AI File Analyzer

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