Co-Pilot / 辅助式
更新于 24 days ago

experiments

Kkehwar
0.0k
kehwar/experiments
78
Agent 评分

💡 摘要

该存储库提供创建和管理代理技能的工具和指南。

🎯 适合人群

人工智能开发者游戏开发者数据分析师人工智能教育工作者对宝可梦感兴趣的爱好者

🤖 AI 吐槽:看起来很能打,但别让配置把人劝退。

安全分析中风险

风险:Medium。建议检查:是否发起外网请求(SSRF/数据外发);文件读写范围与路径穿越风险。以最小权限运行,并在生产环境启用前审计代码与依赖。

experiments

This repository contains experimental projects and Agent Skills.

Agent Skills

skill-writer

A comprehensive guide for creating, structuring, and documenting Agent Skills following the official Agent Skills specification.

What it does:

  • Provides step-by-step instructions for creating Agent Skills
  • Explains the Agent Skills format and structure
  • Includes templates and examples
  • Offers best practices and common patterns

When to use it:

  • Creating a new Agent Skill from scratch
  • Understanding the Agent Skills format
  • Improving existing skill documentation
  • Learning about the Agent Skills ecosystem

Quick start: See skill-writer/SKILL.md for the complete guide and skill-writer/references/template.md for a ready-to-use template.

pokemon-data-fetcher

A Python script that fetches Pokemon data from the PokeAPI and organizes it by generation in JSON format.

What it does:

  • Fetches all Pokemon species from the PokeAPI
  • Organizes Pokemon by their generation (I through IX)
  • Sorts Pokemon alphabetically within each generation
  • Saves results to JSON files for easy parsing

When to use it:

  • Need Pokemon data for analysis or applications
  • Building a Pokedex or Pokemon reference tool
  • Creating Pokemon-related projects or games
  • Learning to work with RESTful APIs

Quick start: See pokemon-data-fetcher/SKILL.md for complete documentation and usage instructions.

About Agent Skills

Agent Skills are an open format for giving AI agents new capabilities and expertise. They are:

  • Portable: Work across different AI platforms (Claude, GPT, Copilot, etc.)
  • Simple: Filesystem-based with markdown files
  • Modular: Each skill is self-contained and reusable
  • Open: No vendor lock-in, community-driven standard

Learn more at agentskills.io

五维分析
清晰度8/10
创新性7/10
实用性9/10
完整性7/10
可维护性8/10
优缺点分析

优点

  • 全面的技能创建指南
  • 有组织的宝可梦数据获取
  • 模块化和可重用的技能
  • 社区驱动的标准

缺点

  • 高级技能的示例有限
  • 依赖外部API
  • 文档可能需要更新
  • 对所有用户来说不够友好

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免责声明:本内容来源于 GitHub 开源项目,仅供展示和评分分析使用。

版权归原作者所有 kehwar.