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python-venvPython venv 测试

Agent Skill

用于辅助 Python 项目开发、测试、依赖管理和常见框架工作流。它适合让 Agent 阅读 Python 代码、定位测试问题、整理运行命令、生成脚本或分析数据处理逻辑。使用时需要确认项目虚拟环境、依赖版本和测试入口;涉及执行脚本、读写文件、访问数据库或调用外部 API 时,应先明确运行目录和输入输出范围,避免误改生产数据。

总安装

9,709

周安装

389

GitHub Stars

公开资料未说明

下载量

3,143
OpenClaw

安装说明

本站只整理中文说明和来源信息,不托管安装包,也不代用户安装。

GitHub

来源数

2

许可证

MIT-0

最后核验

2026-05-01

来源状态

来源可访问

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:python-venv(Python venv 测试)
来源仓库:https://github.com/cikichen/python-venv
安装命令:
openclaw skills install python-venv
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。该命令会通过 OpenClaw 从第三方来源获取 Skill;本站只展示命令,不托管安装包,也不自动执行。

ClawHubOpenClaw
openclaw skills install python-venv

简介

智能管理 Python 虚拟环境,自动检测项目类型。

  • 适合在 OpenClaw 中隔离依赖版本或切换开发分支时使用。
  • 减少环境冲突,仅推荐主流稳定方案。python-venv 属于效率类 Skill,可作为该场景下的辅助能力补充。
  • 安装命令:openclaw skills install python-venv。
  • 操作前请确认当前目录无重要未提交更改。

SKILL.md

name
python-venv
description
Python environment management skill. Automatically detect project type and existing environments, recommend based on popularity. Minimize interruptions, only ask when necessary.

Python Environment Management Skill

Core Principles

  1. Reuse Existing Environments - Don't recreate, reuse existing virtual environments
  2. Use Project-Type Decision - Auto-select based on lock files
  3. Recommend by Popularity - uv > pip > conda > venv
  4. Minimize Interruption - Only ask when necessary

Tool Popularity Ranking

PriorityToolBest For
🥇uvNew projects, fast installs
🥈pipCompatibility first
🥉condaData science, specific versions
4venvBuilt-in, no extra install
5poetryExisting poetry.lock
6pipenvExisting Pipfile (declining)

Decision Flow

┌─────────────────────────────────────┐
│  Detect project dependency files     │
└─────────────────────────────────────┘
              ↓
    ┌─────────┴─────────┐
    ↓                   ↓
  Clear decision       Unclear
    ↓                   ↓
  Use directly     Detect existing env
                        ↓
                  ┌─────┴─────┐
                  ↓           ↓
              Has env        No env
                  ↓           ↓
              Reuse      Assess complexity
                            ↓
                  ┌─────────┴─────────┐
                  ↓                   ↓
              Simple task       Needs deps
                  ↓                   ↓
            System Python      Recommend uv/conda

1. Clear Decisions (Execute Directly, No Ask)

When these files are detected, use the corresponding tool directly:

Detected FileExecute
uv.lock existsuv sync or uv pip install -r requirements.txt
poetry.lock existspoetry install
environment.yml existsconda env create -f environment.yml
Pipfile.lock existspipenv install

2. Detect Existing Environments (Reuse First)

# Priority: uv venv > conda > venv

# 2.1 Detect uv virtual environment
ls -la .venv/ 2>/dev/null && uv pip list 2>/dev/null | head -3

# 2.2 Detect conda environment
conda info --envs 2>/dev/null | grep "*" || echo $CONDA_PREFIX

# 2.3 Detect standard venv
ls -la venv/ .venv/ env/ 2>/dev/null

# 2.4 If exists → Reuse (activate and run commands)

Reuse Example:

Detected existing .venv/ directory
→ Activate: source .venv/bin/activate
→ Run: uv pip install <package>

3. When Unclear (Assess Complexity)

ScenarioAction
Stdlib only, no 3rd partySystem Python (python3)
Simple pip install testSystem Python (temp)
Has requirements.txtRecommend uv > pip > venv
Has pyproject.tomlRecommend uv > pip
Multi-file project, needs isolationRecommend uv

4. When to Ask User (Only These Cases)

Ask:

  1. Empty project + first dependency install → Ask which tool
  2. Both requirements.txt + pyproject.toml → Ask which to use
  3. User explicitly wants different tool → e.g., "I want conda"

Don't Ask:

  • Has uv.lock but user didn't specify
  • Has .venv/ directory
  • Regular pip install task

5. Recommended Tool (No Clear Directive)

First: uv
  ├── uv venv (create)
  ├── uv pip install (install)
  └── uv sync (sync)

Backup: pip
  ├── python3 -m venv .venv
  └── pip install

Special: conda
  ├── conda create -n envname python=x.x
  └── conda env create

Detection Commands

# Check available tools
which uv
which conda
which pip
which python3

# Check project files
ls -la *.lock pyproject.toml requirements.txt environment.yml Pipfile 2>/dev/null

# Check existing environments
ls -la .venv/ venv/ env/ 2>/dev/null
conda info --envs 2>/dev/null

# Check current environment
echo $VIRTUAL_ENV
echo $CONDA_PREFIX

Interaction Examples (Only When Needed)

🔍 Detection result:
- Project file: pyproject.toml
- Existing env: None
- Recommended: uv (fastest)

Running: uv pip install <package>
🔍 Detection result:
- Project file: requirements.txt
- Existing env: None
- Recommended: uv

Available options:
1) uv (recommended) - faster
2) pip - better compatibility
3) venv - uses stdlib
4) conda - if specific version needed

Enter option or press Enter to use recommended:

Quick Command Reference

Actionuvpipcondavenv
Create envuv venv-conda createpython3 -m venv
Install pkguv pip installpip installconda installpip install
Install depsuv syncpip install -rconda env createpip install -r
Activate(auto)(auto)conda activatesource venv/bin/activate

Core Principle

"Do more, ask less" - Execute directly when you can determine, only ask when truly unclear.

适合场景

01

OpenClaw 用户查找和安装 Skill 时

02

用户想查找某类 Agent Skill 时

03

需要根据任务场景推荐可安装能力包时

04

需要对比不同来源的安装命令和来源信息时

能力概览

能力 1

按任务关键词查找相关 Skills

能力 2

展示可复制的安装命令

能力 3

保留来源站点、仓库和原始说明,方便继续核验

能力 4

补充不同宿主或平台的使用分布数据

能力 5

展示第三方安全扫描或审计结果

安装后应在对应宿主中按原始 README 的触发条件使用;具体调用方式请以来源页面和 README 为准。

平台分布

OpenClaw

77.29%
按下载量换算2,429

安全审计

VirusTotal

可疑

ClawScan

可疑

Static analysis

通过

权限和风险

只读

该 Skill 主要提供规则、说明或参考内容,本身偏只读;真正读写文件、联网或执行命令仍取决于宿主 Agent 的任务。

安装前确认

本站仅展示第三方公开信息,不托管安装包,不提供自动安装或运行环境。安装前应自行审查源码、依赖和命令行为。来源安全扫描存在 warning/failed 结果,不能写成本站确认安全。当前只有一个来源,正式发布前建议补源仓库或其他目录站核验。

来源信息

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