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Shockwave2k
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pdf

Extract text, tables, metadata, and form data from PDFs.

Updated Apr 22, 2026
Search Tags:#automation#ocr#pdf#data-processing#text-extraction#form-filling#table-extraction
One-click install
npx skills add https://github.com/Shockwave2k/team-claude-skills --skill pdf-shockwave2k
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: pdf
Source: https://github.com/Shockwave2k/team-claude-skills/tree/main/skills/docs/pdf
Command: npx skills add https://github.com/Shockwave2k/team-claude-skills --skill pdf-shockwave2k

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires pypdf, pdfplumber, pdf2image, Pillow.

What problem does it solve?

PDFs are pervasive but extracting text, tables, metadata, and form data is tedious and error-prone, hindering data workflows and automation.

Core Features & Use Cases

  • Text and table extraction from PDFs, including metadata and embedded content.
  • PDF manipulation: merge, split, rotate, watermark, and OCR for searchable text.
  • Form handling: auto-fill both fillable and non-fillable forms and automate document workflows.

Quick Start

Process your first PDF to extract text, tables, or fill a form with a single command.

Frequently Asked Questions about pdf

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I extract text and tables from PDF documents for data processing?▼

PDF text and table extraction automates pulling structured content from PDFs using libraries like pypdf and pdfplumber, returning actionable data for finance, legal, and operations workflows. It handles metadata and embedded content seamlessly.

Can I automate filling out both fillable and non-fillable PDF forms?▼

Automated PDF form filling supports both fillable and non-fillable forms with robust field validation. It applies clear fallbacks for non-fillable documents to ensure accurate data entry across document workflows.

What's the best way to process scanned PDFs that need searchable text?▼

OCR for searchable text converts scanned PDFs into searchable documents using pdf2image and Pillow. This process applies optical character recognition to extract text from images embedded within PDF files.

Does this PDF automation approach work for merging, splitting, and watermarking documents?▼

PDF manipulation handles merging, splitting, rotating, and watermarking documents comprehensively. It supports multi-library integration to automate document manipulation tasks across archival and data workflows.

What are the limitations when extracting tables from complex PDF files?▼

PDF table extraction limitations depend on document structure and formatting complexity. Multi-library support with pypdf and pdfplumber provides fallbacks, but highly irregular or image-based tables may require OCR preprocessing.

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