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在 OpenClaw 中安装
/install python-venv
功能描述
Python environment management skill. Automatically detect project type and existing environments, recommend based on popularity. Minimize interruptions, only...
安全使用建议
This skill is generally coherent for managing Python virtual environments, but be cautious before letting it run commands automatically. Two specific risks to consider: (1) The docs recommend installing 'uv' by piping a remote script from https://astral.sh (curl | sh / irm | iex). Avoid blind piping remote scripts — verify the source or install via your OS/package manager instead. (2) Troubleshooting recommends 'rm -rf .venv' to recover a broken venv, which will irreversibly delete the environment; require user confirmation before destructive actions. Also note the skill reads environment variables like VIRTUAL_ENV and CONDA_PREFIX and inspects project files (expected behavior) — ensure you trust the agent to run filesystem commands. If you want to reduce risk, require explicit user consent for installs and deletions, or run the recommended commands manually after reviewing them.
功能分析
Type: OpenClaw Skill
Name: python-venv
Version: 1.2.0
The skill automates Python environment management and package installation, including instructions in SKILL.md to execute commands like 'uv sync' or 'poetry install' without user confirmation when specific lockfiles are detected. It also contains 'curl|bash' and PowerShell 'iex' strings for installing the 'uv' tool from 'astral.sh' in troubleshooting.md. While these behaviors are aligned with the skill's stated purpose, the automated execution of potentially untrusted project files and the inclusion of remote install scripts represent significant security risks (RCE) that could be exploited, though no direct evidence of malicious intent was found.
能力评估
Purpose & Capability
Name and description align with the instructions: detecting project files, reusing/creating virtual environments, and choosing between uv/pip/conda/venv is coherent. The commands and file checks are directly relevant to environment management.
Instruction Scope
Runtime instructions reference system files and environment variables (e.g., .venv/, requirements.txt, $VIRTUAL_ENV, $CONDA_PREFIX) which is appropriate for detecting environments, but the skill also recommends destructive actions (rm -rf .venv) and automating remote installs and activations. It does not limit or require explicit user confirmation for those destructive or network-install actions.
Install Mechanism
Although the skill is instruction-only (no install spec), the troubleshooting doc instructs installing 'uv' by piping a remote script (curl ... | sh or irm ... | iex from https://astral.sh). Running a remote install script without verification is a high-risk pattern and should be treated cautiously.
Credentials
The skill declares no required environment variables, but its instructions read $VIRTUAL_ENV and $CONDA_PREFIX to detect active environments — this is normal and reasonable for the purpose. There are no unrelated credentials requested. Still, the skill will inspect filesystem and environment state, so consider that it can read project files and typical venv-related env vars.
Persistence & Privilege
Instruction-only skill, no install spec, always:false and no claimed persistence. It does not request system-wide config changes in the provided docs. Autonomous invocation is allowed by default (platform behavior) but not combined here with broad credential access.
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 python-venv - 安装完成后，直接呼叫该 Skill 的名称或使用
/python-venv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
v1.2.0
**English translation and language updates.**
- All instructions, explanations, and comments are now provided in English instead of Chinese.
- Modernized and clarified descriptions and headings.
- No major changes to logic, principles, or workflow content.
- Updated UI examples and table headers to English for wider accessibility.
v1.1.0
- Overhauled workflow to favor minimal user interaction: only prompt when necessary, auto-select when possible.
- Updated priority order for environment tools: prefer uv, then pip, conda, venv, poetry, pipenv.
- Added automatic tool selection based on project files (e.g., uv.lock, poetry.lock, environment.yml).
- Clarified detection and reuse of existing environments, reducing duplicate prompts.
- Rewrote documentation with concise decision flows, examples, and a focus on recommended best practices.
- All instructions and references now in Chinese for better accessibility to Chinese-speaking users.
v1.0.1
- Improved environment detection logic and description for clarity.
- Now prioritizes reusing uv and conda environments before standard venv.
- Interactive prompts expanded with example user options.
- Expanded when to use system Python vs. virtual environments.
- Added plain-language flowchart and reference commands for quick checks.
- Refined guidance for project file detection and tool selection.
v1.0.0
- Initial release defining core rules for requiring and reusing Python virtual environments before running scripts or installing packages.
- Provides detailed workflow and decision tree for venv detection, creation, and activation.
- Clarifies which scenarios require a virtual environment and which don’t (e.g., simple stdlib use).
- Includes project type detection and quick command references for Linux/macOS and Windows.
- Covers both venv and conda environment reuse and creation.
- Adds practical checklists, quick reference tables, and troubleshooting pointers.
元数据
常见问题
Python Venv 是什么？
Python environment management skill. Automatically detect project type and existing environments, recommend based on popularity. Minimize interruptions, only... 它是一个面向 Claude Code / OpenClaw 的 AI Agent Skill 插件，目前累计下载 313 次。
如何安装 Python Venv？
在 OpenClaw 或 Claude Code 对话框中运行命令「/install python-venv」即可一键安装，无需额外配置。
Python Venv 是免费的吗？
是的，Python Venv 完全免费，采用 MIT-0 许可证，可自由下载、安装和使用。
Python Venv 支持哪些平台？
Python Venv 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 Python Venv？
由 Simon（@cikichen）开发并维护，当前版本 v1.2.0。
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