Can I use this to password-protect my documents?

Yes, it provides Python code snippets using the pypdf library to encrypt documents with user and owner passwords.

Does this skill support command-line tools for faster processing?

Absolutely. It includes comprehensive guidance for using CLI utilities like qpdf, pdftk, and poppler-utils for efficient batch operations.

What is the best tool for extracting complex tables from PDFs?

This toolkit recommends and provides patterns for pdfplumber, which is superior for preserving table layouts and converting them into structured data like Excel or DataFrames.

Can this skill handle scanned PDFs that aren't text-searchable?

Yes, the skill includes specific implementations for OCR using pytesseract and pdf2image to extract text from image-based PDF documents.

PDF Processing Toolkit

Name: PDF Processing Toolkit
Author: pur3v4d3r

bypur3v4d3r

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Content Management

Manipulates and analyzes PDF documents programmatically through text extraction, document merging, report generation, and form filling.

About

This skill provides a comprehensive framework for automating complex PDF workflows directly within Claude. It equips the assistant with standardized patterns for high-fidelity text and table extraction using pdfplumber, document manipulation (merging, splitting, and rotating) via pypdf, and programmatic PDF creation using ReportLab. Additionally, it covers advanced scenarios such as OCR for scanned documents, password protection, and command-line processing with tools like qpdf and poppler-utils, making it an essential toolkit for developers handling document-heavy data pipelines.

Key Features

Programmatic PDF generation and multi-page report creation
Document assembly including merging, splitting, and page rotation
1 GitHub stars
High-fidelity text and table extraction with layout preservation
Security management including encryption and password decryption
OCR capabilities for converting scanned documents into searchable text

Use Cases

Building dynamic reporting engines that generate custom PDF documents at scale
Batch processing legacy scanned archives into searchable text-based repositories
Automating the extraction of tabular data from financial statements into Pandas DataFrames

About

Key Features

Programmatic PDF generation and multi-page report creation
Document assembly including merging, splitting, and page rotation
1 GitHub stars
High-fidelity text and table extraction with layout preservation
Security management including encryption and password decryption
OCR capabilities for converting scanned documents into searchable text

Use Cases

Building dynamic reporting engines that generate custom PDF documents at scale
Batch processing legacy scanned archives into searchable text-based repositories
Automating the extraction of tabular data from financial statements into Pandas DataFrames