Roast My Design System

Name: Roast My Design System
Author: gregkozakiewicz

by gregkozakiewiczversion 10.2.4i★ –iRuns on your computer

Registry nameio.github.gregkozakiewicz/roast-my-design-system

Install

Overview

Description from the maker (original English)

Audit your Design System and serve your Agent the rules that keep AI-written UI on-system.

PopNx MCP’s three pillars

These three are never merged into one score: opinions, measurements and popularity are different things.

User voiceiNo reviews yetReviews open together with accounts in a later step
Our basic checksi1 of 1 passedChecked from public information; code not scanned yet
UsageiEarly↓ 369/wk · ★ –

What you can do with it

We have not written a plain-language summary for this one yet. Below are the facts we read from the registry.

Connection: Runs on your computer
Transport: stdio
Category: Design, images & audio

Install

Pick the AI app you use, then copy the settings.

Before you install

Basic checks: 1 of 1 passed
Runs on your computer with your user’s permissions (files, network, apps).
The registry lists no key to fill in.

You need

npmNode.js installed (for the npx command)

Which app do you use?

ClaudeClaude CodeCursorVS CodeChatGPT

Pick your app above. We remember it, so next time the button says “Install in …”.

Open Claude Desktop → Settings → Developer → Edit Config, and paste this into claude_desktop_config.json

{
  "mcpServers": {
    "roast-my-design-system": {
      "command": "npx",
      "args": [
        "-y",
        "roast-my-design-system",
        "--mcp"
      ]
    }
  }
}

Run this in your terminal

claude mcp add roast-my-design-system -- npx -y roast-my-design-system --mcp

Open in Cursor

Or copy the settings yourself

Paste into .cursor/mcp.json in your project, or ~/.cursor/mcp.json

{
  "mcpServers": {
    "roast-my-design-system": {
      "command": "npx",
      "args": [
        "-y",
        "roast-my-design-system",
        "--mcp"
      ]
    }
  }
}

Your browser asks to open the app, then the app shows the settings and asks you to confirm. Key values are left empty for you to fill in.

Open in VS Code

Or copy the settings yourself

Paste into .vscode/mcp.json in your project

{
  "servers": {
    "roast-my-design-system": {
      "type": "stdio",
      "command": "npx",
      "args": [
        "-y",
        "roast-my-design-system",
        "--mcp"
      ]
    }
  }
}

Your browser asks to open the app, then the app shows the settings and asks you to confirm. Key values are left empty for you to fill in.

This one runs on your computer, and ChatGPT can only connect to servers on the internet. Pick another app.

Your choice stays on this device in a cookie; no account needed.

These settings are generated from the maker’s registry entry. If the README says otherwise, follow the README.

What it can do

Runs on your computer; the tool list appears in your AI app after you install it.

Basic checksi

We check information anyone can see; we have not read the code. Checks that do not apply are left out of the count. · Checked Nov 10, 2026

✓ Pass
Maker matches the repo
The registry name was verified with the GitHub account gregkozakiewicz, which owns the repo
… Not checked yet
Still maintained
We have not read this repo from GitHub yet
… Not checked yet
Has a licence
We have not read this repo from GitHub yet
– Not applicable
Endpoint responds
This one runs on your computer; there is no internet endpoint
– Not applicable
Sign-in with OAuth
Runs on your computer and uses local settings instead
… Not checked yet
No hidden instructions in tool descriptions
Runs on your computer; we can only read tool lists from internet endpoints

Compared with others in Design, images & audioi

More stars than 0% of the other 2857 servers in this category
Published to the registry more recently than 92% of the other 2857 servers in this category
Basic checks equal to or better than 100% of the other 2857 servers in this category

Compared with every active server in this category in the registry. Stars count only when the publisher owns the repo.

Common questions

Is Roast My Design System safe?

It passed 1 of 1 applicable basic checks. We have not read the code. Before adding a key or token, see what access the server asks for and use a key with only the permissions you need.

What keys or codes does it need?

The registry does not list a required key, though some servers ask you to sign in on first use.

Does it run on my computer or in the cloud?

It runs on your computer. Your AI app starts it when needed, and data does not pass through the maker’s servers (unless it calls an online service itself).

Is it still maintained?

The GitHub repo last changed –, and the latest version (10.2.4) reached the registry 2 days ago.

Which apps can use it?

Apps that support MCP, such as Claude Desktop, Claude Code, Cursor and VS Code. You also need Node.js on your computer.

What can I use instead?

In the same category: Figma Context MCP, Claude Real Video, Figma MCP Server

Alternatives

Servers in the same category from other makers, sorted by stars.

Reading a card:↓ Downloads per weeki★ GitHub starsiThree pillars: reviews · checks · usageiUpdated = latest version published to the registryi

Figma Context MCP

Give your coding agent access to your Figma data. Implement designs in any framework in one-shot.

by GLipsWidely used↓ 161.2K/wk★ 16.2KUpdated 5 months ago

Runs on your computer

Install

Claude Real Video

Let any LLM watch a video locally — and search everything it has ever watched.

by HUANGCHIHHUNGLeoWidely used↓ 1.1K/wk★ 2.3KUpdated 2 months ago

Runs on your computer

Install

Figma MCP Server

Figma’s official server gives AI your design data so it can turn designs into code or describe them accurately. Connects to Figma’s cloud.

by figmaWidely used★ 2.2KUpdated 13 months ago

Runs in the cloud✓ mcp.figma.com

Install

README from the maker

Open the README

Copied from the maker’s repo as written. PopNx MCP has not reviewed or endorsed it. HTML, images and scripts are removed. Links lead off this site.

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:

Task	Model	When	Without roast	Roast MCP and rules installed	Roast plugin with its edit hook
A new chart and a new component, 4 products, 3 runs each	Sonnet 5	Oct 2026, roast 10.1	21 in 24 runs	not run	7 in 24 runs
A new chart and a new component, 4 products, 3 runs each	Haiku 4.5	Oct 2026, roast 10.1	72 in 24 runs	not run	1 in 24 runs
Add a panel, build a dashboard, tighten a list (80 sessions)	Sonnet 5	Sept 2026	7	9	not run
A Christmas theme, 10 products	Sonnet 5	Sept 2026	28	2	not run
A new chart, 4 products, 5 runs each	Sonnet 5	Sept 2026	10 in 20 runs	not run	0 in 20 runs
A new chart, 4 products	Haiku 4.5	Sept 2026	25	39	0 in 14 of 15 runs
Chart, status colour, empty state, new component	Haiku 4.5	Sept 2026	42 in 16 runs	49 in 16 runs	3 in 51 runs

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

Only the beginning is shown; read the rest in the repo

Roast My Design System

Overview

PopNx MCP’s three pillars

What you can do with it

Install

Before you install

What it can do

Basic checksi

Maker matches the repo

Still maintained

Has a licence

Endpoint responds

Sign-in with OAuth

No hidden instructions in tool descriptions

Compared with others in Design, images & audioi

Common questions

Alternatives

Figma Context MCP

Claude Real Video

Figma MCP Server

README from the maker

roast-my-design-system

Find where your AI agent will invent UI.

The idea

An agent copies what it finds.

It invents where the repo has no answer.

Roast. Teach. Guard.

What you get

Where will your agent have to guess?

Fixes you can make right now to increase the health score

A score you can defend in a meeting

Every finding, with its file path

Rules for your agent

A script does the counting

How the runs were done

Live examples

Why the numbers hold

Works with

Frameworks

Kits and styling