Agent Skills › plugin87/ux-ui-agent-skills › image-to-code

image-to-code

GitHub

将设计参考图转化为基于 Token 的可访问 UI 代码。通过推断设计系统并映射到 Token，生成符合规范的组件代码，并通过对比、对比度及自动化脚本验证结果，确保视觉与功能一致性。

.claude/skills/image-to-code/SKILL.md plugin87/ux-ui-agent-skills

Trigger Scenarios

用户提供设计稿或截图并要求生成对应前端代码需要将视觉原型转换为可维护的 Token 驱动 UI

Install

npx skills add plugin87/ux-ui-agent-skills --skill image-to-code -g -y

More Options

Non-standard path

npx skills add https://github.com/plugin87/ux-ui-agent-skills/tree/main/.claude/skills/image-to-code -g -y

Use without installing

npx skills use plugin87/ux-ui-agent-skills@image-to-code

指定 Agent (Claude Code)

npx skills add plugin87/ux-ui-agent-skills --skill image-to-code -a claude-code -g -y

安装 repo 全部 skill

npx skills add plugin87/ux-ui-agent-skills --all -g -y

预览 repo 内 skill

npx skills add plugin87/ux-ui-agent-skills --list

SKILL.md

Frontmatter

{
    "name": "image-to-code",
    "description": "Turn a reference image, screenshot, or mockup into token-driven, accessible code — infer the design system from the reference (palette, type scale, spacing, radius, layout archetype), map it to the 3-tier tokens, rebuild it, then verify with the kit's gates. Use when the user provides a design\/screenshot and wants matching UI code."
}

Skill: Image to Code

Reconstruct a design from a visual reference as a real design system, not a one-off copy. Match the system (color/type/spacing language), never lift copyrighted imagery or brand assets.

Steps

Read the reference like a designer. Infer and write down:
- Palette — 1 dominant surface family, text colors, 1 primary action + at most 1 accent (sample the hues; don't guess random hex).
- Type — family feel (geometric/grotesk/serif), the scale jumps, display vs. body contrast, weights.
- Spacing & density — base unit, section rhythm, card padding; airy vs. compact.
- Radius & depth — radius language (sharp/soft/pill), shadow vs. hairline separation.
- Layout archetype + sequence — full-bleed hero / asymmetric split / bento / editorial stack (taste/design-taste.md → Variance Mandate).
Anchor to a known system if it's close — browse taste/aesthetic-systems.md / python3 scripts/design_systems.py search <term> and adopt that recipe to stabilize decisions.
Build the token theme from the inferred values → 3-tier DTCG (design-tokens skill); generate a single theme.css. Verify every color pair with scripts/contrast.py / scripts/validate_contrast.py (light + dark) — a sampled brand color that fails AA gets adjusted; taste never overrides POUR.
Rebuild layout + components token-driven via frameworks/adapter-protocol.md + components/*: one shared primitive layer, all 8 states, a11y wired, no emoji (lucide), single theme. Apply taste (design-taste.md) so it doesn't regress to generic.
Verify against the reference — render and screenshot it, compare side-by-side to the reference; run node scripts/measure_render.mjs, lint_hardcodes.py, taste_audit.mjs, and npm run verify.

Verification (definition of done)

npm run verify is 100% (tokens resolve, contrast AA light+dark, no hardcodes/emoji, real-render WCAG).
The rebuilt UI uses ONE inferred token theme — no per-section palettes.
A screenshot of the result visibly matches the reference's design language.

Honest limit: this matches the design system, not a pixel-perfect copy. Do not reproduce the reference's photographs, logos, or copyrighted copy — substitute your own or generic placeholders.