ai-agent-camp — Claude Skill by minicoohei

by minicoohei · Claude Skill · ★ 344

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About ai-agent-camp

English Español ai-agent-camp AI Agent Training for Non-Engineers - Complete Guide to Claude Code / Cursor / Codex ### ⚠️ Before you clone Official repository (maintained by the authors): - Running AI agents from this repo grants them shell, file-write, and external-API permissions on your machine. Forks and mirrors can silently alter lessons or skills. Before running any lesson, verify your clone: If the check reports a fork or missing files, review before proceeding. See . <!-- AGENT-META v1 schema: https://github.com/minicoohei/ai-agent-camp/blob/main/docs/release-process.md#agent-meta-v1 repo: minicoohei/ai-agent-camp primarybranch: main languages: [ja, en, es] defaultlanguage: ja latesttagapi: https://api.github.com/repos/minicoohei/ai-agent-camp/releases/latest releaseasse

ai-agentclaude-codecodexcurriculumcursoreducation

Quick Facts

Stars344
Forks11
LanguagePython
CategoryClaude Skill
Quality Score74.4531247811307/100
Open Issues11
Last Updated2026-06-22
Created2026-04-14
Platformsclaude-code, codex, python
Est. Tokens~22k

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Frequently Asked Questions

What is ai-agent-camp?

ai-agent-camp is AI Agent Camp — non-engineer-friendly AI agent training curriculum. Lessons, skills, commands, and hooks for Claude Code, Cursor, and Codex.. It is categorized as a Claude Skill with 344 GitHub stars.

What programming language is ai-agent-camp written in?

ai-agent-camp is primarily written in Python. It covers topics such as ai-agent, claude-code, codex.

How do I install or use ai-agent-camp?

You can find installation instructions and usage details in the ai-agent-camp GitHub repository at github.com/minicoohei/ai-agent-camp. The project has 344 stars and 11 forks, indicating an active community.

What are the best alternatives to ai-agent-camp?

The top alternatives to ai-agent-camp on Agent Skills Hub include Overture, deterministic-agent-control-protocol, claude-workflow-v2. Each offers a different approach to the same problem space — compare them side-by-side by stars, quality score, and community activity.

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