Does it support filling out PDF forms?

Yes, it includes guidance for programmatically filling out PDF forms using specialized libraries like pdf-lib or pypdf's form-handling capabilities.

Which Python libraries are recommended for text extraction?

For basic text extraction, pypdf is efficient; however, for complex layouts and table extraction, pdfplumber is recommended for its high accuracy and structure-aware processing.

How do I merge multiple PDF files using this skill?

The skill utilizes the pypdf PdfWriter or the qpdf command-line tool to merge multiple source documents into a single output file efficiently.

Can this skill help with scanned PDF documents?

Yes, it provides implementation patterns using pytesseract and pdf2image to convert scanned images into searchable and extractable text via OCR.

Is it possible to password-protect documents?

Yes, the toolkit includes methods for encrypting PDFs with user and owner passwords using the pypdf library.

PDF Processing Toolkit

Name: PDF Processing Toolkit
Author: RebelPotato

byRebelPotato

Productivity & Workflow

Manipulates, generates, and extracts data from PDF documents using a comprehensive suite of Python libraries and command-line tools.

About

The PDF Processing Toolkit skill empowers Claude to perform advanced document operations with precision. It provides standardized patterns for text and table extraction using pdfplumber, document manipulation (merging, splitting, rotating) via pypdf, and programmatic PDF generation using ReportLab. Additionally, the skill includes guidance for OCR on scanned documents, password protection, and high-performance command-line processing with tools like qpdf and poppler-utils, making it an essential resource for automating document workflows and data extraction pipelines.

Key Features

Comprehensive document manipulation including merging, splitting, and rotating
Dynamic PDF report and document generation using ReportLab and Platypus
High-accuracy text and tabular data extraction with pdfplumber
CLI integration for batch processing using qpdf and poppler-utils
0 GitHub stars
OCR capabilities for converting scanned PDFs into machine-readable text

Use Cases

Building automated workflows for merging, splitting, and watermarking document batches
Automating the extraction of structured data from financial statements or invoices
Generating dynamic PDF reports and certificates from application data

About

Key Features

Comprehensive document manipulation including merging, splitting, and rotating
Dynamic PDF report and document generation using ReportLab and Platypus
High-accuracy text and tabular data extraction with pdfplumber
CLI integration for batch processing using qpdf and poppler-utils
0 GitHub stars
OCR capabilities for converting scanned PDFs into machine-readable text

Use Cases

Building automated workflows for merging, splitting, and watermarking document batches
Automating the extraction of structured data from financial statements or invoices
Generating dynamic PDF reports and certificates from application data