ui-design-system
UI design system toolkit for Senior UI Designer including design token generation, component documentation, responsive design calculations, and developer handoff tools. Use for creating design systems, maintaining visual consistency, and facilitating design-dev collaboration.
- License 许可
- MIT
- 最近更新
- 2026-06-04
- Stars
- ★ 2
- Forks
- 0
01 前言 Front Matter
- name
- ui-design-system
- description
- UI design system toolkit for Senior UI Designer including design token generation, component documentation, responsive design calculations, and developer handoff tools. Use for creating design systems, maintaining visual consistency, and facilitating design-dev collaboration.
02 资源文件 6
- 资产文件assets/design_system_doc_template.md6.7 KB
- 参考文档references/component-architecture.md9.9 KB
- 参考文档references/developer-handoff.md10.0 KB
- 参考文档references/responsive-calculations.md8.6 KB
- 参考文档references/token-generation.md8.3 KB
- 脚本scripts/design_token_generator.py20.1 KB
03 SKILL.md 正文
UI Design System
Generate design tokens, create color palettes, calculate typography scales, build component systems, and prepare developer handoff documentation.
Table of Contents
Trigger Terms
Use this skill when you need to:
- "generate design tokens"
- "create color palette"
- "build typography scale"
- "calculate spacing system"
- "create design system"
- "generate CSS variables"
- "export SCSS tokens"
- "set up component architecture"
- "document component library"
- "calculate responsive breakpoints"
- "prepare developer handoff"
- "convert brand color to palette"
- "check WCAG contrast"
- "build 8pt grid system"
Workflows
Workflow 1: Generate Design Tokens
Situation: You have a brand color and need a complete design token system.
Steps:
-
Identify brand color and style
- Brand primary color (hex format)
- Style preference:
modern|classic|playful
-
Generate tokens using script
python scripts/design_token_generator.py "#0066CC" modern json -
Review generated categories
- Colors: primary, secondary, neutral, semantic, surface
- Typography: fontFamily, fontSize, fontWeight, lineHeight
- Spacing: 8pt grid-based scale (0-64)
- Borders: radius, width
- Shadows: none through 2xl
- Animation: duration, easing
- Breakpoints: xs through 2xl
-
Export in target format
# CSS custom properties python scripts/design_token_generator.py "#0066CC" modern css > design-tokens.css # SCSS variables python scripts/design_token_generator.py "#0066CC" modern scss > _design-tokens.scss # JSON for Figma/tooling python scripts/design_token_generator.py "#0066CC" modern json > design-tokens.json -
Validate accessibility
- Check color contrast meets WCAG AA (4.5:1 normal, 3:1 large text)
- Verify semantic colors have contrast colors defined
Workflow 2: Create Component System
Situation: You need to structure a component library using design tokens.
Steps:
-
Define component hierarchy
- Atoms: Button, Input, Icon, Label, Badge
- Molecules: FormField, SearchBar, Card, ListItem
- Organisms: Header, Footer, DataTable, Modal
- Templates: DashboardLayout, AuthLayout
-
Map tokens to components
Component Tokens Used Button colors, sizing, borders, shadows, typography Input colors, sizing, borders, spacing Card colors, borders, shadows, spacing Modal colors, shadows, spacing, z-index, animation -
Define variant patterns
Size variants:
sm: height 32px, paddingX 12px, fontSize 14px md: height 40px, paddingX 16px, fontSize 16px lg: height 48px, paddingX 20px, fontSize 18pxColor variants:
primary: background primary-500, text white secondary: background neutral-100, text neutral-900 ghost: background transparent, text neutral-700 -
Document component API
- Props interface with types
- Variant options
- State handling (hover, active, focus, disabled)
- Accessibility requirements
-
Reference: See
references/component-architecture.md
Workflow 3: Responsive Design
Situation: You need breakpoints, fluid typography, or responsive spacing.
Steps:
-
Define breakpoints
Name Width Target xs 0 Small phones sm 480px Large phones md 640px Tablets lg 768px Small laptops xl 1024px Desktops 2xl 1280px Large screens -
Calculate fluid typography
Formula:
clamp(min, preferred, max)/* 16px to 24px between 320px and 1200px viewport */ font-size: clamp(1rem, 0.5rem + 2vw, 1.5rem);Pre-calculated scales:
--fluid-h1: clamp(2rem, 1rem + 3.6vw, 4rem); --fluid-h2: clamp(1.75rem, 1rem + 2.3vw, 3rem); --fluid-h3: clamp(1.5rem, 1rem + 1.4vw, 2.25rem); --fluid-body: clamp(1rem, 0.95rem + 0.2vw, 1.125rem); -
Set up responsive spacing
Token Mobile Tablet Desktop --space-md 12px 16px 16px --space-lg 16px 24px 32px --space-xl 24px 32px 48px --space-section 48px 80px 120px -
Reference: See
references/responsive-calculations.md
Workflow 4: Developer Handoff
Situation: You need to hand off design tokens to development team.
Steps:
-
Export tokens in required formats
# For CSS projects python scripts/design_token_generator.py "#0066CC" modern css # For SCSS projects python scripts/design_token_generator.py "#0066CC" modern scss # For JavaScript/TypeScript python scripts/design_token_generator.py "#0066CC" modern json -
Prepare framework integration
React + CSS Variables:
import './design-tokens.css'; <button className="btn btn-primary">Click</button>Tailwind Config:
const tokens = require('./design-tokens.json'); module.exports = { theme: { colors: tokens.colors, fontFamily: tokens.typography.fontFamily } };styled-components:
import tokens from './design-tokens.json'; const Button = styled.button` background: ${tokens.colors.primary['500']}; padding: ${tokens.spacing['2']} ${tokens.spacing['4']}; `; -
Sync with Figma
- Install Tokens Studio plugin
- Import design-tokens.json
- Tokens sync automatically with Figma styles
-
Handoff checklist
- [ ] Token files added to project
- [ ] Build pipeline configured
- [ ] Theme/CSS variables imported
- [ ] Component library aligned
- [ ] Documentation generated
-
Reference: See
references/developer-handoff.md
Tool Reference
design_token_generator.py
Generates complete design token system from brand color.
| Argument | Values | Default | Description |
|---|---|---|---|
| brand_color | Hex color | #0066CC | Primary brand color |
| style | modern, classic, playful | modern | Design style preset |
| format | json, css, scss, summary | json | Output format |
Examples:
# Generate JSON tokens (default)
python scripts/design_token_generator.py "#0066CC"
# Classic style with CSS output
python scripts/design_token_generator.py "#8B4513" classic css
# Playful style summary view
python scripts/design_token_generator.py "#FF6B6B" playful summary
Output Categories:
| Category | Description | Key Values |
|---|---|---|
| colors | Color palettes | primary, secondary, neutral, semantic, surface |
| typography | Font system | fontFamily, fontSize, fontWeight, lineHeight |
| spacing | 8pt grid | 0-64 scale, semantic (xs-3xl) |
| sizing | Component sizes | container, button, input, icon |
| borders | Border values | radius (per style), width |
| shadows | Shadow styles | none through 2xl, inner |
| animation | Motion tokens | duration, easing, keyframes |
| breakpoints | Responsive | xs, sm, md, lg, xl, 2xl |
| z-index | Layer system | base through notification |
Quick Reference Tables
Color Scale Generation
| Step | Brightness | Saturation | Use Case |
|---|---|---|---|
| 50 | 95% fixed | 30% | Subtle backgrounds |
| 100 | 95% fixed | 38% | Light backgrounds |
| 200 | 95% fixed | 46% | Hover states |
| 300 | 95% fixed | 54% | Borders |
| 400 | 95% fixed | 62% | Disabled states |
| 500 | Original | 70% | Base/default color |
| 600 | Original × 0.8 | 78% | Hover (dark) |
| 700 | Original × 0.6 | 86% | Active states |
| 800 | Original × 0.4 | 94% | Text |
| 900 | Original × 0.2 | 100% | Headings |
Typography Scale (1.25x Ratio)
| Size | Value | Calculation |
|---|---|---|
| xs | 10px | 16 ÷ 1.25² |
| sm | 13px | 16 ÷ 1.25¹ |
| base | 16px | Base |
| lg | 20px | 16 × 1.25¹ |
| xl | 25px | 16 × 1.25² |
| 2xl | 31px | 16 × 1.25³ |
| 3xl | 39px | 16 × 1.25⁴ |
| 4xl | 49px | 16 × 1.25⁵ |
| 5xl | 61px | 16 × 1.25⁶ |
WCAG Contrast Requirements
| Level | Normal Text | Large Text |
|---|---|---|
| AA | 4.5:1 | 3:1 |
| AAA | 7:1 | 4.5:1 |
Large text: ≥18pt regular or ≥14pt bold
Style Presets
| Aspect | Modern | Classic | Playful |
|---|---|---|---|
| Font Sans | Inter | Helvetica | Poppins |
| Font Mono | Fira Code | Courier | Source Code Pro |
| Radius Default | 8px | 4px | 16px |
| Shadows | Layered, subtle | Single layer | Soft, pronounced |
Knowledge Base
Detailed reference guides in references/:
| File | Content |
|---|---|
token-generation.md |
Color algorithms, HSV space, WCAG contrast, type scales |
component-architecture.md |
Atomic design, naming conventions, props patterns |
responsive-calculations.md |
Breakpoints, fluid typography, grid systems |
developer-handoff.md |
Export formats, framework setup, Figma sync |
Validation Checklist
Token Generation
- [ ] Brand color provided in hex format
- [ ] Style matches project requirements
- [ ] All token categories generated
- [ ] Semantic colors include contrast values
Component System
- [ ] All sizes implemented (sm, md, lg)
- [ ] All variants implemented (primary, secondary, ghost)
- [ ] All states working (hover, active, focus, disabled)
- [ ] Uses only design tokens (no hardcoded values)
Accessibility
- [ ] Color contrast meets WCAG AA
- [ ] Focus indicators visible
- [ ] Touch targets ≥ 44×44px
- [ ] Semantic HTML elements used
Developer Handoff
- [ ] Tokens exported in required format
- [ ] Framework integration documented
- [ ] Design tool synced
- [ ] Component documentation complete
04 同仓库更多 Skills
syllabus
Generates a curated supplementary reading list from any course syllabus using Consensus academic search. Grill-me intake (syllabus input format + course audience + year range) plus a grouping forcing-options checkpoint before any search runs — so the reading list matches the course's level and recency need. Parses the syllabus to extract topics and learning outcomes, searches Consensus for recent peer-reviewed papers per topic, and produces a professionally formatted .docx with clickable Consensus links, plain-language summaries calibrated to audience level, and Bloom-higher-order discussion questions tied to course learning goals. Triggers whenever a user uploads a syllabus, course outline, or curriculum document and wants supplementary readings. Also triggers on: 'syllabus reading list', 'find papers for my course', 'create a reading list from this syllabus', 'recent research for my class', 'supplementary readings', 'find journal articles for these topics', 'what recent papers cover this material', 'any new research on these course topics', 'update my syllabus with recent papers'. Even casual mentions when a syllabus is attached should trigger this skill.
research
Default entry point for any research request — a hybrid router that classifies the question deterministically and either delegates to a specialist research skill (pulse for trends/sentiment, grants for NIH funding, litreview for academic literature, syllabus for course reading, patent for prior-art + IP landscape, dossier for entity research) or runs its own plan-decompose-multi-source-search-synthesize-cite fallback workflow when no specialist matches. Always surfaces the routing decision so users can override. Triggers — "research [topic]", "look into [topic]", "what do we know about [topic]", "investigate [topic]", "find me information on [topic]", "do some research on [topic]", "I need to understand [topic]", or any research request that doesn't obviously match a more-specific specialist skill. Output is a markdown briefing (default) or .docx document (on request) with full citations and an audit log.
pulse
Multi-source recency research skill that takes the pulse of any topic across Reddit, Hacker News, the open web, and optionally X/Twitter within a configurable recent window (default 30 days). Forcing intake clarifies topic specificity, angle (trend/sentiment/problems/opportunities/comparison), time window, and platform scope before searching. Returns a synthesized briefing with citations, engagement metrics, and cross-platform pattern analysis. Triggers: 'pulse on [topic]', 'what's happening with [topic]', 'what are people saying about [topic]', 'current conversation about [topic]', 'take the pulse of [topic]', 'trending: [topic]', 'find me info on [topic]', or any variation requesting multi-source recency intelligence on a topic. Also use for competitor research, trend discovery, tool comparisons, and audience sentiment analysis.
patent
Patent prior-art and landscape intelligence skill — not generic patent help. Commits to one of five sub-use-cases via forcing intake (novelty search / freedom-to-operate / competitive landscape / acquisition diligence / litigation prior-art) before any search runs. Searches Google Patents, Espacenet, USPTO, and optionally Lens.org for citation-graph signals. Output is an editable Word document (.docx) with verdict, ranked closest art (claim-text extracted), CPC-class-aware landscape, family-resolved hits, geographic coverage, FTO flags where applicable, strategy recommendations, and full audit log. Triggers: 'prior art search for [invention]', 'patent search on [topic]', 'freedom to operate analysis', 'FTO for [product]', 'patent landscape for [field]', 'is [invention] novel', 'patents on [topic]', 'competitive patent analysis', 'prior art for litigation', 'patent diligence on [company]'. Produces search signal, not legal advice — always recommends consulting a patent attorney before filing or licensing decisions. Trademark, copyright, and trade-secret questions are out of scope.
notebooklm
Browser automation skill for controlling Google's NotebookLM. Handles reading and querying notebooks, adding sources (URLs, text, files, YouTube links, synthesized content), generating Studio outputs (Audio Overview, infographics, slide decks, study guides, briefing docs, mind maps, timelines, FAQs), and creating new notebooks. Triggers on any phrase involving NotebookLM — 'open NotebookLM', 'check my [name] notebook', 'pull info from NotebookLM', 'ask my notebook about X', 'add [source] to NotebookLM', 'create an infographic in NotebookLM', 'use NotebookLM Studio', 'generate a slide deck from my notebook', or any variation where the goal involves NotebookLM. Requires browser automation environment — fails gracefully when unavailable.
litreview
Academic literature orientation skill that searches papers via Consensus, builds a strategic search plan using PICO (default) or SPIDER / Decomposition / hybrid as fallbacks, and synthesizes findings into a professionally formatted Word document (.docx) research guide. Grill-me intake (research question specificity + framework hint + tentative depth) before the recon search; a second forcing checkpoint after Phase 2 confirms framework + sub-areas + depth before searches consume budget. Configurable depth (5/10/20 queries) controls coverage vs. speed. Output is a 'launching pad' — not a finished review, but an orientation guide that lets a researcher dive in confidently. Triggers: 'litreview on [topic]', 'literature review on [topic]', 'I'm starting a literature review on X', 'I'm writing a paper on X', 'help me research X', 'I'm doing research on X', 'can you help me research X'. Do NOT trigger for single one-off paper searches where the user just wants a quick list — that's a plain Consensus search.