Is it possible to generate new PDFs from scratch?

Yes, it includes detailed examples for using reportlab to create professional, multi-page documents with custom text, graphics, and layouts.

How does this help with large-scale document merging?

It provides efficient scripts to iterate through directories and merge multiple PDF files into a single document while maintaining specific page ordering and metadata.

Can I extract tables from PDFs into spreadsheets?

Yes, this skill provides implementation patterns using pdfplumber and pandas to extract complex tables and convert them into structured formats like Excel or DataFrames.

Does this support scanned images or non-selectable text?

Yes, it includes specialized guidance on using pytesseract and pdf2image to perform Optical Character Recognition (OCR) on scanned documents.

Can I password-protect my documents using this skill?

Absolutely, the toolkit provides methods using both Python (pypdf) and command-line tools (qpdf) to encrypt and decrypt PDF files securely.

PDF Power Toolkit

Name: PDF Power Toolkit
Author: Activer007

byActiver007

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Content Management

Automates PDF document processing including text extraction, table parsing, merging, splitting, and programmatic document creation.

About

The PDF Power Toolkit is a comprehensive suite for programmatic document management within Claude, enabling users to handle complex PDF workflows with ease. By leveraging industry-standard Python libraries such as pypdf and pdfplumber alongside powerful command-line utilities like qpdf, this skill allows for advanced text and table extraction, OCR for scanned documents, and the generation of custom reports. Whether you need to automate data entry from invoices, secure documents with passwords, or batch-process large archives, this skill provides the patterns and best practices required for efficient document analysis and manipulation.

Key Features

1 GitHub stars
High-fidelity text and table extraction with layout preservation
Programmatic PDF generation and report styling using reportlab
Bulk file manipulation including merging, splitting, and rotation
OCR capabilities to convert scanned images into searchable text
Advanced security features for encryption, decryption, and watermarking

Use Cases

Automating financial data extraction from PDF bank statements into structured spreadsheets
Generating dynamic invoices and business reports from application data via Python scripts
Batch-processing document archives to apply uniform watermarks and security permissions

About

Key Features

1 GitHub stars
High-fidelity text and table extraction with layout preservation
Programmatic PDF generation and report styling using reportlab
Bulk file manipulation including merging, splitting, and rotation
OCR capabilities to convert scanned images into searchable text
Advanced security features for encryption, decryption, and watermarking

Use Cases

Automating financial data extraction from PDF bank statements into structured spreadsheets
Generating dynamic invoices and business reports from application data via Python scripts
Batch-processing document archives to apply uniform watermarks and security permissions