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Agent Skill · 研究检索

dependency-manager(依赖管理器)

dependency-manager 用于查找、检索和筛选相关信息,适合在 Codex、Claude、Cursor、Gemini CLI 中需要根据关键词、任务场景或来源线索快速定位候选结果时使用。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。

dependency-manager 是研究检索类 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,按安装量在研究检索类的 73,675 个 Skill 里排第 73,543。

总安装 1周安装 8GitHub Stars 27下载 65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:dependency-manager(依赖管理器)
来源仓库:https://github.com/armanzeroeight/fastagent-plugins
仓库路径:skills/dependency-manager
安装命令:
npx skills add https://github.com/armanzeroeight/fastagent-plugins --skill dependency-manager
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/armanzeroeight/fastagent-plugins --skill dependency-manager

这个 Skill 是做什么的

研究检索类 Skill 主要解决「找资料、核对事实、把来源整理清楚」的问题,通常会让助手先检索再总结。

用于 Python 项目依赖管理,支持 UV、pip-tools 与 requirements.txt 三种方案。推荐新项目使用 UV 以获得更快解析速度。适用于依赖锁定与跨环境一致性维护场景。安装方式:通过 npx skills add 命令从指定 GitHub 仓库添加。

使用前应评估团队现有工具链偏好,避免引入学习成本。

来源仓库内路径:skills/dependency-manager

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/armanzeroeight/fastagent-plugins --skill depen…;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

dependency-manager 怎么安装?

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

dependency-manager 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。

dependency-manager 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。

dependency-manager 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。

dependency-manager 用的人多吗?

公开数据是累计安装 1 次,近一周安装 8 次,下载 65 次,GitHub 27 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。

dependency-manager 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。
  • 需要处理研究检索类任务、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。

研究检索类 Skill 对比

6 个同类
Skill总安装GitHub 星权限许可证扫描
find-skills

寻找技能 · Codex、Claude

31,199,81316,486操作浏览器MIT有提醒
self-improving-agent

自我改进 Agent · OpenClaw

16,464,0023,396接触敏感数据MIT-0通过
soultrace

灵魂追踪 · Codex、Claude

7,588,94412需要联网未明确有提醒
self-improving

自我完善 · OpenClaw

6,829,2841,046需要联网MIT-0通过
microsoft-foundry

微软代工厂 · Codex、Claude

6,614,144764调用外部服务未明确有提醒
dependency-manager

依赖管理器 · 本页

127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

Dependency Manager

Manage Python project dependencies with UV, pip-tools, or requirements.txt.

Quick Start

Choose UV for new projects (fast, modern), pip-tools for existing pip workflows, or requirements.txt for simple projects.

Instructions

Choosing a Tool

UV - Fast, modern Python package manager (recommended):

  • Extremely fast dependency resolution (10-100x faster than pip)
  • Automatic virtual environment management
  • Drop-in replacement for pip and pip-tools
  • Lock file support with uv.lock
  • Best for: All projects, especially new ones

pip-tools - Lightweight, pip-compatible workflow:

  • Generates lock files from requirements.in
  • Works with existing pip workflows
  • Minimal changes to project structure
  • Best for: Existing projects, CI/CD with pip, gradual adoption

requirements.txt - Simple, universal:

  • Direct pip install
  • No additional tools
  • No lock file (unless manually maintained)
  • Best for: Simple scripts, minimal dependencies, quick prototypes

UV Setup (Recommended)

Install UV:

curl -LsSf https://astral.sh/uv/install.sh | sh
# Or with pip
pip install uv

Initialize new project:

uv init my-project
cd my-project

Add dependencies:

# Runtime dependency
uv add requests

# Development dependency
uv add --dev pytest

# With version constraint
uv add "requests>=2.28.0,<3.0.0"

Install dependencies:

uv sync

Update dependencies:

# Update all
uv lock --upgrade

# Update specific package
uv lock --upgrade-package requests

Remove dependencies:

uv remove requests

Show dependency tree:

uv tree

Export to requirements.txt:

uv pip compile pyproject.toml -o requirements.txt

Run commands in virtual environment:

uv run python script.py
uv run pytest

pip-tools Setup

Install pip-tools:

pip install pip-tools

Create requirements.in:

# requirements.in
requests>=2.28.0
flask>=2.0.0

Create requirements-dev.in:

# requirements-dev.in
-c requirements.txt  # Constrain to production versions
pytest>=7.0.0
black>=23.0.0
mypy>=1.0.0

Compile lock files:

# Compile production dependencies
pip-compile requirements.in

# Compile dev dependencies
pip-compile requirements-dev.in

This generates requirements.txt and requirements-dev.txt with pinned versions.

Install dependencies:

pip-sync requirements.txt requirements-dev.txt

Update dependencies:

# Update all
pip-compile --upgrade requirements.in

# Update specific package
pip-compile --upgrade-package requests requirements.in

Add new dependency:

  1. Add to requirements.in
  2. Run pip-compile requirements.in
  3. Run pip-sync requirements.txt

requirements.txt Workflow

Create requirements.txt:

pip freeze > requirements.txt

Install dependencies:

pip install -r requirements.txt

Separate dev dependencies:

Create requirements-dev.txt:

-r requirements.txt
pytest>=7.0.0
black>=23.0.0

Install with:

pip install -r requirements-dev.txt

Version Constraints

UV/PEP 621 syntax (pyproject.toml):

[project]
dependencies = [
    "requests>=2.28.0,<3.0.0",  # Range
    "flask~=2.0.0",              # Compatible release
    "django>=3.2,<4.0",          # Range
    "numpy==1.24.0",             # Exact version
]

pip syntax (requirements.in or requirements.txt):

requests>=2.28.0,<3.0.0
flask~=2.0.0
django>=3.2,<4.0
numpy==1.24.0
pandas

Constraint operators:

  • ==: Exact version
  • >=, <=: Minimum/maximum version
  • ~=: Compatible release (patch updates)
  • ,: Combine constraints (AND)

Dependency Groups

UV/PEP 621 groups:

[project.optional-dependencies]
dev = ["pytest>=7.0.0", "black>=23.0.0"]
docs = ["sphinx>=5.0.0"]
test = ["coverage>=7.0.0"]

Install specific groups:

uv sync --extra dev
uv sync --extra docs
uv sync --all-extras

pip-tools approach:

Create separate .in files:

  • requirements.in - Production
  • requirements-dev.in - Development
  • requirements-test.in - Testing
  • requirements-docs.in - Documentation

Resolving Conflicts

With UV:

  1. Check conflict: uv add package-name # UV will show conflict if it exists
  2. Update constraints in pyproject.toml: [project] dependencies = ["package-a>=2.0.0", # Relax constraint "package-b>=3.0.0",]
  3. Force resolution: uv lock uv sync

With pip-tools:

  1. Check conflict: pip-compile requirements.in # Will show resolution errors
  2. Adjust constraints in requirements.in: package-a>=2.0.0 # Relax constraint package-b>=3.0.0
  3. Recompile: pip-compile requirements.in

Common conflict patterns:

  • Transitive dependency conflict: Two packages require incompatible versions of a third package

- Solution: Update one or both packages, or relax constraints

  • Python version conflict: Package requires newer Python than project supports

- Solution: Upgrade Python version or find alternative package

  • Platform-specific conflict: Package not available on current platform

- Solution: Use platform markers or optional dependencies

Platform-Specific Dependencies

UV/PEP 621:

[project]
dependencies = [
    "pywin32>=305; sys_platform == 'win32'",
    "python-daemon>=2.3; sys_platform == 'linux'",
]

pip:

pywin32>=305; sys_platform == 'win32'
python-daemon>=2.3; sys_platform == 'linux'

Optional Dependencies

UV/PEP 621:

[project.optional-dependencies]
aws = ["boto3>=1.26.0"]
all = ["boto3>=1.26.0"]  # Include all optional deps

Install with:

uv sync --extra aws
uv pip install package-name[aws]

Virtual Environments

UV (automatic):

# UV creates and manages venv automatically
uv sync
uv run python script.py
source .venv/bin/activate  # Manual activation if needed

pip-tools (manual):

# Create venv
python -m venv venv

# Activate
source venv/bin/activate  # Linux/Mac
venv\Scripts\activate     # Windows

# Install
pip-sync requirements.txt

requirements.txt (manual):

python -m venv venv
source venv/bin/activate
pip install -r requirements.txt

CI/CD Integration

UV in CI (recommended):

# .github/workflows/test.yml
- name: Install UV
  run: curl -LsSf https://astral.sh/uv/install.sh | sh

- name: Install dependencies
  run: uv sync

- name: Run tests
  run: uv run pytest

pip-tools in CI:

- name: Install dependencies
  run: |
    pip install pip-tools
    pip-sync requirements.txt requirements-dev.txt

- name: Run tests
  run: pytest

requirements.txt in CI:

- name: Install dependencies
  run: pip install -r requirements.txt

- name: Run tests
  run: pytest

Migration Strategies

From requirements.txt to UV:

  1. Initialize UV project: uv init --no-readme
  2. Import dependencies: # Add each dependency from requirements.txt cat requirements.txt | grep -v "^#" | xargs -I {} uv add {}
  3. Separate dev dependencies: uv add --dev pytest black mypy
  4. Test: uv sync uv run pytest

From requirements.txt to pip-tools:

  1. Rename requirements.txt: mv requirements.txt requirements.in
  2. Compile lock file: pip-compile requirements.in
  3. Create dev requirements: echo "-c requirements.txt" > requirements-dev.in echo "pytest" >> requirements-dev.in pip-compile requirements-dev.in
  4. Test: pip-sync requirements.txt requirements-dev.txt

From pip-tools to UV:

  1. Create pyproject.toml: uv init --no-readme
  2. Import from requirements.in: cat requirements.in | grep -v "^#" | grep -v "^-" | xargs -I {} uv add {}
  3. Test: uv sync

Common Patterns

Monorepo with Shared Dependencies

UV workspace:

# Root pyproject.toml
[tool.uv.workspace]
members = ["packages/*"]

# packages/package1/pyproject.toml
[project]
name = "package1"
dependencies = ["requests>=2.28.0"]

# packages/package2/pyproject.toml
[project]
name = "package2"
dependencies = ["requests>=2.28.0"]

pip-tools approach:

# shared-requirements.in
requests>=2.28.0

# package1/requirements.in
-c ../shared-requirements.txt
flask>=2.0.0

# package2/requirements.in
-c ../shared-requirements.txt
django>=4.0.0

Lock File Best Practices

Commit lock files:

  • uv.lock - Always commit
  • requirements.txt (from pip-compile) - Always commit
  • requirements.txt (from pip freeze) - Consider committing

Update regularly:

# UV
uv lock --upgrade

# pip-tools
pip-compile --upgrade requirements.in

Verify after updates:

# Run tests
uv run pytest

# Check for security issues
pip-audit

Troubleshooting

UV lock takes too long:

  • UV is typically very fast; if slow, check for network issues
  • Use uv lock --offline to use cached packages
  • Check for circular dependencies

pip-compile fails with conflict:

  • Relax version constraints in requirements.in
  • Use pip-compile --resolver=backtracking for better resolution
  • Check for incompatible transitive dependencies

Dependencies not found:

  • Verify package name (check PyPI)
  • Check Python version compatibility
  • Ensure correct index URL (for private packages)
  • With UV: uv pip install --index-url https://custom-index.com package

Virtual environment issues:

  • Delete and recreate: rm -rf.venv && uv sync
  • Check Python version matches project requirements
  • UV automatically manages virtual environments

Outdated dependencies:

  • Check with: uv tree --outdated or pip list --outdated
  • Update carefully, test after each major update
  • Use uv lock --upgrade --dry-run to preview changes

平台分布

Codex

36.23%
按下载量换算24

Claude

31.69%
按下载量换算21

Cursor

19.06%
按下载量换算12

Gemini CLI

9.38%
按下载量换算6

安全审计

Gen Agent Trust Hub

未通过

Socket

通过

Snyk

未通过

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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