Which Python libraries are recommended for PDF processing?

This skill focuses on using pypdf for basic operations (merging/splitting), pdfplumber for advanced table extraction, and reportlab for high-quality document generation.

Can this skill handle scanned PDFs without selectable text?

Yes, it includes patterns for OCR (Optical Character Recognition) using pytesseract and pdf2image to extract text from scanned pages.

Is it possible to fill out interactive PDF forms programmatically?

Yes, the skill provides specific implementation patterns for interacting with PDF form fields using specialized libraries like pdf-lib or pypdf.

How do I secure my PDF documents using this skill?

The skill includes commands and code snippets for encrypting PDFs with user/owner passwords and decrypting files using tools like qpdf and pypdf.

PDF Manipulation & Processing

Name: PDF Manipulation & Processing
Author: kivilaid

bykivilaid

•

Content Management

Manipulates and processes PDF documents programmatically through text extraction, document merging, and professional-grade file generation.

About

This Claude Code skill equips Claude with specialized knowledge for handling complex PDF tasks using industry-standard Python libraries and command-line tools. Whether you need to extract structured table data from financial reports, automate the generation of custom documents with ReportLab, merge/split files with qpdf, or perform OCR on scanned documents, this skill provides the implementation patterns and best practices required to process PDFs at scale. It covers everything from basic metadata extraction to advanced form handling and layout preservation, making it an essential tool for document-heavy automation workflows.

Key Features

Security features for document encryption and password protection
Automated PDF generation and multi-page document creation using ReportLab
Advanced document operations including merging, splitting, and rotating pages
OCR capabilities for converting scanned documents into searchable text
6 GitHub stars
Comprehensive text and table extraction with layout preservation

Use Cases

Automating the extraction of tabular data from financial statements into Excel or CSV
Building automated document generation pipelines for custom invoices, reports, or certificates
Programmatically merging multiple source documents into a single cohesive PDF for distribution

About

Key Features

Security features for document encryption and password protection
Automated PDF generation and multi-page document creation using ReportLab
Advanced document operations including merging, splitting, and rotating pages
OCR capabilities for converting scanned documents into searchable text
6 GitHub stars
Comprehensive text and table extraction with layout preservation

Use Cases

Automating the extraction of tabular data from financial statements into Excel or CSV
Building automated document generation pipelines for custom invoices, reports, or certificates
Programmatically merging multiple source documents into a single cohesive PDF for distribution