Image To Code

CommunityPopular

plugin87

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.

Overview

Publisher	plugin87
Repository	`ux-ui-agent-skills`
Skill name	`image-to-code`
Stars	3K
Forks	290
Bundled files	Instructions only
License	MIT
Links	Skill source Repository Homepage

Markdown instructions
A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.
Works with any LLM
AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.
Self-contained
Everything the model needs lives in the instructions — no extra files to sync.
Open source
Published by plugin87 on GitHub. Read the source before you install it.

Installation

Install the Image To Code AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

Open the app and go to Plugins → Skills.
Choose "Install from GitHub".
Paste the skill folder URL below and confirm.
https://github.com/plugin87/ux-ui-agent-skills/tree/main/.claude/skills/image-to-code
Enable the skill in any chat where you want it available.

Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills

git clone --depth 1 https://github.com/plugin87/ux-ui-agent-skills.git /tmp/ux-ui-agent-skills
mkdir -p .claude/skills
cp -r /tmp/ux-ui-agent-skills/.claude/skills/image-to-code .claude/skills/image-to-code

Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Image To Code in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Image To Code on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Image To Code is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

Loaded only when it is needed
The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.
Switch models mid-chat
Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

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_MISSING On KIT_MISSING only the skill folders were installed, which is what npx skills add does. Say so plainly, point the user at npx ux-ui-agent-skills init or 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-tokens skill); generate a single theme.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, 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.

Frequently asked questions

What does the Image To Code AI skill do?

Why use Image To Code on TypingMind?

Because you install it once and use it with any model. Image To Code is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Image To Code in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/plugin87/ux-ui-agent-skills/tree/main/.claude/skills/image-to-code. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Image To Code?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Image To Code?

As many as you like. As long as a model supports skills, you can use Image To Code with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Image To Code AI skill free?

Yes. It is published on GitHub by plugin87 under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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Overview

Installation

Install in TypingMind

Install in another agent

Use it in TypingMind

Works with any AI model

Skill instructions

Skill: Image to Code

Steps

Verification (definition of done)

Frequently asked questions

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