Roast My Design System

Name: Roast My Design System
Author: gregkozakiewicz

作者：gregkozakiewicz版本 10.2.4i★ 65i在你的电脑上运行

注册名称io.github.gregkozakiewicz/roast-my-design-system

安装

概览

作者提供的说明（英文原文）

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

PopNx MCP 的三大支柱

这三项永远不会合并成一个分数：意见、测量和人气是不同的东西。

用户评价i暂无评价评价功能将在后续阶段与账户功能一起开放
我们的基础检查i2 项中通过 2 项依据公开信息检查；尚未扫描代码
使用情况i正在增长↓ 946/周 · ★ 65

它能帮你做什么

我们还没有为它写通俗的介绍。下面是我们从注册中心读取到的事实。

连接方式: 在你的电脑上运行
传输方式: stdio
分类: 设计、图片与音频

安装

选择你使用的 AI 应用，然后复制设置。

安装之前

基础检查：2 项中通过 2 项
在你的电脑上运行，拥有你的用户账户的权限（文件、网络、应用）。
注册中心没有列出需要填写的密钥。

你需要

npm已安装 Node.js（用于 npx 命令）

你用的是哪个应用？

ClaudeClaude CodeCursorVS CodeChatGPT

在上方选择你的应用。我们会记住它，下次按钮会显示“安装到 …”。

打开 Claude Desktop → Settings → Developer → Edit Config，把下面的内容粘贴到 claude_desktop_config.json

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

在终端中运行这条命令

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

在 Cursor 中打开

或者自己复制设置

粘贴到项目中的 .cursor/mcp.json，或 ~/.cursor/mcp.json

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

浏览器会先询问是否打开应用，然后应用会显示设置并请你确认。密钥的值会留空，由你自己填写。

在 VS Code 中打开

或者自己复制设置

粘贴到项目中的 .vscode/mcp.json

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

浏览器会先询问是否打开应用，然后应用会显示设置并请你确认。密钥的值会留空，由你自己填写。

这个服务器在你的电脑上运行，而 ChatGPT 只能连接互联网上的服务器。请选择其他应用。

你的选择通过 Cookie 保存在这台设备上，无需账户。

这些设置是根据作者在注册中心的条目生成的。如果 README 的写法不同，请以 README 为准。

哪些应用可以使用它

依据这个服务器的连接方式和各应用自己的文档，检查于 2026年11月10日。

在你的电脑上运行，适用于

Claude Goose LM Studio Msty Studio Cherry Studio Cursor VS Code + GitHub Copilot Visual Studio Windsurf (Devin Desktop)Zed Kiro Cline Continue JetBrains AI Assistant Claude Code Codex CLI Gemini CLI OpenCode nodecode Warp LibreChat Raycast

全部应用及其优缺点 →

它能做什么

它在你的电脑上运行；安装后，工具列表会显示在你的 AI 应用中。

基础检查i

我们检查的是任何人都能看到的信息；我们没有阅读代码。不适用的检查项不计入总数。 · 检查于 2026年11月10日

✓ 通过
作者与仓库一致
注册名称已通过 GitHub 账户 gregkozakiewicz 验证，该账户拥有此仓库
✓ 通过
仍在维护
代码最后更新于3天前
… 尚未检查
有许可证
我们还没有从 GitHub 读取这个仓库
– 不适用
端点有响应
它在你的电脑上运行，没有互联网端点
– 不适用
使用 OAuth 登录
在你的电脑上运行，改用本地设置
… 尚未检查
工具描述中没有隐藏指令
它在你的电脑上运行；我们只能读取互联网端点的工具列表

与“设计、图片与音频”中的其他服务器比较i

星标数多于此分类中其他 2880 个服务器的 96%
发布到注册中心的时间比此分类中其他 2880 个服务器的 91% 更新
基础检查结果等于或优于此分类中其他 2880 个服务器的 100%

与注册中心里这个分类中所有活跃的服务器比较。只有当发布者拥有该仓库时，星标数才计入。

常见问题

Roast My Design System 安全吗？

它在 2 项适用的基础检查中通过了 2 项。我们没有阅读代码。在添加密钥或令牌之前，请先看看这个服务器要求哪些权限，并使用只具备所需权限的密钥。

它需要哪些密钥或代码？

注册中心没有列出必需的密钥，不过有些服务器会在首次使用时要求你登录。

它在我的电脑上运行还是在云端？

它在你的电脑上运行。你的 AI 应用会在需要时启动它，数据不会经过作者的服务器（除非它自己调用在线服务）。

它还在维护吗？

GitHub 仓库最后更新于3天前，最新版本（10.2.4）于3天前进入注册中心。

哪些应用可以使用它？

支持 MCP 的应用，例如 Claude Desktop、Claude Code、Cursor 和 VS Code。你的电脑上还需要有 Node.js。

有什么可以替代它？

同一分类中有：Next AI Draw.io, Pascal 3D Editor, screenpipe

替代选择

同一分类中其他作者的服务器，按星标数排序。

如何看卡片：↓ 每周下载量i★ GitHub 星标i三大支柱：评价 · 检查 · 使用情况i更新 = 最新版本发布到注册中心的时间i

Next AI Draw.io

draw.io diagrams your AI agent draws on a live browser canvas that you can also edit by hand

作者：DayuanJiang广泛使用↓ 2.2万/周★ 3.7万3天前更新

在你的电脑上运行

安装

Pascal 3D Editor

Create, inspect, validate, and save editable 3D building scenes with Pascal's MCP server.

作者：pascalorg广泛使用↓ 1037/周★ 2.5万前天更新

电脑或云端✓ pascal.app

安装

screenpipe

Search your local screen recordings, audio transcripts, and computer activity from screenpipe.

作者：screenpipe广泛使用↓ 6626/周★ 2.2万8天前更新

在你的电脑上运行

安装

作者的 README

打开 README

按原文从作者的仓库复制。PopNx MCP 没有审查或背书其内容。HTML、图片和脚本已被移除。链接会离开本站。

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

只显示了开头部分；其余内容请在仓库中阅读