Roast My Design System

roast-my-design-system

Find where your AI agent will invent UI.

Your AI can write the UI. This makes sure it writes *your* UI.

npx roast-my-design-system@latest

Run it at the root of a UI repo. One second later, a report opens. No account. No network. No telemetry. Nothing in your repo changes.

Website, with the live example reports: www.roastds.com.

Version history is in CHANGELOG.md.

The idea

An agent copies what it finds.

It invents where the repo has no answer.

We tested this on 10 real open-source products, in 355 agent sessions, with and without this tool.

Findings each session added, counted by this tool's own rules:

Routine work stayed on-system with or without the tool. Work that needed something new did not.

An agent does not always call a tool when it should. In October, Sonnet called the MCP tools in 7 of 24 sessions and Haiku in 2 of 24. The edit hook runs without being asked. That is the column with the lowest numbers.

Where did the agent invent? Where the repo had nothing to copy. Dub has no chart palette. Its own charts hardcode 17 colours. Asked for a chart, Haiku hardcoded 9 more. In October, 5 of the 7 findings Sonnet left with the plugin on were chart colours on Dub. The agent kept them and wrote a comment saying the repo has no chart palette.

So the mess an agent adds is a map of the gaps in your system.

This tool draws the map.

Roast. Teach. Guard.

Roast the repo to find its real design system, the mess in it, and the gaps.

Teach the agent, through generated rules and a local MCP server.

Guard every edit, so the agent does not have to remember to ask.

ROAST what is in the repo, and what is missing ↓ TEACH rules in the agent files, answers over MCP ↓ GUARD every edit checked, the PR gated

What you get

Where will your agent have to guess?

The first thing the report says: the places where the repo has no answer yet, or "No gaps found".

• the gap, in one line
• the files that prove it
• the one move that closes it

One gap is known for certain today, because the runs found it: charts hardcoding colours in a repo with no chart palette. 43 of 126 public repos look like that. A gap joins the list when it has been measured.

Fixes you can make right now to increase the health score

The mess the agent will copy, ranked by what fixing it is worth.

• what was found
• where, with the file path
• why it matters
• what to change
• a copy button with the fix prompt for your agent

Fix, rescan, press the next button.

A score you can defend in a meeting

0 to 100. The same number every run.

Measured against three yardsticks: the ideal norms of a design system, the median of 34 product repos at the core of a 119-repo benchmark, and 10 reputable systems (Primer, Polaris, Carbon, shadcn/ui and others).

Monorepos get a score per package. packages/ui at 80 stops hiding apps/web at 40.

Every finding, with its file path

• every hardcoded colour, and its near-identical twin
• every spacing value off the scale
• every duplicated component

And 8 more kinds, all in What it measures. One HTML file. Open it, Slack it, email it.

The colour usage bar shows where the repo's colour comes from: of every 100 colour uses, how many read a theme colour by name, how many use Tailwind's palette, and how many are strays written by hand. It follows CSS variables, Tailwind themes, Sass and Less variables and JavaScript theme objects to do the counting.

The header names what the repo is built on: shadcn/ui, a Tailwind theme, MUI, Mantine, Chakra or Ant Design, and both kits when a repo uses two.

Rules for your agent

Generated from your repo, into design-system-rules.md:

canonical components the file of colour, spacing and type values known duplicates to avoid spacing steps typefaces the kit's own vocabulary

--apply writes them into every agent file you have: Claude, Cursor, GitHub Copilot, Windsurf. Every scan also checks the rules you already have for stale references.

A script does the counting

Every number comes from a deterministic read of your files. Claude writes the explanation, labelled as written by AI and kept apart from the numbers.

How the runs were done

Claude Code, headless, on 10 public products pinned to one commit each: cal.com, Dub, Metabase, Plausible, SigNoz, trigger.dev and four more. 259 sessions in September 2026 and 96 in October 2026 on roast 10.1, with Sonnet 5 and Haiku 4.5. The October sessions repeat the chart and new-component tasks on Plausible, SigNoz, trigger.dev and Dub at the same commits. Every changed file was judged by this tool's rules at the end of the session and at the pinned commit. A finding counts only if the session added it.

Nothing was rendered. Zero findings means the code follows these rules. It does not mean the design was reviewed. Method, tables and limits are in the research write-up, which will be published separately.

Live examples

Eleven reports, hosted exactly as the tool writes them. Every number deterministic, every path real.

• [npx shadcn create, fresh](https://www.roastds.com/examples/shadcn-create-fresh) (factory install, all 61 components): read as a fresh install, "the score is the kit's, not yours"; 13 colours, every theme variable in place, shadcn's own 24 bracket values named and not counted. No score.
• [Unleash](https://www.roastds.com/examples/unleash-mui) (MUI): 1,109 files import the kit and the theme is read 6,166 times; 4 colours and 2 spacings per 100 kit files are written onto components. Score 60.
• [Metabase](https://www.roastds.com/examples/metabase-mantine) (Mantine): its own wrapper over Mantine counts as the kit, so 2,679 files are read instead of 392; nothing written onto components, 2 spacings per 100 kit files. Score 47.
• [SigNoz](https://www.roastds.com/examples/signoz-antd) (Ant Design): 2 colours and 7 spacings per 100 kit files written in style objects where a token exists. Score 51.
• [Apache Airflow](https://www.roastds.com/examples/airflow-chakra) (Chakra UI): no colours written onto components, 4 spacings per 100 kit files as pixel strings where a space step exists. Score 43.
• [vercel/ai-chatbot](https://www.roastds.com/examples/vercel-ai-chatbot) (shadcn install): 71 values like [13px] written outside the Tailwind scale, and 66 palette colours per 100 files where a theme variable exists; Claude's notes embedded. Score 80.
• [excalidraw/excalidraw](https://www.roastds.com/examples/excalidraw-excalidraw): 78 off-scale spacing values and 90 !important declarations. Score 55.
• [dubinc/dub](https://www.roastds.com/examples/dubinc-dub): 642 arbitrary bracket values, 21 duplicated components, and the chart-palette gap named. Score 20.
• [telekom/scale](https://www.roastds.com/examples/telekom-scale) (Stencil): 95 Stencil components read by tag; 66 spacing values outside the scale where about 12 would do; Claude's notes embedded. Score 55.
• [magicuidesign/magicui](https://www.roastds.com/examples/magicui) (registry): counted on the components it publishes, 52 off-theme colours per 100 files in the code it ships, its docs site kept out and named. Score 78.
• [adobe/spectrum-web-components](https://www.roastds.com/examples/adobe-spectrum) (Lit): 740 colour tokens with 8 hardcoded colours beside them, and 37 !important declarations. Score 83.

The full report for vercel/ai-chatbot. The verdict answers what the agent will learn here, the gap section comes first, then "What the repo teaches the agent", Claude's read of the scan:

The same report in light mode (one file, built-in toggle):

Why the numbers hold

• Deterministic. A zero-dependency Node script reads every file and returns the same numbers every run. About a second on a normal repo.
• Read-only. No network. No telemetry. The test suite fails if package.json ever declares a dependency. Every release runs 468 checks against 29 sample repos before it is tagged; the fixtures and their snapshots live in tests/, one JSON file each.
• Honest gaps. What the scan cannot read says "not measured" and drops out of the score.
• Honest exclusions. Tests, stories, docs sites, artwork and email templates are left out. Your own exclusions are printed in the report header with file counts.
• A real benchmark. 119 public repos. A core fleet of 34 React repos sets the medians; the rest feed the kit and web-component groups, so a shadcn repo is compared with shadcn repos and a Lit system with Lit and Stencil systems. The builder is in tools/benchmark/.
• Importable scoring. scoreHarvest(harvest) returns the score and metrics as plain data. The report and a CI check get the same numbers.

The long version, with scan scoping and what the plugin runs on your machine, is in docs/reference.md.

Works with

Frameworks

React, Next.js, Remix, Vite Stencil, Lit, custom elements

Kits and styling

Tailwind, sha