screenshot-to-code

onewave-ai/claude-skills · updated Apr 8, 2026

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$npx skills add https://github.com/onewave-ai/claude-skills --skill screenshot-to-code
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summary

Convert UI screenshots into production-ready code with accurate styling and structure.

skill.md

Screenshot to Code

Convert UI screenshots into production-ready code with accurate styling and structure.

How This Works

When a user provides a screenshot of a UI design:

  1. Analyze the visual design thoroughly
  2. Generate clean, modern code that recreates it
  3. Provide complete, runnable implementation

Instructions

1. Analyze the Screenshot

Examine the image carefully and identify:

  • Layout structure: Grid, flexbox, or custom positioning
  • Components: Buttons, inputs, cards, navigation, modals, etc.
  • Visual details: Colors, fonts, spacing, borders, shadows, borders-radius
  • Responsive considerations: Mobile vs. desktop layout cues

2. Determine the Framework

Ask the user which framework they prefer:

  • React (with Tailwind CSS or styled-components)
  • Vue.js
  • Plain HTML/CSS
  • Next.js

Default: If not specified, use React with Tailwind CSS for modern designs, or plain HTML/CSS for simple pages.

3. Generate Complete Code

Create the implementation:

For React/Vue:

  • Build component hierarchy (break into logical components)
  • Use semantic HTML elements
  • Implement modern CSS (flexbox, grid, custom properties)
  • Include prop types and sensible defaults

For HTML/CSS:

  • Use semantic HTML5 structure
  • Write clean, organized CSS (consider using BEM naming)
  • Make it responsive by default

Critical requirements:

  • Match colors EXACTLY (extract hex codes from screenshot)
  • Match spacing and proportions as closely as possible
  • Use appropriate semantic elements (header, nav, main, section, etc.)
  • Include accessibility attributes (alt text, ARIA labels where needed)

4. Make It Responsive

  • Use responsive units (rem, em, %, vw/vh) rather than fixed pixels
  • Add breakpoints for mobile, tablet, desktop if the design suggests it
  • Use min(), max(), clamp() for fluid typography where appropriate

5. Deliver Complete Implementation

Provide:

  1. Complete code (all files needed, fully functional)
  2. File structure (explain what each file does)
  3. Usage instructions (how to run/use the code)
  4. Notes on design decisions (any assumptions or interpretations)

Output Format

// Example structure for React + Tailwind
import React from 'react';

export default function ComponentName() {
  return (
    <div className="...">
      {/* Component structure */}
    </div>
  );
}

Always include:

  • All necessary imports
  • Any required dependencies
  • Clear comments for complex sections
  • Suggestions for improvements or next steps

Best Practices

  • Accuracy: Match the design as closely as possible
  • Modern CSS: Prefer Grid/Flexbox over floats or tables
  • Accessibility: Include ARIA labels, alt text, semantic HTML
  • Performance: Optimize images, use efficient selectors
  • Maintainability: Write clean, well-organized code with comments
  • Responsiveness: Design mobile-first when possible

Common Patterns

Navigation Bars: Flexbox with space-between, sticky positioning Card Grids: CSS Grid with auto-fit/auto-fill for responsiveness Hero Sections: Full-height with centered content, background images Forms: Proper labels, validation states, accessible inputs Modals: Fixed positioning, backdrop, focus management

When You Can't Match Exactly

If the screenshot is unclear or ambiguous:

  • Make reasonable assumptions based on common UI patterns
  • Note your interpretation in comments
  • Suggest alternatives the user might prefer
  • Ask for clarification on critical decisions

Example Workflow

User provides: Screenshot of a landing page with hero section, feature cards, and footer

Your response:

  1. Analyze: Hero with large headline, 3-column feature grid, simple footer
  2. Ask: "Would you like this in React with Tailwind or plain HTML/CSS?"
  3. Generate: Complete implementation with responsive design
  4. Deliver: All code files with clear structure and usage instructions

Remember: The goal is to produce code so clean and accurate that it could be deployed immediately with minimal modifications.

how to use screenshot-to-code

How to use screenshot-to-code on Cursor

AI-first code editor with Composer

1

Prerequisites

Before installing skills in Cursor, ensure your development environment meets these requirements:

  • Cursor installed and configured on your development machine
  • Node.js version 16.0+ with npm package manager (verify with node --version)
  • Active project directory or workspace where you want to add screenshot-to-code
2

Execute installation command

Execute the skills CLI command in your project's root directory to begin installation:

$npx skills add https://github.com/onewave-ai/claude-skills --skill screenshot-to-code

The skills CLI fetches screenshot-to-code from GitHub repository onewave-ai/claude-skills and configures it for Cursor.

3

Select Cursor when prompted

The CLI will show a list of available agents. Use arrow keys to navigate and space to select Cursor:

◆ Which agents do you want to install to?
│ ── Universal (.agents/skills) ── always included ────
│ • Amp
│ • Antigravity
│ • Cline
│ • Codex
│ ●Cursor(selected)
│ • Cursor
│ • Windsurf
4

Verify installation

Confirm successful installation by checking the skill directory location:

.cursor/skills/screenshot-to-code

Reload or restart Cursor to activate screenshot-to-code. Access the skill through slash commands (e.g., /screenshot-to-code) or your agent's skill management interface.

Security & Verification Notice

We perform automated surface-level scans (Gen AI Scanner, Socket, Snyk) during installation. These checks detect common vulnerabilities but do not guarantee complete security. Always review skill source code and verify the publisher's reputation before production use.

Skills execute code in your development environment. Always verify the publisher's identity, review recent commits, and test in isolated environments before production deployment.

List & Monetize Your Skill

Submit your Claude Code skill and start earning

GET_STARTED →

Use Cases

User Story & Requirements Generation

Create detailed user stories, acceptance criteria, and feature specs

Example

Generate user stories for 'password reset feature' with acceptance criteria, edge cases, and test scenarios

Reduce spec writing time by 50%, ensure comprehensive coverage

Competitive Analysis

Research competitors, compare features, identify gaps

Example

Analyze 5 competitor products, create feature comparison matrix, suggest differentiation opportunities

Complete competitive research in 2 hours instead of 2 days

Roadmap Prioritization

Evaluate features using frameworks (RICE, ICE, Kano) and create prioritized backlogs

Example

Score 20 feature ideas using RICE framework, generate prioritized roadmap with rationale

Make data-driven prioritization decisions faster

Stakeholder Communication

Draft PRDs, status updates, and stakeholder presentations

Example

Create executive summary of Q3 roadmap, monthly progress report, feature launch announcement

Save 3-5 hours/week on communication overhead

Implementation Guide

Prerequisites

  • Claude Desktop or compatible AI client
  • Access to product documentation and roadmap tools (Jira, Notion, etc.)
  • Understanding of product management frameworks (RICE, Jobs-to-be-Done, etc.)
  • Stakeholder contact information and communication channels

Time Estimate

30-60 minutes to see productivity improvements

Installation Steps

  1. 1.Install product management skill
  2. 2.Start with user story generation for known feature
  3. 3.Progress to competitive analysis: research 2-3 competitors
  4. 4.Use for roadmap prioritization: apply RICE/ICE scoring
  5. 5.Draft stakeholder communications and refine based on feedback
  6. 6.Build template library for recurring PM tasks
  7. 7.Share effective prompts with product team

Common Pitfalls

  • Not validating competitive research—verify facts before sharing
  • Accepting user stories without involving engineering team
  • Over-relying on frameworks without qualitative judgment
  • Not customizing outputs to company culture and communication style
  • Skipping stakeholder validation of generated requirements

Best Practices

✓ Do

  • +Validate research and competitive analysis with real data
  • +Collaborate with engineering when generating technical requirements
  • +Customize frameworks and templates to your company context
  • +Use skill for first drafts, refine with stakeholder input
  • +Document successful prompt patterns for PM tasks
  • +Combine AI efficiency with human judgment and intuition

✗ Don't

  • Don't publish competitive analysis without fact-checking
  • Don't finalize user stories without engineering review
  • Don't make prioritization decisions solely on AI scoring
  • Don't skip customer validation of generated requirements
  • Don't ignore company-specific context and culture

💡 Pro Tips

  • Provide context: company goals, constraints, customer feedback
  • Ask for alternatives: 'Show 3 ways to prioritize this roadmap'
  • Request stakeholder-specific formatting: 'Executive summary vs. engineering spec'
  • Use skill for 70% generation + 30% customization to company needs

When to Use This

✓ Use When

Use for user story writing, competitive research, roadmap prioritization, stakeholder communication, and PRD drafting. Best for reducing repetitive documentation and research work.

✗ Avoid When

Avoid for strategic product vision (requires deep customer empathy), pricing decisions (needs market and financial expertise), or when face-to-face customer discovery is more valuable than speed.

Learning Path

  1. 1Basic: user stories, feature specs, status updates
  2. 2Intermediate: competitive analysis, prioritization frameworks, PRDs
  3. 3Advanced: product strategy, go-to-market planning, OKR setting
  4. 4Expert: product vision, market positioning, business model innovation

Discussion

Product Hunt–style comments (not star reviews)
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general reviews

Ratings

4.739 reviews
  • Ganesh Mohane· Dec 24, 2024

    screenshot-to-code is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.

  • Aanya Menon· Dec 20, 2024

    screenshot-to-code fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.

  • James Khan· Dec 16, 2024

    I recommend screenshot-to-code for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.

  • Sakura Khan· Dec 8, 2024

    Solid pick for teams standardizing on skills: screenshot-to-code is focused, and the summary matches what you get after install.

  • Noor Patel· Dec 4, 2024

    Keeps context tight: screenshot-to-code is the kind of skill you can hand to a new teammate without a long onboarding doc.

  • Arya Bansal· Nov 23, 2024

    screenshot-to-code has been reliable in day-to-day use. Documentation quality is above average for community skills.

  • Rahul Santra· Nov 15, 2024

    Useful defaults in screenshot-to-code — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.

  • Fatima Kapoor· Nov 11, 2024

    We added screenshot-to-code from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.

  • Sakura Rahman· Oct 14, 2024

    screenshot-to-code fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.

  • Pratham Ware· Oct 6, 2024

    Registry listing for screenshot-to-code matched our evaluation — installs cleanly and behaves as described in the markdown.

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