Adobe Illustrator File Analyzer

Extract comprehensive design information from Adobe Illustrator (.ai) files including text, fonts, colors, and visual previews.

When to Use This Skill

Use this skill when:

• Analyzing existing logo files (.ai) to understand design elements
• Extracting brand colors from design files
• Identifying fonts used in artwork
• Generating preview images from Illustrator files without opening Adobe Illustrator
• Understanding the structure and content of .ai files for design decisions
• Preparing design specifications or style guides from source files

How It Works

Adobe Illustrator files (.ai) have been PDF-based since Creative Suite versions. This means .ai files can be read and analyzed using PDF processing libraries like PyMuPDF, without requiring Adobe Illustrator itself.

The analyzer extracts:

1. Text content - All text elements and labels
2. Font information - Font families and sizes used
3. Color palette - All colors with usage frequency
4. Preview images - High-resolution PNG previews (300 DPI)
5. Metadata - Artboard dimensions, creation info
6. Design complexity - Vector paths, images, structure

Quick Start

Install Dependencies

pip install pymupdf pillow

Analyze AI File

python scripts/analyze_ai_file.py <path/to/logo.ai> --output-dir ./analysis

Output Structure

The script creates the following output:

analysis/
├── analysis_report.md      # Human-readable summary
├── analysis_data.json      # Complete structured data
└── previews/               # High-resolution previews
    ├── artboard_1_preview.png
    ├── artboard_2_preview.png
    └── ...

Usage in Claude Code

When a user provides an .ai file for analysis:

1. Check dependencies: Verify PyMuPDF and Pillow are installed
2. Run analyzer: Execute scripts/analyze_ai_file.py with the .ai file path
3. Review outputs: Read the markdown report and JSON data
4. Analyze previews: Inspect generated preview images
5. Extract insights: Identify key design elements for decision-making

Example workflow:

# Step 1: Analyze the AI file
python scripts/analyze_ai_file.py "existing_logo.ai" --output-dir ./logo_analysis

# Step 2: Read the summary report
cat ./logo_analysis/analysis_report.md

# Step 3: Check the color palette
cat ./logo_analysis/analysis_data.json | grep -A 10 '"colors"'

# Step 4: View preview images
ls ./logo_analysis/previews/

Extracted Information

Text Content

• All text elements from all artboards
• Unique text strings (brand names, slogans, etc.)
• Text organized by artboard

Example output:

{
  "unique_texts": ["COMPANY NAME", "Est. 2022", "Quality Products"],
  "total_text_elements": 5
}

Font Information

• Font family names
• Font sizes used
• All unique font/size combinations

Example output:

[
  ["Helvetica-Bold", 48.0],
  ["Arial-Regular", 12.0],
  ["CustomFont-Light", 24.0]
]

Color Palette

• Hex color codes (#RRGGBB)
• Usage frequency for each color
• Sorted by most-used colors first

Example output:

[
  {"color": "#000000", "occurrences": 25},
  {"color": "#ff6600", "occurrences": 12},
  {"color": "#ffffff", "occurrences": 8}
]

Artboard Dimensions

• Width and height in points (pt)
• Width and height in millimeters (mm)
• Rotation angle
• Image count

Example output:

{
  "artboard_number": 1,
  "width": 612.0,
  "height": 792.0,
  "width_mm": 216.0,
  "height_mm": 279.4
}

Preview Images

• PNG format with transparency
• 300 DPI resolution (print-quality)
• One image per artboard

Advanced Features

High-Resolution Previews

The analyzer generates 300 DPI previews, suitable for:

• Print quality inspection
• Design presentations
• Web mockups
• Client presentations

Color Frequency Analysis

Colors are ranked by usage, helping identify:

• Primary brand colors (most used)
• Accent colors (less frequent)
• Unused colors in palette

Design Complexity Score

The analyzer calculates complexity based on:

• Number of vector paths
• Number of text elements
• Number of embedded images

Higher scores indicate more complex designs.

Integration with Logo Design Workflows

Analyzing Existing Brand Logos

When creating a new logo based on existing brand assets:

1. Extract brand colors:

   python scripts/analyze_ai_file.py "old_logo.ai" --output-dir ./brand_analysis
   # Review analysis_data.json for color palette
   

2. Identify typography:

   # Check fonts section in analysis_report.md
   cat ./brand_analysis/analysis_report.md | grep -A 20 "## Fonts Used"
   

3. Review design elements:

   # View preview images
   open ./brand_analysis/previews/artboard_1_preview.png
   

4. Use findings for new design:

   • Maintain brand colors from palette
   • Consider existing typography style
   • Reference design complexity level

Brand Guidelines Extraction

For logo design contests requiring brand adherence:

1. Analyze existing logo file
2. Extract official brand colors → Use in new design
3. Identify font styles → Match typography approach
4. Review design simplicity → Maintain brand consistency

Troubleshooting

File Not Recognized

If the analyzer fails to open the .ai file:

# Verify file integrity
file logo.ai

# Check if it's truly a PDF-based AI file
pymupdf logo.ai

Older .ai files (pre-CS) may use EPS format and require conversion.

Missing Color Information

If few colors are detected:

• Colors may be defined as vector fill/stroke (not text)
• Consider manual inspection of preview images
• Some colors might be in embedded images

Large File Size

For very large .ai files (>50MB):

• Processing may take longer
• Preview generation is memory-intensive
• Consider processing individual artboards

Technical Details

Why PyMuPDF?

PyMuPDF (fitz) is ideal for .ai files because:

• ⚡ Fast performance (C++ backend)
• 📄 Native PDF handling (AI files are PDF-based)
• 🖼️ High-quality image rendering
• 💾 Low memory footprint
• 🔧 No external dependencies (like Ghostscript)

AI File Format Background

Since Adobe Creative Suite (CS):

• .ai files contain embedded PDF
• PDF portion is readable by standard PDF tools
• Proprietary AI data is in separate layer
• PyMuPDF accesses the PDF layer

Limitations

What the analyzer can extract:

• ✅ Text content and fonts
• ✅ Basic color information
• ✅ Artboard dimensions
• ✅ Visual previews (raster)
• ✅ Embedded images

What the analyzer cannot extract:

• ❌ Editable vector paths (proprietary format)
• ❌ Layer structure (AI-specific)
• ❌ Blend modes and effects (AI-specific)
• ❌ Symbols and brushes (AI-specific)

For full editing capabilities, Adobe Illustrator is still required.

Example Outputs

Logo Analysis for Contest

# AI File Analysis Report

## File Information
- **Filename**: company_logo.ai
- **Artboards**: 2
- **Creator**: Adobe Illustrator 27.0
- **Created**: 2024-08-02

## Artboards
### Artboard 1
- **Dimensions**: 500x500 pt (176.39x176.39 mm)
- **Images**: 0

### Artboard 2
- **Dimensions**: 1000x300 pt (352.78x105.83 mm)
- **Images**: 1

## Text Content
1. COMPANY NAME
2. Innovation Through Technology

## Fonts Used
- Montserrat-Bold (48.0pt)
- Montserrat-Regular (18.0pt)

## Color Palette
- `#1a1a1a` (used 15 times)
- `#ff6b35` (used 8 times)
- `#ffffff` (used 5 times)

## Design Analysis
- **Contains text**: Yes
- **Contains images**: Yes
- **Contains vector paths**: Yes
- **Complexity score**: 127

Integration Tips

For Logo Design Projects

After analyzing an existing brand logo:

1. Color consistency: Use extracted hex codes in design tools
2. Typography reference: Match font style and weight
3. Size reference: Use artboard dimensions for aspect ratios
4. Visual comparison: Compare new designs against preview images

For Brand Guidelines

After analyzing design assets:

1. Document colors: Create palette from frequency data
2. Typography specs: List fonts with sizes and weights
3. Usage examples: Use preview images in guidelines
4. File specifications: Include dimension data

For Design Handoff

Before submitting final designs:

1. Analyze your own .ai file
2. Verify all required elements present
3. Check color consistency
4. Generate previews for review
5. Include analysis report with submission