Agent skill

review-design

Multi-provider AI design review of UI screenshots and design tokens for UX audits.

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Forks 31

Install this agent skill to your Project

npx add-skill https://github.com/majiayu000/claude-skill-registry/tree/main/skills/other/other/review-design

Metadata

Additional technical details for this skill

short description
Vision-driven UX design review

SKILL.md

review-design

Multi-provider AI design review skill. Submits UI screenshots + design tokens to vision-capable LLMs for structured UX audits.

Triggers

  • review design
  • design review
  • UX audit
  • audit this UI
  • review this UI
  • review the design
  • critique this design
  • compare to raycast
  • design comparison
  • visual review
  • UI review
  • check the UX
  • assess the design
  • design feedback

Description

Iterative 3-step design review pipeline inspired by review-code:

  1. Audit - Analyze screenshots against design tokens + reference images, identify gaps
  2. Judge - Critique the audit findings for accuracy and prioritization
  3. Finalize - Produce actionable recommendations with specific token/layout changes

Supports multiple vision-capable providers:

  • Claude (claude) - claude-sonnet-4-20250514 (vision)
  • OpenAI (openai) - gpt-4o (vision)
  • Gemini (gemini) - gemini-2.0-flash (vision)

Requirements

Screenshots are MANDATORY. This skill will fail if no screenshots are provided. A design review without visual evidence is impossible — it would be pure speculation.

Capture screenshots before running a review:

  • /surf snap — Browser screenshot via CDP
  • /surf-qml — QML/Qt app screenshot via AT-SPI
  • flameshot full --path ./screenshots/current.png — System screenshot

The --screenshots directory must contain at least one PNG/JPG image.

Usage

bash
# Basic design review (single round)
./run.sh review --screenshots ./screenshots/ --tokens ./design-tokens.json

# With reference images (compare to target design)
./run.sh review --screenshots ./current/ --reference ./raycast/ --tokens ./tokens.json

# Multi-round iterative review (recommended)
./run.sh review-full --screenshots ./current/ --reference ./target/ --tokens ./tokens.json --rounds 2

# Specific provider
./run.sh review --provider claude --screenshots ./ui/

# Generate review request bundle (for manual submission)
./run.sh bundle --screenshots ./ui/ --tokens ./tokens.json --output review_request.md

Input Format

Design Tokens (JSON)

json
{
  "meta": { "name": "...", "description": "..." },
  "colors": { ... },
  "typography": { ... },
  "layout": { ... },
  "animation": { ... },
  "effects": { ... },
  "interactions": { ... }
}

Screenshots

  • PNG/JPG files in a directory
  • Named descriptively: full-launcher-empty.png, result-list-hover.png
  • Include both current UI and reference/target UI if comparing

Output Format

Per-Round Files (in review_output/)

roundN_step1.md      # Initial audit findings
roundN_step2.md      # Judge critique
roundN_final.md      # Finalized recommendations
roundN_audit.json    # Structured findings (machine-readable)

Audit JSON Structure

json
{
  "summary": "Overall assessment",
  "findings": [
    {
      "severity": "high|medium|low",
      "category": "color|typography|layout|spacing|animation|interaction",
      "element": "search-bar",
      "issue": "Description of the gap",
      "current": "Current value or behavior",
      "recommended": "Suggested fix",
      "token_change": { "path": "colors.text.primary", "from": "#fff", "to": "#f5f5f5" }
    }
  ],
  "token_changes": [ ... ],
  "praise": [ "Things done well" ]
}

Provider Capabilities

Provider Model Vision Cost Session
claude claude-sonnet-4-20250514 Yes Paid Yes
openai gpt-4o Yes Paid No
gemini gemini-2.0-flash Yes Free tier No

Commands

review - Single-round design audit

Basic audit with optional reference comparison.

review-full - Multi-round iterative audit (recommended)

Runs the 3-step pipeline for N rounds, each round refining findings.

bundle - Generate review request

Creates a markdown file with embedded images (base64) for manual submission to any LLM.

compare - Side-by-side comparison

Generates a visual comparison report between current and target design.

check - Verify provider access

Tests that the selected provider has vision capability and valid credentials.

Example Workflow

bash
# 1. Capture screenshots of your UI
flameshot full --path ./screenshots/current.png

# 2. Gather reference screenshots (e.g., Raycast)
cp ~/raycast-ref/*.png ./screenshots/reference/

# 3. Create/update design tokens
cat > design-tokens.json << 'EOF'
{ "colors": { ... }, "typography": { ... } }
EOF

# 4. Run iterative design review
./run.sh review-full \
  --screenshots ./screenshots/ \
  --reference ./screenshots/reference/ \
  --tokens ./design-tokens.json \
  --rounds 2 \
  --provider claude

# 5. Apply recommendations
# Read review_output/round2_final.md for actionable changes

Integration with review-code

After design review produces token changes, you can:

  1. Update your style files (QML, CSS, etc.) based on recommendations
  2. Run review-code to validate the implementation changes
  3. Iterate until both design and code reviews pass

Allowed Tools

  • Bash (for provider CLI invocation)
  • Read (for loading tokens and configs)
  • WebFetch (for fetching remote design specs)

Notes

  • Screenshots should be captured at 1x scale for consistent analysis
  • Include the full UI context (not just cropped elements) for better spatial reasoning
  • Reference images help but aren't required. However, screenshots ARE required — the skill will fail without them.
  • Large images are automatically resized to fit provider limits

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