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Agent Skill · 待分类

uv-dependency-management(uv 依赖管理)

uv-dependency-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-dependency-management 是待分类类 Agent Skill,可用宿主为 Codex、Claude、Cursor、Gemini CLI,通过GitHub 仓库获取,权限为需要联网;许可证信息还不明确,第三方扫描有未通过项,按安装量在待分类类的 11,209 个 Skill 里排第 10,868。

总安装 188周安装 8GitHub Stars 1下载 66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-dependency-management(uv 依赖管理)
来源仓库:https://github.com/dawiddutoit/custom-claude
仓库路径:skills/uv-dependency-management
安装命令:
npx skills add https://github.com/dawiddutoit/custom-claude --skill uv-dependency-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-dependency-management

这个 Skill 是做什么的

这个 Skill 的分类还没最终确定,用法以来源仓库的说明为准。

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-dependency-management 属于待分类类 Skill,可作为该场景下的辅助能力补充。

来源仓库内路径:skills/uv-dependency-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-dependenc…;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

    它需要需要联网,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-dependency-management 怎么安装?

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

uv-dependency-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-dependency-management 需要什么权限?

权限级别是需要联网。该 Skill 可能需要联网访问来源站点、仓库或外部 API;具体网络访问范围需要结合源码和 README 复核。

uv-dependency-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-dependency-management 用的人多吗?

公开数据是累计安装 188 次,近一周安装 8 次,下载 66 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-dependency-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

  • 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。
  • 需要处理待分类类任务、又不想每次都手写提示词的人。

不太适合

  • 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。

待分类类 Skill 对比

6 个同类
Skill总安装GitHub 星权限许可证扫描
infsh-cli

infsh CLI · Codex、Claude

4,374,576382权限未标注未明确未收录
ai-video-generation

AI 视频生成 · Codex、Claude

4,313,376382调用外部服务未明确有提醒
lark-openapi-explorer

云雀 OpenAPI 浏览器 · Codex、Claude

2,064,1209,011需要联网未明确有提醒
lark-workflow-standup-report

Lark 工作流程站立报告 · Codex、Claude

2,041,6328,978需要联网未明确通过
use-my-browser

使用我的浏览器 · Codex、Claude

1,848,49140操作浏览器未明确未通过
uv-dependency-management

uv 依赖管理 · 本页

1881需要联网未明确未通过

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 Dependency Management

Purpose

Master dependency management with uv, including adding/removing packages, version constraints, dependency groups for development and production, lock files, and resolving version conflicts.

Quick Start

Add a dependency and see it in your lock file:

# Add a package with version constraint
uv add "requests>=2.31.0"

# View your dependency tree
uv tree

# Update all dependencies to latest compatible versions
uv lock --upgrade

Your pyproject.toml is automatically updated, and uv.lock ensures reproducible installs.

Instructions

Step 1: Understand Dependency Scopes

uv manages three types of dependencies:

Main Dependencies (project requirements)

[project]
dependencies = [
    "fastapi>=0.104.0",
    "sqlalchemy>=2.0.0",
]

Optional Dependencies (extras for features)

[project.optional-dependencies]
database = ["psycopg2-binary>=2.9.0"]
aws = ["boto3>=1.34.0"]

Development Groups (dev-only tools)

[dependency-groups]
dev = ["pytest>=8.0.0", "black>=23.0.0"]
test = ["pytest-cov>=4.1.0"]
lint = ["ruff>=0.1.0", "mypy>=1.7.0"]

Step 2: Add Dependencies

Add to main project:

uv add requests httpx
uv add "fastapi>=0.104.0"
uv add "django>=4.2,<5.0"

Add to specific group:

uv add --dev pytest                    # Add to 'dev' group
uv add --group test pytest-cov        # Add to 'test' group
uv add --group lint ruff mypy         # Add to 'lint' group

Add with extras:

uv add "pandas[excel,plot]"
uv add --dev "pytest[cov]"

Step 3: Use Version Constraints

Common patterns (semantic versioning):

uv add "requests"                   # Latest
uv add "requests>=2.31.0"          # Minimum version
uv add "requests>=2.31.0,<3.0.0"   # Range (major bump)
uv add "requests~=2.31.0"          # Compatible release (~= 2.31.x)
uv add "requests==2.31.0"          # Exact version (production)

Recommended approach:

  • Development: >= (flexible, want latest)
  • Production: >=X,<Y (range, tested with that version)
  • Stable packages: ~= (compatible releases)

Step 4: Remove and Update Dependencies

Remove a package:

uv remove requests
uv remove pytest black              # Remove multiple

Update to specific version:

uv add "requests@2.32.0"

Update all dependencies:

uv sync --upgrade                   # Update and sync
uv lock --upgrade                   # Just update lock file

Step 5: Organize with Dependency Groups

Define logical groupings in pyproject.toml:

[dependency-groups]
dev = [
    "pytest>=8.0.0",
    "pytest-cov>=4.1.0",
    "black>=23.0.0",
]
lint = [
    "ruff>=0.1.0",
    "mypy>=1.7.0",
    "pylint>=3.0.0",
]
docs = [
    "mkdocs>=1.5.0",
    "mkdocs-material>=9.0.0",
]

Install specific groups:

uv sync --group dev --group lint    # Install groups
uv sync --all-groups                # Install everything
uv sync --no-dev                    # Only main deps (production)

Step 6: Understand Lock Files

Lock file (uv.lock):

  • Records exact versions of all dependencies
  • Ensures reproducible installs across machines
  • Should be committed to version control
  • Automatically updated when you change pyproject.toml

Workflow:

# After changing pyproject.toml
uv sync              # Installs from lock or creates new lock

# To explicitly update lock file
uv lock --upgrade    # Update all to latest compatible

# In CI/CD (use frozen to prevent surprises)
uv sync --frozen     # Fails if lock is out of sync

Step 7: Handle Dependency Conflicts

Problem: Two packages need incompatible versions of same library

Solution 1: Check if newer versions are compatible

uv add "package-a"
uv add "package-b"   # Might fail with version conflict

# Try adding with different constraints
uv add "package-a>=1.0,<2.0"
uv add "package-b>=2.0,<3.0"

Solution 2: Use separate dependency groups

[dependency-groups]
ml-cpu = ["torch-cpu>=2.0"]
ml-gpu = ["torch-gpu>=2.0"]
# Install one group at a time
uv sync --group ml-cpu

Solution 3: Investigate and pick winning version

# See what's needed
uv add --dry-run "package-a" "package-b"

# One might need updating
uv add "package-a>=2.0"
uv add "package-b>=3.0"

Examples

Example 1: Web API Project Setup

# Initialize and add web dependencies
uv init my-api
cd my-api
uv add fastapi uvicorn sqlalchemy pydantic

# Add development tools
uv add --group dev pytest pytest-asyncio
uv add --group lint ruff mypy black

# Verify setup
uv tree

Resulting pyproject.toml:

[project]
name = "my-api"
version = "0.1.0"
dependencies = [
    "fastapi>=0.104.0",
    "uvicorn>=0.24.0",
    "sqlalchemy>=2.0.0",
    "pydantic>=2.5.0",
]

[dependency-groups]
dev = ["pytest>=8.0.0", "pytest-asyncio>=0.21.0"]
lint = ["ruff>=0.1.0", "mypy>=1.7.0", "black>=23.0.0"]

Example 2: Library with Optional Features

# Create library with core deps
uv init my-library
uv add "click>=8.1.0"

# Add optional features as extras
uv add --group excel "openpyxl>=3.0.0"
uv add --group database "sqlalchemy>=2.0.0"
uv add --group async "aiohttp>=3.8.0"

# Setup development tools
uv add --dev pytest

Example 3: Resolving Version Conflicts

# Trying to add packages with conflicting requirements
uv add package-a                    # Works fine
uv add package-b                    # Fails - needs different version of shared lib

# View what's going on
uv add --dry-run package-b

# Try different constraints
uv add "package-a>=1.0,<1.5"
uv add "package-b>=2.0,<2.5"

# Check if it works
uv tree

Example 4: Data Science Project

# Create project
uv init data-pipeline
cd data-pipeline

# Data science core
uv add pandas numpy scikit-learn

# Analysis tools
uv add jupyter matplotlib seaborn plotly

# Development
uv add --group dev pytest pytest-cov

# Final tree
uv tree

Example 5: Update Strategy for Production

# Initial setup with compatible ranges
uv add "requests>=2.31.0,<3.0.0"
uv add "fastapi>=0.104.0,<1.0.0"

# After testing on latest patch
uv add "requests@2.31.3"
uv add "fastapi@0.104.1"

# Lock file is frozen for production
git add uv.lock
git commit -m "Pin exact versions for production"

# CI/CD uses frozen lock
uv sync --frozen

Example 6: Monorepo with Path Dependencies

# Main project
uv init main-app
cd main-app

# Add local packages (editable)
uv add --editable ../shared-lib
uv add --editable ../utils-lib

# Now imports work from both packages

Requirements

  • uv installed (install: curl -LsSf https://astral.sh/uv/install.sh | sh)
  • Understanding of PEP 508 version specifiers (recommended)
  • Project with pyproject.toml (created by uv init)
  • Python 3.8+ available

See Also

平台分布

Codex

38.51%
按下载量换算25

Claude

27.84%
按下载量换算18

Cursor

20.24%
按下载量换算13

Gemini CLI

9.99%
按下载量换算7

安全审计

Gen Agent Trust Hub

通过

Socket

未通过

Snyk

可疑

权限和风险

需要联网

该 Skill 可能需要联网访问来源站点、仓库或外部 API;具体网络访问范围需要结合源码和 README 复核。

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。

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