AI coding agents generate decent code. But decent ≠ production-ready.
They miss the stuff experienced engineers know instinctively — accessibility standards, proper auth flows, database reliability patterns, API design conventions. The gap between "it works" and "it's production-grade" is real.
The Idea
What if we could give AI agents that missing knowledge as loadable skill modules?
That's what TechSkills does — an open-source library of SKILL.md files containing structured workflows, design checklists, and battle-tested patterns that any AI agent can consume.
How It Works
Skills use progressive loading to stay context-efficient:
- Metadata — ~100 words, always visible, triggers activation
- Core instructions — loaded on activation, kept lean (<500 lines)
- References — deep checklists and patterns, loaded only when needed
No context window waste. Agent loads what it needs, when it needs it.
Current Skills
- 🎨 frontend-engineer — responsive layouts, accessibility, design systems, React/Vue/Svelte
- ⚙️ backend-engineer — APIs, auth, databases, reliability, observability, security
What Makes It Different
- Agent-agnostic — works with any AI tool that reads markdown
- Framework-neutral — pseudocode patterns, not framework-specific recipes
- Eval-driven — every skill includes eval cases to verify it actually works
Early Stage, Looking for Contributors
This is Day 1. Two foundational skills. The vision is a community-curated library covering DevOps, system design, data engineering, mobile, and more.
If you've got domain expertise and want to turn it into a skill module others can use — contributions are very welcome.
⭐ GitHub | 📄 MIT Licensed
What skills would you want your AI agent to have? Drop ideas in the comments 👇
Top comments (1)
Will read all your ideas and try to implement it and also want your contribution to make it grow