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Screenshot Feature Extractor

  • 507 installs
  • 30.1k repo stars
  • Updated August 4, 2026
  • davila7/claude-code-templates

screenshot-feature-extractor is a Claude Code skill that converts UI screenshots into structured feature lists and implementation prompts for Claude Code or Cursor development sessions.

About

screenshot-feature-extractor is a Claude Code skill from davila7/claude-code-templates (rank 29 on skills.sh, 480 installs) that turns UI screenshots into structured feature lists and implementation prompts. Developers reach for screenshot-feature-extractor when they have a design reference image—mockup, competitor screen, or wireframe—and need agent-ready specs instead of manually listing components. The skill bridges design references and coding agents by producing actionable feature breakdowns Claude or Cursor can implement. With 480 installs, it is a common validate-phase shortcut for teams prototyping UI from visual inputs before writing frontend code.

  • Converts screenshots into clean feature specifications
  • Outputs ready-to-use prompts for agentic coding
  • Reduces manual reverse-engineering of designs
  • Works with any screenshot format via vision models
  • Integrates directly into Claude Code and Cursor workflows

Screenshot Feature Extractor by the numbers

  • 507 all-time installs (skills.sh)
  • Ranked #1,756 of 16,546 AI & Agent Building skills by installs in the Skillselion catalog
  • Data as of Aug 5, 2026 (Skillselion catalog sync)
npx skills add https://github.com/davila7/claude-code-templates --skill screenshot-feature-extractor

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Listed on Skillselion
Installs507
repo stars30.1k
Last updatedAugust 4, 2026
Repositorydavila7/claude-code-templates

How do you turn UI screenshots into implementation specs?

Turn UI screenshots into structured feature lists and implementation prompts for Claude or Cursor.

Who is it for?

Developers or designers with UI reference screenshots who want agent-ready feature specs before writing frontend implementation code.

Skip if: Production accessibility audits, automated visual regression testing, or teams with complete Figma dev-mode specs already exportable as code.

When should I use this skill?

User uploads a UI screenshot and wants a feature breakdown, component list, or implementation prompt for Claude or Cursor.

What you get

Structured feature list and Claude or Cursor implementation prompts derived from screenshot analysis

  • feature list document
  • implementation prompt
  • UI component breakdown

By the numbers

  • 480 installs on skills.sh
  • Rank 29 on skills.sh

Files

SKILL.mdMarkdownGitHub ↗

Screenshot Analyzer (Multi-Agent)

Extract product features from UI screenshots using a coordinated multi-agent analysis pipeline.

Core principle: Describe WHAT to build (features/interactions), NOT HOW (no tech stack).

Multi-Agent Architecture

This skill orchestrates 5 specialized agents for comprehensive analysis:

                    ┌─────────────────┐
                    │   Coordinator   │
                    │   (this skill)  │
                    └────────┬────────┘
                             │
         ┌───────────────────┼───────────────────┐
         │                   │                   │
         ▼                   ▼                   ▼
┌─────────────────┐ ┌─────────────────┐ ┌─────────────────┐
│  UI Analyzer    │ │  Interaction    │ │   Business      │
│  (parallel)     │ │   Analyzer      │ │    Analyzer     │
│                 │ │  (parallel)     │ │   (parallel)    │
└────────┬────────┘ └────────┬────────┘ └────────┬────────┘
         │                   │                   │
         └───────────────────┼───────────────────┘
                             ▼
                    ┌─────────────────┐
                    │   Synthesizer   │
                    │   (sequential)  │
                    └────────┬────────┘
                             │
                             ▼
                    ┌─────────────────┐
                    │    Reviewer     │
                    │   (sequential)  │
                    └─────────────────┘

Process

Phase 1: Screenshot Collection

Gather all screenshots to analyze: 1. Read the screenshot file(s) provided by the user 2. For each screenshot, note the file path and any context provided 3. If multiple screenshots, determine if they are from the same product

Phase 2: Parallel Analysis

Launch THREE Task agents IN PARALLEL for each screenshot:

Agent 1: screenshot-ui-analyzer

Analyze this screenshot for UI components, layout structure, and design patterns.
Screenshot: [file path]
Return your analysis as JSON.

Agent 2: screenshot-interaction-analyzer

Analyze this screenshot for user interactions, navigation flows, and state transitions.
Screenshot: [file path]
Return your analysis as JSON.

Agent 3: screenshot-business-analyzer

Analyze this screenshot for business functions, data entities, and domain logic.
Screenshot: [file path]
Return your analysis as JSON.

IMPORTANT: Use the Task tool with THREE parallel calls in a single message to maximize efficiency.

Phase 3: Synthesis

After all parallel analyses complete, launch the synthesizer agent:

Agent 4: screenshot-synthesizer

Synthesize these analysis results into a unified development task list.

UI Analysis:
[paste UI analyzer result]

Interaction Analysis:
[paste Interaction analyzer result]

Business Analysis:
[paste Business analyzer result]

Product Name: [product name]
Output file: docs/plans/YYYY-MM-DD-<product>-features.md

Phase 4: Review

Launch the reviewer agent to validate the output:

Agent 5: screenshot-reviewer

Review this task list for completeness and quality.

Original screenshot(s): [file paths]
Task list: [synthesized output]

If issues found, provide corrections.

Phase 5: Output

1. Write final task list to docs/plans/YYYY-MM-DD-<product>-features.md 2. Use format from references/output-format.md 3. Present summary to user

Key Guidelines

  • Use - [ ] checkbox format for all tasks
  • Break features into small, executable subtasks
  • Focus on user interactions, not implementation details
  • For multiple screenshots: deduplicate features across all screens
  • For competitive analysis: highlight unique features and gaps

Benefits of Multi-Agent Approach

1. Thoroughness - Three specialized perspectives catch more details 2. Speed - Parallel analysis reduces total time 3. Quality - Synthesis + Review ensures coherent, complete output 4. Specialization - Each agent focuses on its domain expertise

Related skills

How it compares

Use screenshot-feature-extractor for quick screenshot-to-spec workflows; use Figma-to-code tools when you have structured design files with tokens and components already defined.

FAQ

What does screenshot-feature-extractor output?

screenshot-feature-extractor analyzes UI screenshots and outputs structured feature lists plus implementation prompts tailored for Claude Code or Cursor—giving agents concrete UI requirements without manual spec writing.

How popular is screenshot-feature-extractor?

screenshot-feature-extractor from davila7/claude-code-templates has 480 installs and ranks 29 on skills.sh, making it a frequently used skill for screenshot-driven UI spec generation.

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