoami)', editing LD_LIBRARY_PATH, running build.sh). These instructions are coherent with MUSA GPU setup but entirely outside the advertised transcription purpose, and they can require elevated privileges on the host.
Install Mechanism
No install spec is provided (instruction-only), so nothing is automatically downloaded or executed during install. The skill includes code files (converter and templates) that will be present on disk, but there are no external URLs, archive extracts, or package installs declared.
Credentials
requires.env declares OPENAI_API_KEY as required and primaryEnv, but neither SKILL.md nor the included Python files reference OpenAI APIs or use that key. The SKILL.md also lists MUSA-specific environment variables (MUSA_VISIBLE_DEVICES, etc.) in prose but does not declare them as required. The declared required binary 'curl' is not used anywhere in the repository. Requesting an unrelated secret (OPENAI_API_KEY) is disproportionate and suspicious.
Persistence & Privilege
The skill does not set always:true and does not claim to modify other skills or system-wide agent settings. However, the runtime instructions encourage privileged system changes (adding user to 'render' group, running build/install scripts) which could have security implications if executed without review. The skill itself does not request persistent elevated agent 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 musa-torch-coding - 安装完成后，直接呼叫该 Skill 的名称或使用
/musa-torch-coding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
musa-torch-coding 1.0.0 – Initial release
- Provides a guide for generating PyTorch code compatible with Moore Threads (MUSA) GPUs using torch_musa.
- Documents key differences between CUDA and MUSA APIs.
- Outlines environment setup, detection, and usage of pre-configured conda environments for MUSA.
- Details code generation rules, including device selection and distributed training with mccl backend.
- Includes model templates, common code patterns, and troubleshooting tips specific to MUSA environments.
元数据
常见问题
musa-torch-coding 是什么？
Transcribe audio via OpenAI Audio Transcriptions API (Whisper). 它是一个面向 Claude Code / OpenClaw 的 AI Agent Skill 插件，目前累计下载 254 次。
如何安装 musa-torch-coding？
在 OpenClaw 或 Claude Code 对话框中运行命令「/install musa-torch-coding」即可一键安装，无需额外配置。
musa-torch-coding 是免费的吗？
是的，musa-torch-coding 完全免费，采用 MIT-0 许可证，可自由下载、安装和使用。
musa-torch-coding 支持哪些平台？
musa-torch-coding 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 musa-torch-coding？
由 peli（@lipeidcc）开发并维护，当前版本 v1.0.0。
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