PDF Smart Split

PDF Smart Split Skill

Split multi-page scanned PDF documents into separate files based on content analysis. Supports duplicate detection, page reordering, and intelligent naming.

Workflow

1. PDF to Images

from pdf2image import convert_from_path
images = convert_from_path(pdf_path, dpi=200, thread_count=4)

• DPI=200 for quality
• Multi-threading for speed

2. Duplicate Detection

import hashlib
def get_image_hash(path):
    with open(path, 'rb') as f:
        return hashlib.md5(f.read()).hexdigest()

• Use MD5 hash comparison
• Record duplicates for summary

3. Content Analysis and Naming

Use view_file tool to analyze each image:

• File type (cover, content, signature page)
• Document category (application, agreement, statement)
• Page sequence number

Naming format: sequence_filetype_description.jpg

4. Page Reordering

Analyze content continuity:

• Check table sequence numbers
• Check chapter numbering progression
• Ensure signature pages follow content

Reorder by logical content, not physical order.

5. Merge Images to PDF

from PIL import Image
def images_to_pdf(image_paths, output_pdf):
    images = [Image.open(p).convert('RGB') for p in image_paths]
    images[0].save(output_pdf, "PDF", save_all=True, append_images=images[1:])

• Merge signature pages with their content
• Combine continuous content into single files

6. Generate Summary

Summary should include:

• Source file info (name, original pages)
• Duplicate removal records (if any)
• Page reorder records (if any)
• Split file list (name, original pages, page count, description)
• Output directory paths

Script Usage

Full Processing

python scripts/convert_dedup.py <pdf_path> [output_dir]
python scripts/merge_images.py <image1> <image2> ... <output.pdf>

Output Structure

filename_images/     # Intelligently named images
filename_split_PDF/  # Content-grouped PDFs

Requirements

• Install: pdf2image, Pillow
• Windows needs poppler: conda install -c conda-forge poppler