lamina
Product design skill for developers who build with AI coding agents. Use when you need to know what to build before prompting your agent — domain model, workflows, edge cases, product states, and UX gaps handled upfront. Works alongside Cursor, Claude Code, Codex, Gemini, Pi. Any stack, any UI library. Do NOT use for visual styling, pixel layouts, or writing app source.
Profile →npx skills add aryaniyaps/lamina --skill templates --agent claude-code
Same command for any agent — swap --agent for codex, cursor, copilot.
Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.
# Lamina — For Developers Who Build with AI **Design how it works.** Lamina runs alongside your AI coding agent — Cursor, Claude Code, Codex, Gemini, Pi. It helps you know what to build before you prompt: edge cases, UX gaps, product states, and invariants in a transactional product graph your agent implements. Verified with isolated Persona Missions after you ship. Does not write your app source.
What does the lamina skill do?
Product design skill for developers who build with AI coding agents. Use when you need to know what to build before prompting your agent — domain model, workflows, edge cases, product states, and UX gaps handled upfront. Works alongside Cursor, Claude Code, Codex, Gemini, Pi. Any stack, any UI library. Do NOT use for visual styling, pixel layouts, or writing app source.
How do I install it?
Run `npx skills add aryaniyaps/lamina --skill templates --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.
Where does this skill come from?
From aryaniyaps/lamina, a repository with 111 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.
Is a popular skill a good skill?
Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.