lyse

# Lyse > Design systems drift. Lyse measures it. The local, deterministic health score for your design system — audit, explain, and hand the fixes to your coding agent, locally or in CI. [](https://github.com/lyse-labs/lyse/actions/workflows/ci.yml) [](https://www.npmjs.com/package/@lyse-labs/lyse) [](https://www.npmjs.com/package/@lyse-labs/lyse) [](./LICENSE) ## Quickstart AI coding agents ship UI fast — and hardcode `#3b82f6` where `color.brand.primary` exists, reinvent `<Button>`, and skip stories. Lyse audits the drift they (and humans) introduce, scores it 0–100, and hands the fixes back to the same agent. ```bash npx -y @lyse-labs/lyse@latest ``` That's it — no config, no prompts, your Health Score in seconds. ## Optional: calibrate `lyse init` detects your framework, writes `.lyse.yaml`, and optionally wires the MCP server for your AI agent. ```bash npx -y @lyse-labs/lyse@latest init ``` ## Commands ```bash lyse audit # rerun the audit (text, JSON, or SARIF) lyse handoff # audit, then hand the findings to your coding agent to fix (Claude Code / Cursor / Codex) lyse init --scaffold # generate missing AI-readiness files (llms.txt, AGENTS.md) lyse init --migrate-tokens # convert legacy {value,type} token JSON to DTCG ({$value,$type}) lyse explain X # rationale + examples for a rule lyse mcp setup # wire MCP into Cursor / Claude Code / Codex lyse add ci-gate # install the score-regression CI gate (.github/workflows/lyse.yml) lyse share # copy a Markdown summary to your clipboard ``` > **Trust boundary.** By default, `lyse handoff` launches your coding agent with its permission prompts bypassed so it can apply fixes unattended — only run it on repositories you trust. It confirms before spawning (`Continue? [y/N]`, skipped under `--yes` or non-interactively); pass `--review` to keep the agent's own per-action permission prompts instead. ## What it audits A Health Score (0–100) across **6 axes** — tokens, a11y, components, stories, ai-surface, ai-governance — from deterministic static rules. Each axis is an opportunity-weighted clean-adoption ratio (`scoring-v3`); axes need 30+ opportunities to count. CMMI-style maturity tier (Foundational → Autonomous) mapped from the score. No LLM, no network, fully local by default. The previous severity-weighted formula stays reachable for one minor release via `--score-model v2` — scores are not comparable across the two. Full formula and per-rule docs in [`docs/`](./docs/). The optional **render layer** (`lyse audit --render`) runs additional checks against a pre-built Storybook (`storybook-static/` or a URL): `tokens/rendered-token-fidelity` (CSS custom property drift) and `a11y/runtime-axe` (axe-core a11y violations). Both are experimental and do not affect the Health Score. `lyse explain --score` also reports an **AI-Governance Maturity Level** (L0–L5, by presence of AI affordances — marker components, AI tokens, interaction patterns, governance docs). Deterministic by default; an optional LLM tier reads semantic affordances for the harder cases. ## Privacy `lyse audit` is **static-only by default**: nothing leaves your machine. The optional LLM precision filter is **opt-in** (`--llm`, `LYSE_LLM=1`, or explicit `llm.provider` config) and BYOK — having the `claude` CLI installed does not enable it silently, and the default audit never prompts for it. Telemetry is opt-in only (a one-time prompt shown after your first report, default declines). See [PRIVACY.md](./PRIVACY.md). ## More - [`CHANGELOG.md`](./CHANGELOG.md) — release history - [`docs/`](./docs/) — full documentation, rule pages, architecture - [`CONTRIBUTING.md`](./CONTRIBUTING.md) — how to add a rule or fix a bug - [`LICENSE`](./LICENSE) / [`COMMERCIAL.md`](./COMMERCIAL.md) — dual AGPLv3 / commercial - [`SECURITY.md`](./SECURITY.md) — vulnerability reports --- © 2026 Lyse Labs.