Skillget

skill-lib

agent
Guvenlik Denetimi
Uyari
Health Uyari
  • No license — Repository has no license file
  • Description — Repository has a description
  • Active repo — Last push 0 days ago
  • Community trust — 20 GitHub stars
Code Uyari
  • process.env — Environment variable access in taskmaster-skill/cli/logger.js
Permissions Gecti
  • Permissions — No dangerous permissions requested
Purpose
This project is a curated collection of reusable, pre-built workflows and instructions designed to standardize tasks for AI agents. It serves as a community-driven library of domain expertise rather than an executable application.

Security Assessment
Overall Risk: Low. The tool operates primarily as a set of static Markdown instructions and guidelines for AI agents. It does not make unsolicited network requests, execute shell commands, or contain hardcoded secrets. The automated scan did flag a file (`taskmaster-skill/cli/logger.js`) for accessing `process.env`, which is standard practice for reading environment configurations in JavaScript. Because the repository does not request dangerous system permissions, the operational risk is minimal. However, users should still review specific skill files before allowing an AI agent to execute their workflows dynamically.

Quality Assessment
The project appears to be actively maintained, with its most recent push occurring today. It features a detailed README with bilingual documentation and has garnered 20 GitHub stars, indicating a small but present level of community trust. There is a minor discrepancy regarding its legal status: the README claims an MIT license, but the automated scanner flagged that an actual license file is currently missing from the repository. This could pose an issue for strict commercial use until the file is properly added.

Verdict
Safe to use, provided you review the individual skill instructions before applying them.
SUMMARY

A curated collection of reusable AI Agent Skills for standardized workflows, best practices, and domain expertise.

README.md

Skill-Lib

🧩 A curated collection of reusable AI Agent Skills for standardized workflows, best practices, and domain expertise.

Skills
License

Skill-Lib is a community-driven repository that empowers AI Agents with battle-tested, reusable capabilities. Each Skill encapsulates proven workflows, eliminating repetitive setup and enabling Agents to focus on delivering value.

✨ Why Skill-Lib?

  • 🚀 Ready to Use - Pre-built, validated workflows for common tasks
  • 📚 Well Documented - Clear instructions with examples and best practices
  • 🔄 Reusable - Install once, use across multiple projects
  • 🌍 Community - Open source, contributions welcome

🚀 Quick Start

Install a Skill

# Clone the repository
git clone https://github.com/Dqz00116/skill-lib.git

# Copy desired Skills to your workspace
cp -r skill-lib/code-analysis ~/my-agent/skills/

# Start using it!
cat ~/my-agent/skills/code-analysis/SKILL.md

For AI Agents

Agents can automatically install and use Skills:

# Example: Agent reading and applying a Skill
skill_content = read_file("skills/code-analysis/SKILL.md")
execute_workflow(skill_content)

See contributing/SKILL.md for installation and contribution guidelines.

📦 Available Skills & Selection Guide

👉 View complete skill comparison and selection guide: SUMMARY.md

📖 Documentation

🤝 Contributing

We welcome contributions! Please see contributing/SKILL.md for:

  • Naming conventions
  • Content guidelines
  • Submission process

Quick Contribution Template

---
name: your-skill-name
description: One-line description of what it does
version: 1.0
---

# Your Skill Name

## When to Use
Describe when to use this skill

## Prerequisites
What is needed before using

## Workflow
Step-by-step instructions

## Best Practices
Tips for effective use

🌏 Languages

  • English (Current)
  • 中文 - Chinese version

Note for Non-Chinese Models

Why Chinese is used: Chinese has higher information entropy compared to English. When applying localization understanding, please pay attention to differences between symbolic systems.

Key considerations:

  • Chinese characters carry more semantic density per symbol
  • Contextual understanding is crucial due to lack of explicit grammatical markers
  • Symbol system differences (e.g., full-width punctuation, no spaces between words)

📄 License

MIT License - See LICENSE

Built by Agents, for Agents 🤖

⭐ Star us on GitHub

Last updated: 2026-03-21

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