Can I extract tables from complex multi-page PDFs?

Yes, the skill includes specific code patterns for automatic table detection and extraction across multiple pages, which can then be exported to CSV or other formats.

How do I handle performance issues with very large PDF files?

The skill includes performance tips such as batch processing pages, utilizing multiprocessing, and extracting only necessary page ranges to minimize memory usage.

Can I use this skill to automate form filling?

Absolutely. It contains references and logic for field analysis, validation, and programmatic filling of interactive PDF forms.

Does this skill work with scanned PDF documents?

Yes, the skill provides guidance on using OCR tools like Tesseract to extract text from PDFs that contain images instead of selectable text.

Which Python libraries does this Claude skill support?

This skill provides implementation patterns for pdfplumber (extraction), pypdf (merging/splitting), pdf2image (conversion), and pytesseract (OCR).

PDF Processing & Data Extraction

Name: PDF Processing & Data Extraction
Author: Microck

byMicrock

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Productividad y Flujo de Trabajo

Automates text and table extraction, document merging, and form filling for PDF files using optimized Python patterns.

Acerca de

The PDF Processing skill empowers Claude to handle complex document tasks by providing optimized implementation patterns for text and table extraction, form filling, and structural PDF manipulation. It leverages industry-standard Python libraries like pdfplumber and pypdf to handle everything from simple text recovery to OCR for scanned documents. This skill is essential for developers building automated document workflows, data analysis pipelines, or administrative tools that require reliable PDF data recovery and structural modifications.

Características Principales

81 GitHub stars
Seamless document merging and page-specific splitting with pypdf.
Support for OCR (Optical Character Recognition) for scanned document processing.
High-accuracy text and structured table extraction using pdfplumber.
Automated PDF form filling and field validation capabilities.
Built-in error handling for empty pages, scanned files, and corrupted objects.

Casos de Uso

Converting financial reports and invoices into structured CSV or JSON data.
Automating the generation of filled corporate or legal forms from database inputs.
Batch processing large document libraries for searchable text archival and analysis.

Acerca de

Características Principales

81 GitHub stars
Seamless document merging and page-specific splitting with pypdf.
Support for OCR (Optical Character Recognition) for scanned document processing.
High-accuracy text and structured table extraction using pdfplumber.
Automated PDF form filling and field validation capabilities.
Built-in error handling for empty pages, scanned files, and corrupted objects.

Casos de Uso

Converting financial reports and invoices into structured CSV or JSON data.
Automating the generation of filled corporate or legal forms from database inputs.
Batch processing large document libraries for searchable text archival and analysis.