@classcad/skill

An agent skill for the ClassCAD headless CAD engine — structured API references with verified annotations that help AI agents generate correct ClassCAD code.

Status: 0.0.x pre-release. Content is actively evolving; expect additions and corrections between versions.

What this is

ClassCAD is a headless, programmable parametric CAD engine driven entirely through a JSON/WebSocket API (254 methods across 7 domains: part, assembly, sketch, curve, solid, drawing2d, common). This package documents that API for LLM consumption:

• SKILL.md — entry point: domain index, all 254 APIs with one-line summaries, cross-cutting guides
• references/api/*.md — source API documentation per domain (signatures, parameter tables, return types)
• references/<domain>/*.md — per-API LLM docs: gotchas, dead ends, common errors, working examples
• references/SKETCHING.md — the constrained-sketching workflow guide; the data contract (DATA/STRUCTURE/GRAPHICS) ships with @classcad/script
• method-registry.json / bundle.json — build artifacts: the full v1 method registry (generated from engine JSDoc) and every doc bundled as JSON (browser-safe, no filesystem)

Every per-API doc is battle-tested: the documented behavior was observed by executing real API calls against a live ClassCAD server — including the failure modes, silent no-ops, and doc discrepancies that source documentation doesn't cover.

The discovery module — one source for every agent host

@classcad/skill/discovery is the single implementation of everything an agent host needs to serve this knowledge:

• searchMethods — ranked search over name + summary with CAD-synonym expansion (split→slice, hole→bore, round→fillet, …)
• describeMethod — one key, fuzzy: bare names resolve, ambiguity lists candidates, typos get suggestions; also serves whole documents (topic docs, domain overviews, recipes)
• methodIndex — the compact one-line-per-method index (~5k tokens) that hosts put into the system prompt / MCP initialize instructions so the model knows the full surface from turn one
• bulkDocs + DOCS_TOOL — the docs(keys[]) bulk tool itself: contract (name, LLM-facing description, key/size caps) AND implementation (# ═══ key ═══ sections, "not found" reporting, optional per-key resolver hook for host-specific key spaces)

The buerli in-app agent and the ClassCAD MCP server both register their discovery tools from this module — same code, same behavior, verbatim.

import { createDiscovery, DOCS_TOOL } from '@classcad/skill/discovery'
import registry from '@classcad/skill/method-registry.json' with { type: 'json' }
import bundle from '@classcad/skill/bundle.json' with { type: 'json' }

const discovery = createDiscovery({ registry, bundle })
const { text } = await discovery.bulkDocs(['DATA', 'v1.part.extrusion', 'v1.part.chamfer'])

Usage

As a Claude Code / agent skill — drop the package into your skills directory:

npm install @classcad/skill
mkdir -p .claude/skills
ln -s ../../node_modules/@classcad/skill .claude/skills/classcad

SKILL.md carries Agent Skills frontmatter (name: classcad), so any skill-aware agent picks it up from there.

With classcad-mcp — the ClassCAD MCP server resolves this package automatically (via CLASSCAD_SKILL_PATH or a sibling classcad-skill checkout) and composes these docs into its describe_method tool.

As plain context — load SKILL.md as the index and pull references/ files on demand. The per-API docs are self-contained.

Related

• classcad.ch/docs — official ClassCAD documentation
• classcad-mcp — MCP server for driving ClassCAD from agents
• buerli.io — CAD-as-a-service built on ClassCAD

License

MIT © AWV Informatik AG