Co-Pilot
Updated 24 days ago

experiments

Kkehwar
0.0k
kehwar/experiments
78
Agent Score

💡 Summary

This repository provides tools and guidelines for creating and managing Agent Skills.

🎯 Target Audience

AI developersGame developersData analystsEducators in AIHobbyists interested in Pokemon

🤖 AI Roast:Powerful, but the setup might scare off the impatient.

Security AnalysisMedium Risk

Risk: Medium. Review: outbound network access (SSRF, data egress); filesystem read/write scope and path traversal. Run with least privilege and audit before enabling in production.

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

5-Dim Analysis
Clarity8/10
Novelty7/10
Utility9/10
Completeness7/10
Maintainability8/10
Pros & Cons

Pros

  • Comprehensive guides for skill creation
  • Organized data fetching for Pokemon
  • Modular and reusable skills
  • Community-driven standards

Cons

  • Limited examples for advanced skills
  • Dependency on external APIs
  • Documentation may require updates
  • Not beginner-friendly for all users

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Disclaimer: This content is sourced from GitHub open source projects for display and rating purposes only.

Copyright belongs to the original author kehwar.