Built by Manav Arya Singh (@Manavarya09)
Sponsors
Atlas Cloud — powers OpenAI-compatible --smart classification. For AI coding workflows, try the Atlas Cloud coding plan.
Bloome — deploys your AI clone to handle every audience conversation, running in the cloud, 24/7.
Try designlang on Bloome.
designlang points a headless browser at any URL and reads the design system off the live DOM. One command emits 17+ files — DTCG tokens, Tailwind config, shadcn theme, Figma variables, motion tokens, typed component anatomy, brand voice, page-intent labels, and a paste-ready prompt pack for v0 / Lovable / Cursor / Claude Artifacts.
It also goes where extractors don't: layout patterns, responsive behavior across 4 breakpoints, hover / focus / active states, WCAG contrast scoring, multi-page consistency, drift checks against a live source-of-truth, visual-diffs, and a shareable graded report card.
Quick start
npx designlang https://stripe.com # extract everything
npx designlang dna stripe.com # place it in the measured design space: neighbours + percentiles ← v13.1
npx designlang site stripe.com # whole-site: one canonical system + consistency grade ← v12.23
npx designlang fidelity stripe.com --clone localhost:3000 # score a clone vs the original (visual + motion) ← v12.24
npx designlang gallery # static shareable gallery of measured clones ← v12.24
npx designlang studio # live token editor: edit, preview, export, share ← v12.19
npx designlang verify stripe.com # fidelity score: rebuild from tokens vs live ← v12.18
npx designlang pair stripe.com linear.app # fuse two designs (visuals A × voice B) ← v12.8
npx designlang brand stripe.com # full brand-guidelines book (13 chapters) ← v12.7
npx designlang theme-swap stripe.com --primary "#ff4800" # recolour around your brand ← v12.6
npx designlang pack stripe.com # one polished design-system directory ← v12.4
npx designlang remix stripe.com --as cyberpunk # restyle in another vocabulary ← v12.3
npx designlang remix stripe.com --all # emit all 6 vocabs at once ← v12.3
npx designlang grade https://stripe.com --badge # report card + SVG badge ← v12.2
npx designlang battle stripe.com vercel.com # head-to-head graded fight ← v12.2
npx designlang clone https://stripe.com # working Next.js starter
npx designlang --full https://stripe.com # screenshots + responsive + interactions
Drop a live design-score badge in any README:

Watch it read — live Extraction Theatre (v13)
Don't take the output on faith — watch it happen. On designlang.app/watch you paste a URL and a real headless Chromium opens the page and reads its entire design system in real time: a split stage with the live browser on the left and the design system — palette, type, spacing, motion — assembling itself on the right as each token lifts off the page.
It's driven by the actual extraction (the browser's CDP screencast streamed frame-by-frame alongside the real token events), recorded so a shared link replays the exact run. No install, no account. Every gallery card can be watched the same way, and the gallery now spans 37 real-graded design systems.
Whole-site design system (site)
Most extractors read a single URL. designlang site crawls a site's canonical
pages (home, pricing, docs, blog, about, product…) and synthesizes one
de-duplicated system. Every token is elected by coverage — the share of pages
that use it — so what's genuinely site-wide is separated from one-off,
page-local choices. Near-identical colours are merged in OKLab. It's fully
deterministic and free; no API key.
npx designlang site stripe.com --max-pages 8
You get, alongside the standard pack emitted from the canonical system:
| File | What it is |
|---|---|
*-site-system.json |
canonical unified tokens + coverage + drift |
*-site-coverage.md |
every token tagged 🟢 site-wide / 🟡 section / 🔴 page-local, with the pages using it |
*-site-consistency.md |
a 0–100 consistency grade, per-category breakdown, and the off-system outliers to consolidate |
Measured clone fidelity (fidelity + gallery)
Cloning tools all claim "pixel-perfect" — none of them measure it. designlang fidelity does. Point it at the original and your clone (often a local dev
server) and it returns one honest number, both halves of the clone:
- Visual — full-page screenshots of each, pixel-diffed.
- Motion —
extractMotion()on both, compared across feel, durations, easings, springs, keyframe kinds, scroll-linked motion, and choreography/ stagger. (Most clones reproduce static pixels and drop the motion entirely; this is where they lose.)
The two blend into a 0–100 score + letter grade, and — the part competitors don't ship — a ranked correction plan: the exact next edits that will raise the score, hardest-hitting first. Measure → fix → re-run until it converges.
npx designlang fidelity https://stripe.com --clone http://localhost:3000
npx designlang fidelity https://stripe.com --clone http://localhost:3000 --min 90 # CI gate
Generating the clone with designlang clone? Add --fidelity and it grades the
clone's token basis against the live site the moment it's built — writing
FIDELITY.md + a correction plan straight into the project, no separate step:
npx designlang clone https://stripe.com --fidelity
You get fidelity.md (score + motion table + correction plan), fidelity.json,
a shareable fidelity-card.svg (88% · B · stripe.com), and a `fidelit