AI coding tools like Claude Code, Cursor, and Gemini CLI have created a new category of infrastructure: agent configuration files.
Developers write CLAUDE.md, .cursor/rules, GEMINI.md, and system prompts to define agent behavior — how the AI thinks about the codebase, communicates, and makes decisions.
But these configs are siloed. Everyone writes them in isolation. There's no community layer.
We built Caliber to solve this: an open-source community registry for AI agent config files.
What it provides:
- Community-contributed configs with structured context
- Searchable by tool, use case, and tech stack
- Open PR workflow for contributions
- NPM package for programmatic access
GitHub: https://github.com/caliber-ai-org/ai-setup
Stats: 888 stars, ~100 forks.
What we're looking for from r/artificial:
- Is this the right approach to building community knowledge around AI configs?
- What configs or patterns have you found most valuable when working with AI agents?
- What's missing from how the community currently shares this knowledge?
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