@nifrajs/skills

Portable agent skills for Nifra - one SKILL.md bundle, published to every agent surface that reads a skills/ directory.

A skill is loaded on demand: the agent sees only each skill's name and description until it decides one applies, then reads the body. That keeps Nifra's conventions out of the context window until they matter.

skills/
  nifra/SKILL.md         entry point - MCP-first rule, the core loop, the non-negotiables
  nifra-api/SKILL.md     typed routes, schemas, middleware, WebSockets, the never-throwing client
  nifra-web/SKILL.md     file routing, loaders/actions, SSR, islands, the client/server boundary
  nifra-verify/SKILL.md  check, assure, capabilities, manifest diff, the verification ladder

Install

Pi

pi install npm:@nifrajs/skills

Claude Code

/plugin marketplace add nifrajs/nifra
/plugin install nifra@nifra

The plugin registers the Nifra MCP server as well as the skills, so a fresh install has the live tools the skills tell it to prefer. Its launch spec is deliberately unpinned - a plugin is installed once and opened against many projects, so the CLI resolves per project and the server reports version skew itself rather than freezing one version across all of them.

Anything that reads a skills directory (Cursor, .agents/skills, a project .pi/skills)

bun add -d @nifrajs/skills
cp -R node_modules/@nifrajs/skills/skills/* .agents/skills/

These skills are deliberately thin

They teach shape and rules, not signatures. Signatures come from the MCP server, which is typechecked against the version installed in the project being edited:

bunx @nifrajs/cli init-agents      # register the MCP server in an existing app

The Claude Code plugin brings its own copy of that server, so init-agents is for the other surfaces - and for committing a version-pinned .mcp.json that every contributor on the project shares.

Not in a Nifra project? The docs tools are hosted at https://mcp.nifra.dev.

That split is the anti-drift design: a skill that restated the API would rot on the next release, while a skill that says "ask nifra_types" stays correct. Keep it that way when editing these files - if you find yourself pasting a signature in, reach for a tool reference instead.

For AI agents

Start with LLM.md - this package's contract card, one cheap read instead of the whole corpus. For the wider framework: the repo's AGENTS.md is the copy-paste quick reference, and llms-full.txt is the full machine-readable corpus. Run nifra check as the done-gate, or nifra mcp to give the agent live project tools.

MIT licensed.