Can I add watermarks or protect PDFs with passwords?

Yes, there are dedicated snippets for merging watermark layers onto existing pages and encrypting documents with user or owner passwords.

Is it possible to automate PDF merging and splitting?

Absolutely. The toolkit provides both Python code via pypdf and command-line instructions using qpdf and pdftk for efficient document manipulation.

Can I extract tables from complex PDF layouts?

Yes, the skill includes specific implementation patterns for using pdfplumber to extract tables and convert them into structured Pandas DataFrames.

Which Python libraries are supported by this skill?

The skill provides guidance and code snippets for pypdf, pdfplumber, reportlab, pytesseract, and various command-line tools like qpdf.

How does this skill handle scanned PDFs without selectable text?

It includes an OCR section that demonstrates how to use pdf2image and pytesseract to convert PDF pages into images and perform optical character recognition.

PDF Processing Toolkit

Name: PDF Processing Toolkit
Author: Microck

byMicrock

•

데이터 과학 및 ML

Simplifies PDF manipulation, data extraction, and document generation using industry-standard Python libraries and CLI tools.

소개

The PDF Processing Toolkit for Claude Code provides a comprehensive suite of implementation patterns for programmatic document handling. It enables developers to extract plain text and structured tables, merge or split documents, and generate professional PDFs from scratch using ReportLab. This skill is particularly useful for building data pipelines that ingest PDF content, automating the creation of dynamic reports, and managing document security or metadata. With support for OCR workflows and command-line utilities like qpdf, it bridges the gap between raw document files and actionable data within your development environment.

주요 기능

Document security features like encryption and password protection
File manipulation including merging, splitting, and page rotation
81 GitHub stars
Text and structured table extraction using pdfplumber
OCR capabilities for processing scanned documents with pytesseract
Programmatic PDF generation and multi-page report creation

사용 사례

Batch processing legacy document archives for searchable text indexing
Automating the extraction of financial data from PDF statements into DataFrames
Generating dynamic invoices, certificates, or business reports from application data

소개

주요 기능

Document security features like encryption and password protection
File manipulation including merging, splitting, and page rotation
81 GitHub stars
Text and structured table extraction using pdfplumber
OCR capabilities for processing scanned documents with pytesseract
Programmatic PDF generation and multi-page report creation

사용 사례

Batch processing legacy document archives for searchable text indexing
Automating the extraction of financial data from PDF statements into DataFrames
Generating dynamic invoices, certificates, or business reports from application data