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How I Built 25 Executable Skills for My AI Agent (and You Can Too)

A developer built 25 executable skills for AI coding agents, packaged into a single open-source repository compatible with Claude Code, Codex, Cursor, and Hermes Agent. The skills include debugging, planning, code review, browser automation, and a Router Learning System that auto-selects the best execution path. The project is MIT licensed and hosted on GitHub.

read1 min views1 publishedJun 30, 2026

After months of building agent skills for Claude Code, Codex, Cursor, and Hermes Agent, I noticed a problem: every agent needs the same foundational capabilities �” debugging, planning, code review, browser automation �” but you have to write them from scratch for each platform.

So I packaged 25 of the most useful skills into a single open-source repo, compatible across all major AI coding agents.

Fix brew Node dylib mismatch, memory analysis, iOS app build automation, self-regulation brake system, GitHub demo recording, install tools with verification, macOS backup, Reddit posting workflow, webhook subscriptions, AI news monitoring, and more.

Cua Driver install + config, a Router Learning System that auto-selects CLI/CDP/Desktop Automation, and a vision-based GUI debug loop.

GitHub OAuth via browser automation, Cua Driver browser control, social media content automation across 6+ platforms.

Cocos Creator debug workflows, WeChat DevTools fixes, UX feedback loop, merit shop system, TypeScript compile check.

The most interesting piece was a Router Learning System that:

def execute(task):
    for path in [CLI, CDP, DESKTOP, VISION]:
        if path.success_rate > 0.7:
            return path.run(task)
    return FALLBACK_STRATEGY
git clone https://github.com/chrislamlayer1-gif/hermes-core-skills
cd hermes-core-skills

All 25 skills are MIT licensed. Contributions welcome!

Built with Hermes Agent �” an open-source AI agent by Nous Research.

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