Token导航 LogoToken导航

Agent Skill · 开发

uv-tool-management(uv 工具管理)

uv-tool-management 用于处理 GitHub 仓库、Issue、Pull Request 和代码协作信息,适合在 Codex、Claude、Cursor、Gemini CLI 中需要围绕仓库状态、代码变更或协作事项进行整理时使用。可结合来源仓库、安装命令和原始 README 继续核验具体用法。安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。

uv-tool-management 是开发类 Agent Skill,可用宿主为 Codex、Claude、Cursor、Gemini CLI,通过GitHub 仓库获取,权限为执行命令;许可证信息还不明确,第三方扫描有未通过项,按安装量在开发类的 21,746 个 Skill 里排第 21,366。

总安装 190周安装 8GitHub Stars 1下载 67核验 2026-05-01

安装说明

本站只整理中文说明,不托管安装包,也不代用户安装。
GitHub
许可证
unknown

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:uv-tool-management(uv 工具管理)
来源仓库:https://github.com/dawiddutoit/custom-claude
仓库路径:skills/uv-tool-management
安装命令:
npx skills add https://github.com/dawiddutoit/custom-claude --skill uv-tool-management
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 npx skills 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。

skills.shnpx skills
npx skills add https://github.com/dawiddutoit/custom-claude --skill uv-tool-management

这个 Skill 是做什么的

开发类 Skill 面向写代码、改代码和排查问题,一般会读写仓库文件,部分还会执行构建或测试命令。

用于处理 GitHub 仓库、Issue、Pull Request 和代码协作信息。适合在 Codex、Claude、Cursor、Gemini CLI 中围绕仓库状态、代码变更或协作事项进行整理。通过 npx skills add 命令从指定 GitHub 仓库安装并使用。

安装前需确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写操作。uv-tool-management 属于开发类 Skill,可作为该场景下的辅助能力补充。

来源仓库内路径:skills/uv-tool-management

上手步骤

4 步
  1. 1

    确认自己的宿主工具

    公开资料标注支持 Codex、Claude、Cursor、Gemini CLI;先确认自己用的是其中之一,再按对应工具的 Skills 目录放置。

  2. 2

    拿到安装命令

    可以直接复制的命令是 npx skills add https://github.com/dawiddutoit/custom-claude --skill uv-tool-mana…;命令里的占位符换成自己的路径或密钥再执行。

  3. 3

    安装后重启宿主

    命令执行完要完全退出宿主工具再打开,让新装的 Skill 被重新扫描到,否则列表里可能看不到。

  4. 4

    按最小权限试用

    它需要执行命令,先在测试目录或测试账号里跑,确认没问题再放到正式项目。

常见问题

6 条

uv-tool-management 怎么安装?

在终端执行 npx skills add https://github.com/dawiddutoit/custom-claude --skill uv-tool-management。装完完全退出宿主工具再打开,让它重新扫描本地 Skill。

uv-tool-management 支持哪些 AI 工具?

公开资料标注支持 Codex、Claude、Cursor、Gemini CLI。其他工具只要能读取本地 Skill 目录,一般也能手动放进去,但要自己确认触发方式是否一致。

uv-tool-management 需要什么权限?

权限级别是执行命令。安装流程涉及命令执行,可能通过 npx skills add https://github.com/dawiddutoit/custom-claude --skill uv-tool-management 联网下载 Skill 或依赖。用户安装前应确认命令来源、仓库内容和执行环境。

uv-tool-management 是免费的吗?

公开资料没有标注明确许可证,收费和商用限制都无法确认。正式使用前请到来源仓库核对授权说明。

uv-tool-management 用的人多吗?

公开数据是累计安装 190 次,近一周安装 8 次,下载 67 次,GitHub 1 星。这些数字来自第三方目录统计,只能当作热度参考,不代表质量或安全性。

uv-tool-management 安全吗?

第三方扫描有未通过项,风险较高。除非你确认过源码,否则不建议直接安装到常用环境。

值得选的地方和要先想清楚的地方

值得选的地方

  • 同时适配 4 种工具,换客户端不用重新找替代品。

先想清楚的地方

  • 需要执行命令,装到常用环境前要先评估影响面。
  • 许可证没有明确标注,能不能商用、能不能再分发都不确定。
  • 第三方扫描存在提醒项或未通过项,需要人工逐条确认。
  • 第三方目录整理,版本更新和行为细节以来源仓库为准。

适不适合你

更适合

  • 已经在用 Codex,想直接扩展它能力的人。
  • 需要处理开发类任务、又不想每次都手写提示词的人。

不太适合

  • 不能接受 Skill 在你机器上执行命令的人。
  • 需要明确授权才能用到公司项目里的场景。
  • 需要厂商级技术支持和 SLA 的生产系统。

开发类 Skill 对比

6 个同类
Skill总安装GitHub 星权限许可证扫描
skill-vetter

技能审查员 · OpenClaw

8,779,018986操作浏览器MIT-0通过
ontology

本体论 · OpenClaw

6,636,960576只读MIT-0通过
entra-app-registration

内部应用程序注册 · Codex、Claude

6,631,872764接触敏感数据未明确通过
entra-app-registration

内部应用程序注册 · Codex、Claude

3,757,680201接触敏感数据未明确通过
nano-banana-pro

纳米香蕉专业版 · OpenClaw

3,526,898364接触敏感数据MIT-0有提醒
uv-tool-management

uv 工具管理 · 本页

1901执行命令未明确未通过

按安装量取同分类前几名;数字来自第三方目录统计,只作热度参考,不代表质量结论。

SKILL.md 原文

uv Tool Management

Purpose

This skill teaches you how to efficiently manage Python command-line tools using uv, including running tools on-demand without installation, installing persistent tools globally, managing versions, and understanding when to use tools versus project dependencies.

Quick Start

Run any CLI tool without installing it:

# Run ruff (Python linter) once without installation
uvx ruff check .

# Equivalent longer form
uv tool run ruff check .

# Install a tool permanently for repeated use
uv tool install ruff

# Then run the installed tool
ruff check .

Instructions

Step 1: Understand the Tool Management Landscape

uv replaces pipx for tool management. There are three main approaches:

uvx (temporary execution): Run a tool once without installation

  • Tool is fetched, cached, and executed in an isolated environment
  • No modification to your system
  • Ideal for: occasional use, trying tools, CI/CD where tools aren't needed repeatedly

uv tool install (persistent installation): Install a tool for repeated use

  • Tool is installed globally in a dedicated environment
  • Available in PATH after installation
  • Ideal for: tools you use regularly (linters, formatters, test runners)

uv run (project environment): Run tools that need access to your project

  • Tools run within your project's virtual environment
  • Can access your project's installed packages
  • Ideal for: testing, linting, formatting your project code

Step 2: Choose Between uvx and uv tool install

Use uvx (ephemeral) when:

  • Running a tool for the first time to test it
  • Tool is used rarely or on-demand
  • You want no installation footprint
  • Running in CI/CD pipelines (cleaner, no persistent state)
  • Tool has conflicting dependencies with other tools
# Try a new tool without committing to it
uvx httpie https://api.github.com/users/github

# Run a tool on-demand in CI
uvx mypy src/

# Run tool from different package
uvx --from httpie http https://example.com

Use uv tool install (persistent) when:

  • Tool is part of your regular workflow
  • Team uses it consistently (document in README)
  • Tool provides utility functions beyond single invocation
  • You want faster execution (no download overhead each time)
  • Tool is referenced in project docs or scripts
# Install tools you use daily
uv tool install ruff
uv tool install black
uv tool install mypy

# Then run directly without prefix
ruff check .
black --check src/
mypy src/

Use uv run (project environment) when:

  • Running tests, linters, or formatters on your project
  • Tool needs access to project dependencies
  • Running from within project directory
  • Tool is listed in project's dev dependencies
# Test runner needs access to project (test libraries, modules)
uv run pytest tests/

# Linter running on project code
uv run mypy src/

# Format project code
uv run black src/

Step 3: Run Tools with uvx

Basic execution without arguments:

uvx ruff check .
uvx black --check src/

Specify exact version:

# Run specific version of a tool
uvx ruff@0.3.0 check .

# Use version constraint
uvx --from 'ruff>=0.3.0,<0.4.0' ruff check .

Run tools from different packages:

# httpie is in package 'httpie', command is 'http'
uvx --from httpie http https://api.github.com

# mkdocs is in 'mkdocs', command is 'mkdocs'
uvx mkdocs serve

Include optional dependencies (extras):

# mypy with optional faster caching
uvx --from 'mypy[faster-cache]' mypy src/

# mkdocs with material theme
uvx --with mkdocs-material mkdocs serve

Run with specific Python version:

# Run tool with Python 3.10 (useful for compatibility testing)
uvx --python 3.10 ruff check .

# Ensure tool runs on minimum supported version
uvx --python 3.9 pytest tests/

Run from git repository:

# Install directly from GitHub
uvx --from git+https://github.com/httpie/cli httpie

Step 4: Install and Manage Persistent Tools

Install tools:

# Install latest version
uv tool install ruff

# Install specific version
uv tool install ruff@0.3.0

# Install with extras
uv tool install 'mypy[faster-cache]'

# Install from git
uv tool install git+https://github.com/user/tool

List installed tools:

uv tool list

# Example output:
# black           0.23.11  /Users/user/.local/bin/black
# mypy            1.7.0    /Users/user/.local/bin/mypy
# ruff            0.3.0    /Users/user/.local/bin/ruff

Upgrade tools:

# Upgrade specific tool to latest
uv tool upgrade ruff

# Upgrade all tools
uv tool upgrade --all

# Upgrade to specific version
uv tool upgrade ruff@0.4.0

Uninstall tools:

# Remove installed tool
uv tool uninstall ruff

# Remove multiple tools
uv tool uninstall ruff black mypy

Step 5: Understand Tool vs Project Dependencies

Critical distinction for your workflow:

# pyproject.toml

[project]
# Main project dependencies - needed to run your application
dependencies = [
    "fastapi>=0.104.0",
    "httpx>=0.27.0",
]

[project.optional-dependencies]
# Optional features for your application (not development tools)
aws = ["boto3>=1.34.0"]
database = ["sqlalchemy>=2.0.0"]

[dependency-groups]
# Development tools - only needed while developing
test = [
    "pytest>=8.0.0",
    "pytest-cov>=4.1.0",
]
lint = [
    "ruff>=0.1.0",
    "mypy>=1.7.0",
]
format = [
    "black>=23.11.0",
]

Decision matrix:

Use CaseToolCommandWhere
Try a new linteruvxuvx flake8.Any directory
Lint project code regularlyuv runuv run ruff check.Project directory
Lint tool used across projectsuv tool installruff check.Any directory
Test codeuv runuv run pytestProject directory
Build documentationuv tool installuv tool install mkdocsGlobal install
One-time script executionuvxuvx httpieAny directory
Format codeuv runuv run black src/Project directory

Step 6: Manage Tool Versions and Upgrades

Check installed version:

# Show version of installed tool
ruff --version

# Or via uv
uv tool list | grep ruff

Upgrade specific tool:

# Upgrade to latest
uv tool upgrade ruff

# Keep all tools up to date
uv tool upgrade --all

Pin tool version:

# Use specific version (best practice for team consistency)
uv tool install ruff@0.3.0

# Override installed version
uv tool install ruff@0.4.0

Clean up old tools:

# Uninstall unused tools
uv tool uninstall old-tool

# Check what's installed
uv tool list

# Free up disk space
uv cache prune

Step 7: Handle Tool Dependencies and Conflicts

Tools with conflicting dependencies:

# These tools both depend on different versions of a library
# uvx creates isolated environments, avoiding conflicts
uvx tool-a
uvx tool-b

# Both run in separate, isolated environments
# No dependency conflicts

Tools requiring additional packages:

# Add extra packages to tool execution
uvx --with mkdocs-material mkdocs serve

# Tool runs with mkdocs + mkdocs-material installed

Specific Python version for tool:

# Some tools require specific Python versions
# Ensure compatibility
uvx --python 3.9 older-tool

# Run with minimum supported Python
uvx --python 3.10 modern-tool

Examples

Example 1: One-Time Tool Usage (uvx)

You need to check code quality but don't use ruff regularly:

# Run ruff once to check your code
uvx ruff check .

# Output analysis but don't install anything
# After execution, no system changes
# Next time you run it, it's fetched again (but cached locally)

Example 2: Regular Linting in Project (uv run)

Your project uses ruff as a dev dependency:

# In your project directory
cd my-project

# Edit pyproject.toml to add ruff to dev dependencies
# [dependency-groups]
# lint = ["ruff>=0.1.0"]

# Sync environment
uv sync --group lint

# Run linter from project environment
uv run ruff check .

# Everyone on team uses same ruff version (from uv.lock)

Example 3: Global Tool Installation (uv tool install)

You use ruff across multiple projects:

# Install once globally
uv tool install ruff

# Use in any directory
cd project-a && ruff check .
cd ../project-b && ruff check .

# No project setup needed
# Tool always available in PATH

Example 4: Test Different Python Versions

You need to verify code works on Python 3.10 and 3.12:

# Run with Python 3.10
uvx --python 3.10 pytest tests/

# Run with Python 3.12
uvx --python 3.12 pytest tests/

# Each uses different Python version
# No installation overhead

Example 5: Tool with Extras

mypy runs faster with optional faster-cache feature:

# Via uvx (temporary)
uvx --from 'mypy[faster-cache]' mypy src/

# Via uv tool install (persistent)
uv tool install 'mypy[faster-cache]'
mypy src/

Example 6: CI/CD Pipeline

Your CI uses different tools without installation:

# .github/workflows/ci.yml
- name: Lint code
  run: uvx ruff check .

- name: Type check
  run: uvx mypy src/

- name: Format check
  run: uvx black --check .

- name: Test
  run: |
    uv sync --group test
    uv run pytest tests/

Each step is clean, isolated, no tool installation overhead.

Example 7: Cleanup and Maintenance

Remove old tools and free disk space:

# See what's installed
uv tool list

# Remove tool you no longer use
uv tool uninstall old-formatter

# Prune cache of unused packages
uv cache prune

# Check cache location and size
uv cache dir

Requirements

  • uv installed (install via: curl -LsSf https://astral.sh/uv/install.sh | sh)
  • Python 3.8+ available (for running tools)
  • Understanding of your project's dependency structure

See Also

平台分布

Codex

34.21%
按下载量换算23

Claude

27.02%
按下载量换算18

Cursor

19.97%
按下载量换算13

Gemini CLI

9.43%
按下载量换算6

安全审计

Gen Agent Trust Hub

通过

Socket

未通过

Snyk

可疑

权限和风险

执行命令

安装流程涉及命令执行,可能通过 npx skills add https://github.com/dawiddutoit/custom-claude --skill uv-tool-management 联网下载 Skill 或依赖。用户安装前应确认命令来源、仓库内容和执行环境。

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。来源安全扫描存在提醒或未通过项,安装前请自行复核。目前只有一个公开来源,建议同时核对源仓库。

继续浏览同类 Skills