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

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.

What's inside

DevOps & macOS (14 skills)

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.

Desktop Automation (3 skills)

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

Web & Browser (3 skills)

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

WeChat Mini Program (5 skills)

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

The Router Learning System

The most interesting piece was a Router Learning System that:

1. Auto-selects the best execution path (CLI �†’ CDP �†’ Desktop Automation �†’ Vision AI)
2. Learns from past executions �” skips paths that consistently fail
3. Self-optimizes after 5+ runs

# Simplified routing logic
def execute(task):
    for path in [CLI, CDP, DESKTOP, VISION]:
        if path.success_rate > 0.7:
            return path.run(task)
    return FALLBACK_STRATEGY

How to use

git clone https://github.com/chrislamlayer1-gif/hermes-core-skills
cd hermes-core-skills
# Load into your agent (Claude Code, Codex, Cursor, or Hermes)

All 25 skills are MIT licensed. Contributions welcome!

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