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.
How do I install this agent skill?
npx skills add https://github.com/plugin87/ux-ui-agent-skills --skill image-to-codeIs this agent skill safe to install?
- Gen Agent Trust Hubpass
This skill converts design images or mockups into code by analyzing visual styles and mapping them to a design token system. It uses a set of local scripts for design system searching, contrast validation, and rendering measurement. No security concerns were identified beyond the expected operation of the tool within a local project environment.
- Socketpass
No alerts
- Snykpass
Risk: LOW · No issues
What does this agent skill do?
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/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.
How can the creator link this skill?
Add the canonical catalog link to the repository README so users can inspect current installs and available audits. The publishing guide covers the complete discovery path.
<a href="https://skillzs.dev/skills/plugin87/ux-ui-agent-skills/image-to-code">View image-to-code on skillZs</a>