React Screenshot Recreator logo

React Screenshot Recreator

Organization
buildfastwithai
react-screenshot-recreator

Recreate a UI screenshot, mockup, or design image as production-quality React + TypeScript + Tailwind code with near-pixel-perfect visual fidelity. Use this skill whenever the user shares an image of an interface and wants it built, cloned, converted, or "made real" — including phrasings like "build this", "recreate this design", "code this Figma export", "clone this landing page", "turn this mockup into React", "make a component that looks like this", or when they paste a screenshot of a website/dashboard/card/pricing table/navbar with little explanation. Also use it when the user asks for HTML/CSS from an image, or wants an existing component restyled to match a reference image. Trigger even if they never say the words "React" or "Tailwind" — this is the default path for image-to-UI work.

Overview

Publisherbuildfastwithai
Repositorygen-ai-experiments
Skill namereact-screenshot-recreator
Stars
785
Forks
225
Bundled files
4
LicenseMIT
Links
  • 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.

  • 4 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by buildfastwithai on GitHub. Read the source before you install it.

Installation

Install the React Screenshot Recreator AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

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.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/buildfastwithai/gen-ai-experiments/tree/main/skills/react-screenshot-recreator
  4. 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.
2

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/buildfastwithai/gen-ai-experiments.git /tmp/gen-ai-experiments
mkdir -p .claude/skills
cp -r /tmp/gen-ai-experiments/skills/react-screenshot-recreator .claude/skills/react-screenshot-recreator
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable React Screenshot Recreator 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 React Screenshot Recreator 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 React Screenshot Recreator 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.

React Component Screenshot Recreator

Turn a screenshot of an interface into React code that a designer would look at, next to the original, and struggle to tell apart.

The failure mode this skill exists to prevent is the plausible approximation: code that captures the gist — a card, a heading, a button — while getting every spacing value, weight, radius, and shadow slightly wrong. The result feels like a sketch of the design rather than the design. Slightly wrong everywhere reads as unmistakably wrong.

Two habits prevent it. First, measure before you write — read values off the image instead of reaching for defaults. Second, reason about intent — real interfaces are built on a spacing scale, a type ramp, and a small palette, so when one value is ambiguous, infer it from the system the rest of the design reveals.

Workflow

  1. Audit the screenshot — a written pass over layout, type, color, effects, and state. Details you don't name, you won't build.
  2. Derive the design system — spacing unit, type ramp, palette, radius scale, shadow scale.
  3. Plan the component tree — decide what's reusable before writing any JSX.
  4. Write the code — TypeScript, Tailwind, semantic HTML, lucide-react icons.
  5. Verify against the image — walk the audit list and check each item landed.

Steps 1 and 5 are what separate a recreation from an approximation. Don't skip them, and don't collapse the audit into a single glance — writing the observations down is what makes them actionable.


Step 1 — Audit the screenshot

Look at the image carefully and write out what you see, before any code. If multiple screenshots were provided (different breakpoints, states, or scroll positions), audit each and note what changes between them — that's free information about responsive and interactive behavior.

Zoom mentally into each region. State values as numbers, not adjectives: "24px gap", not "generous spacing". A number can be translated to Tailwind; an adjective can't.

Cover:

Layout — overall structure (flex row/column, grid with N columns, absolute overlay), container max-width, outer padding, gaps between siblings, internal padding of each box, alignment (start/center/baseline/stretch), and anything that breaks the flow (a badge pinned to a corner, an avatar overlapping a card edge, a sticky header).

Typography — for every distinct text style: size, weight, line height, letter spacing (tight tracking on large headings is extremely common and its absence is very visible), color, case, and truncation. Note the hierarchy: which is the display size, which is body, which is the small muted label.

Color — background layers (page vs. surface vs. elevated surface — they're often 2–4% apart and that difference is the whole look), text colors at each level of emphasis, border colors, accent/brand color, and gradients (direction, stops, and whether the stops are colors or transparent-to-color).

Depth and effects — shadows (spread, blur, y-offset, opacity, and whether there are two layered shadows, which is the norm in good design systems), borders (width, color, whether it's a hairline at low opacity), backdrop blur, glow, inner highlights, noise, rings.

Components — name each archetype you recognize (navbar, hero, feature card, pricing tier, avatar group, badge, progress bar, tab set, accordion, modal, chart). Naming them tells you which conventions to apply and where the reusable boundaries are.

Media — images and icons: dimensions, aspect ratio, crop behavior, corner radius, any overlay or shadow. Identify icons by shape so you can match them to lucide-react.

Implied behavior — hover treatments, active/selected states visible in the shot (one tab is underlined, one nav item is brighter, one pricing card is "highlighted"), focus rings, disabled styling, transitions the design clearly wants (a lift on a card, a color shift on a button).

references/visual-audit.md has the full checklist with the specific things that are easiest to miss. Read it on the first recreation of a session, or any time the screenshot is dense.

Step 2 — Derive the design system

Before writing JSX, collapse your measurements into a small system. This is what makes the output both accurate and maintainable, and it's how you resolve ambiguity honestly.

  • Spacing unit — nearly every real design snaps to a 4px or 8px grid. Once you spot it, round your measurements to it. A gap you read as "23px" is 24px.
  • Type ramp — the sizes you measured almost certainly form a recognizable scale (12/14/16/18/20/24/30/36/48/60). Snap to it.
  • Palette — map each observed color to the nearest Tailwind token when it's close (within a couple percent of lightness); use an arbitrary value like bg-[#0B0F19] when it isn't. Brand colors are usually arbitrary; grays are usually tokens.
  • Radius scale — typically 2–3 values across a design (e.g. 8px for inputs, 12px for cards, full for pills).
  • Shadow scale — usually 2–3 elevations.

If a value is genuinely unreadable from the image, choose the one the system predicts. That's inference, not guessing, and it's why this step comes before the code.

Step 3 — Plan the component tree

Split where the design repeats or where a section is conceptually independent. Three pricing cards means one PricingCard with props, not three JSX blocks. A page-level screenshot means Navbar, Hero, FeatureGrid, Footer as siblings.

Don't over-split. A Divider component that renders one <div> adds indirection for nothing. The test: would you reuse it, or does naming it make the parent easier to read? If neither, inline it.

Define a props interface for anything that varies, and colocate the content as a typed data array so the markup stays clean:

tsx
const tiers: PricingTier[] = [ /* ... */ ];
// ...
{tiers.map((tier) => <PricingCard key={tier.name} {...tier} />)}

Step 4 — Write the code

Stack: React function components, TypeScript, Tailwind utility classes. The output should drop into a standard Vite + React + Tailwind project and run with no extra setup beyond lucide-react.

Tailwind first. Use arbitrary values (pt-[3.25rem], bg-[#0B0F19], shadow-[0_1px_2px_rgba(0,0,0,0.06),0_8px_24px_rgba(0,0,0,0.08)]) rather than dropping into a stylesheet — precision doesn't require abandoning utilities. Reach for a <style> block or CSS module only for things utilities genuinely can't express: @keyframes, complex multi-layer backgrounds, ::before decorations, scroll-driven effects.

Semantic HTML. <header>, <nav>, <main>, <section>, <footer>, <button>, <a>, <ul>/<li>. A clickable thing is a <button> or <a>, never a <div> with onClick — that single choice delivers keyboard access and focus behavior for free.

Icons. Prefer lucide-react. Match by shape; when the exact icon isn't in the set, pick the closest and note the substitution. Fall back to Heroicons or an inline SVG only for logos and genuinely custom marks. Icons that are purely decorative get aria-hidden="true"; icon-only buttons get an aria-label.

Images. Use a placeholder at the exact dimensions with the same object-fit, aspect ratio, radius, and shadow — sizing is structural and a wrong-sized placeholder breaks the layout. For photos, a neutral bg-slate-200 block or https://placehold.co/{w}x{h} both work; leave a comment marking where the real asset goes.

States and motion. Add the hover, focus, and active treatments the design implies, with transition-colors/transition-all and a duration in the 150–300ms range. Include focus-visible: rings on every interactive element. Recreate entrance and ambient animations (fade, slide, scale, float, gradient shift) when the composition implies them — a hero that reads as animated should be. Respect prefers-reduced-motion for anything continuous.

Responsive. Build mobile-first and layer sm:/md:/lg: upward. The screenshot is one breakpoint; infer the others from structure — multi-column grids collapse to one column, horizontal navs become a menu button, display type steps down a size or two, section padding shrinks. Don't invent layouts the design doesn't suggest.

references/tailwind-mapping.md converts measured pixel values to Tailwind classes and covers arbitrary-value syntax. references/effects.md has tested recipes for glassmorphism, neumorphism, gradient text and borders, glow, animated gradients, and layered shadows — read it when the design has any of those. references/patterns.md has structural and accessibility patterns for the common archetypes (navbar, hero, pricing, tabs, accordion, modal, progress, avatar group).

Step 5 — Verify

Re-read your audit from Step 1 and confirm each observation is present in the code. This catches the things that go missing during writing: the letter-spacing on the heading, the second shadow layer, the 1px border at 8% opacity, the badge on the featured card.

Then check the whole: is the visual weight distributed like the original? Does the eye land in the same place first? Contrast is where fidelity is most often lost — muted text that's too dark, or a surface that's too far from the page background, reads wrong even when every measurement is right.

Finally, sanity-check that it compiles: every import used, no undefined variables, key on mapped elements, props typed.


Constraints

Recreate — don't redesign. The instinct to improve what you see is a real one, and here it's the wrong one: the user is asking for this interface, and the parts that look like mistakes are usually deliberate. Don't swap the layout for one you'd prefer, don't simplify a dense section, don't substitute your own color palette or type scale, don't drop elements that seem decorative.

If something in the design looks like an actual error, build it faithfully and mention it afterward in one line. That respects both the request and your judgment.

Never stall on incomplete information. A screenshot is always missing something — what's below the fold, what happens on hover, the exact hex under an overlay. Infer from the surrounding design system, keep the choice consistent with everything else, and note the assumption briefly at the end. An incomplete answer is worth less than a complete one with three noted assumptions.

Deliverable

Return the code — component files, types, and any subcomponents — with a short note listing icon substitutions, placeholder images, and inferred values. Save files when the environment supports it; otherwise return them inline, one code block per file with the filename as the header.

Skip the tutorial. No setup instructions, no explanation of what Tailwind is, no walkthrough of the JSX. The code and a few lines of assumptions are the whole deliverable.

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the React Screenshot Recreator AI skill do?

Recreate a UI screenshot, mockup, or design image as production-quality React + TypeScript + Tailwind code with near-pixel-perfect visual fidelity. Use this skill whenever the user shares an image of an interface and wants it built, cloned, converted, or "made real" — including phrasings like "build this", "recreate this design", "code this Figma export", "clone this landing page", "turn this mockup into React", "make a component that looks like this", or when they paste a screenshot of a website/dashboard/card/pricing table/navbar with little explanation. Also use it when the user asks for...

Why use React Screenshot Recreator on TypingMind?

Because you install it once and use it with any model. React Screenshot Recreator 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 React Screenshot Recreator in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/buildfastwithai/gen-ai-experiments/tree/main/skills/react-screenshot-recreator. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use React Screenshot Recreator?

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 React Screenshot Recreator?

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

Is the React Screenshot Recreator AI skill free?

Yes. It is published on GitHub by buildfastwithai 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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