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設計系統

使用此技能來生成或審計設計系統、檢查視覺一致性,以及審查涉及樣式的 PR。

設計系統 是什麼?

此技能旨在協助開發者與 AI 代理建立、審計及維護設計系統。它提供三種運作模式:第一種模式會掃描現有程式碼(CSS、Tailwind 或 styled-components),從中提取顏色、排版、間距等設計 token,並參考競爭對手網站後生成一份完整的設計系統,包含一個互動式 HTML 預覽頁面。第二種模式能對現有 UI 進行視覺審計,從色彩一致性、排版層級、間距韻律、動畫、可及性等 10 個維度評分,並針對每個問題給出精確的檔案與行號建議。第三種模式則能辨識常見的 AI 生成設計模式(例如過度漸層、千篇一律的毛玻璃效果、無個性的字型堆疊),幫助團隊避免落入俗套。此技能支援各大程式碼編輯器與 AI 平台(如 Claude Code、Cursor 等),並以指令 ` /design-system` 觸發,對前端工程師、設計師及產品團隊而言是確保視覺一致性的實用工具。

相容平台~Claude Code~Codex CLI~Cursor
npx skills add https://github.com/affaan-m/everything-claude-code/tree/main/skills/design-system

在你喜歡的 AI 中提問

開啟一個已預先載入此 Agent Skill 的新對話。

說明文件

設計系統 — 生成與審計視覺系統

使用時機

  • 啟動一個需要設計系統的新專案
  • 審計現有程式碼庫的視覺一致性
  • 在重新設計之前,了解現有資產
  • 當 UI 看起來「不對勁」但找不出原因時
  • 審查涉及樣式的 PR

運作方式

模式 1:生成設計系統

分析你的程式碼庫並生成統一的設計系統:

1. 掃描 CSS / Tailwind / styled-components 中現有的模式
2. 提取:顏色、排版、間距、邊框圓角、陰影、斷點
3. 研究 3 個競爭對手的網站以獲取靈感(透過瀏覽器 MCP)
4. 提出一套設計 token(JSON + CSS 自訂屬性)
5. 生成 DESIGN.md,說明每個決策的理由
6. 建立一個互動式 HTML 預覽頁面(獨立檔案,無依賴)

輸出:DESIGN.md + design-tokens.json + design-preview.html

模式 2:視覺審計

從 10 個維度為你的 UI 評分(每個維度 0-10 分):

1. 色彩一致性 — 是否使用你的色板,還是隨機的十六進制色碼?
2. 排版層級 — h1 > h2 > h3 > body > caption 是否清晰?
3. 間距韻律 — 使用一致的級距(4px / 8px / 16px)還是隨意設定?
4. 元件一致性 — 相似的元素是否看起來相似?
5. 響應式行為 — 在各斷點下流暢還是破版?
6. 深色模式 — 完整支援還是半成品?
7. 動畫 — 有意義還是過度裝飾?
8. 可及性 — 對比度、焦點狀態、觸控目標
9. 資訊密度 — 雜亂還是簡潔?
10. 精緻度 — 懸浮狀態、過渡效果、載入狀態、空白狀態

每個維度都會有分數、具體範例,以及包含檔案:行數的修正建議。

模式 3:AI 生成設計偵測

辨識常見的 AI 生成設計模式:

- 到處都是不必要的漸層
- 預設紫色到藍色的配色
- 毫無目的的「毛玻璃」卡片
- 不該圓角的元素卻加了圓角
- 滾動時過度的動畫
- 千篇一律的置中文字搭配純色漸層的英雄區
- 沒有個性的無襯線字型堆疊

範例

為 SaaS 應用生成:

/design-system generate --style minimal --palette earth-tones

審計現有 UI:

/design-system audit --url http://localhost:3000 --pages / /pricing /docs

檢查 AI 生成內容:

/design-system slop-check

Individual skills in this repo

This repo contains 20 individual skills — each has its own dedicated page.

accessibility

Design, implement, and audit inclusive digital products using WCAG 2.2 Level AA. Use when building or auditing UI that must meet WCAG 2.2 Level AA, or when reviewing a change for keyboard, contrast, or screen-reader support.

affaan-m/claude-api

Anthropic Claude API patterns for Python and TypeScript. Covers Messages API, streaming, tool use, vision, extended thinking, batches, prompt caching, and Claude Agent SDK. Use when building applications with the Claude API or Anthropic SDKs.

affaan-m/everything-claude-code

End-to-end marketing campaign planning and execution. Covers audience research, positioning, campaign angle definition, landing page copy, email sequences, social posts, ad copy, short-form video scripts, and content calendars. Use as the orchestration layer for multi-channel product launches. Use when planning or executing a multi-channel product launch, or producing landing page, email, social, or ad copy.

affaan-m/everything-claude-code

Development conventions and patterns for everything-claude-code. JavaScript project with conventional commits.

affaan-m/everything-claude-code-conventions

Development conventions and patterns for everything-claude-code. JavaScript project with conventional commits.

affaan-m/frontend-design

Create distinctive, production-grade frontend interfaces with high design quality. Use when the user asks to build web components, pages, or applications and the visual direction matters as much as the code quality.

affaan-m/gget

gget CLI and Python workflow for quick genomic database queries, sequence lookup, BLAST-style searches, enrichment checks, and reproducible bioinformatics evidence logs.

affaan-m/literature-review

Systematic literature-review workflow for academic, biomedical, technical, and scientific topics, including search planning, source screening, synthesis, citation checks, and evidence logging.

affaan-m/motion-ui

Production-ready UI motion system for React/Next.js. Use when implementing animations, transitions, or motion patterns.

affaan-m/project-guidelines-example

Example project-specific skill template based on a real production application.

affaan-m/pubmed-database

Direct PubMed and NCBI E-utilities search workflows for biomedical literature, MeSH queries, PMID lookup, citation retrieval, and API-backed literature monitoring.

affaan-m/scholar-evaluation

Structured scholarly-work evaluation for papers, proposals, literature reviews, methods sections, evidence quality, citation support, and research-writing feedback.

affaan-m/uspto-database

USPTO patent and trademark data workflow for official record lookup, PatentSearch queries, TSDR checks, assignment data, and reproducible IP research logs.

agent-architecture-audit

Full-stack diagnostic for agent and LLM applications. Audits the 12-layer agent stack for wrapper regression, memory pollution, tool discipline failures, hidden repair loops, and rendering corruption. Produces severity-ranked findings with code-first fixes. Essential for developers building agent applications, autonomous loops, or any LLM-powered feature. Use when an agent or LLM feature misbehaves and the failing layer is unknown, or before shipping an agent stack.

agent-eval

Head-to-head comparison of coding agents (Claude Code, Aider, Codex, etc.) on custom tasks with pass rate, cost, time, and consistency metrics. Use when choosing between coding agents, or when a change to an agent setup needs measured pass rate, cost, and time rather than an impression.

agent-harness-construction

Design and optimize AI agent action spaces, tool definitions, and observation formatting for higher completion rates. Use when defining or revising an agent

agentic-engineering

Operate as an agentic engineer using eval-first execution, decomposition, and cost-aware model routing. Use when planning or executing engineering work that agents will carry out end to end.

agentic-os

Build persistent multi-agent operating systems on Claude Code. Covers kernel architecture, specialist agents, slash commands, file-based memory, scheduled automation, and state management without external databases. Use when building a persistent multi-agent system on Claude Code with its own memory, commands, and scheduling.

agent-introspection-debugging

Structured self-debugging workflow for AI agent failures using capture, diagnosis, contained recovery, and introspection reports. Use when an agent run fails and you need a reproducible diagnosis instead of a retry.

agent-payment-x402

Add x402 payment execution to AI agents with per-task budgets, spending controls, and non-custodial wallets. Supports Base through agentwallet-sdk and X Layer through OKX Payments / OKX Agent Payments Protocol. Use when an agent must pay for something itself and needs per-task budgets, spending controls, and a non-custodial wallet.

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