Can this skill handle scanned PDF documents?

Yes, it provides implementation patterns for OCR (Optical Character Recognition) using pytesseract and pdf2image to process scanned files.

How do I extract tables from a PDF using this skill?

The skill includes specialized patterns using pdfplumber's extract_tables() method to automatically detect and structure data from PDF pages.

Which Python libraries does this skill use for PDF tasks?

The skill primarily utilizes pdfplumber for precise text and table extraction and pypdf for document manipulation like merging and splitting.

Does this skill support merging multiple PDF files?

Yes, it includes optimized code snippets using the PdfMerger class from the pypdf library to combine multiple documents into one.

PDF Document Processing

Name: PDF Document Processing
Author: Activer007

byActiver007

Content Management

Automates the extraction, manipulation, and management of PDF documents using specialized Python libraries.

About

This skill equips Claude with the capability to programmatically handle PDF files, enabling complex tasks such as high-fidelity text and table extraction, document merging, and automated form filling. It provides optimized implementation patterns for industry-standard libraries like pdfplumber and pypdf, making it an essential tool for developers building document processing pipelines, data extraction scripts, or automated reporting systems.

Key Features

OCR integration for extracting content from scanned or image-based PDFs
Robust error handling for empty pages and unextractable text elements
Automated PDF form filling with field analysis and validation support
0 GitHub stars
Seamless document manipulation including merging and splitting page ranges
High-accuracy text and structured table extraction from complex layouts

Use Cases

Automating the batch-filling of corporate or legal forms from database records
Building document assembly tools that merge multiple PDF reports into a single file
Extracting financial data from PDF invoices and converting it into structured CSV formats

About

Key Features

OCR integration for extracting content from scanned or image-based PDFs
Robust error handling for empty pages and unextractable text elements
Automated PDF form filling with field analysis and validation support
0 GitHub stars
Seamless document manipulation including merging and splitting page ranges
High-accuracy text and structured table extraction from complex layouts

Use Cases

Automating the batch-filling of corporate or legal forms from database records
Building document assembly tools that merge multiple PDF reports into a single file
Extracting financial data from PDF invoices and converting it into structured CSV formats