image-to-code
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.
- Installs
- 725
- Last 24h
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- Trending rank
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- Security
- Not audited
Install
Works with every agent the skills CLI supports.
npx skills add https://github.com/plugin87/ux-ui-agent-skills --skill image-to-code- 01
Install
Run the command in your project. The CLI asks which agents to install for.
- 02
Describe the task
Ask your agent for something this skill covers. It loads image-to-code automatically when relevant.
- 03
Review the result
The agent follows the SKILL.md steps, scripts and references bundled with the skill.
SKILL.md
The instructions your agent reads when the skill is triggered.
Skill: Image to Code
Step 0: is the kit here? This skill reads files from the kit. Check once:
ls ${CLAUDE_SKILL_DIR}/../../../tokens >/dev/null 2>&1 && echo KIT_OK || echo KIT_MISSINGOnKIT_MISSINGonly the skill folders were installed, which is whatnpx skills adddoes. Say so plainly, point the user atnpx ux-ui-agent-skills initor the plugin install, and stop. Do not guess the contents of a file you could not open.
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: bounded hero / asymmetric split / dense bento / editorial stack (
${CLAUDE_SKILL_DIR}/../../../taste/design-taste.md→ Variance Mandate).
- Anchor to a known system if it's close: browse
${CLAUDE_SKILL_DIR}/../../../taste/aesthetic-systems.md/python3 ${CLAUDE_SKILL_DIR}/../../../scripts/design_systems.py search <term>and adopt that recipe to stabilize decisions. - Build the token theme from the inferred values → 3-tier DTCG (
design-tokensskill); generate a singletheme.css. Verify every color pair with${CLAUDE_SKILL_DIR}/../../../scripts/contrast.py/${CLAUDE_SKILL_DIR}/../../../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
${CLAUDE_SKILL_DIR}/../../../frameworks/adapter-protocol.md+${CLAUDE_SKILL_DIR}/../../../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 ${CLAUDE_SKILL_DIR}/../../../scripts/gate.mjs measure_render.mjs,lint_hardcodes.py,taste_audit.mjs, andnpm run verify.
Verification (definition of done)
npm run verifyis 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.
FAQ
What does the image-to-code skill do?
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.
How do I install image-to-code?
Run npx skills add https://github.com/plugin87/ux-ui-agent-skills --skill image-to-code in your project. The skills CLI detects the agents you use and copies the skill into the right folder. For Claude Code you can also place the skill folder at ~/.claude/skills/image-to-code/ (personal) or .claude/skills/image-to-code/ (project).
Which AI agents can use image-to-code?
Any agent that supports the open Agent Skills format (a folder with a SKILL.md file), including Claude Code, Codex, Cursor, GitHub Copilot, Gemini CLI, Windsurf, Cline, OpenCode and more.
Is image-to-code safe to install?
No partner security audit is available yet. Skills can run commands and scripts, so read the SKILL.md and any bundled files before installing.
Who maintains image-to-code?
It is published by plugin87 in plugin87/ux-ui-agent-skills. It has 725 recorded installs.
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