pdf

Automates PDF text, table extraction, and form filling for documents.

2|Updated Apr 15, 2026
One-click install
npx skills add https://github.com/mdnaimul22/human-skills --skill pdf-mdnaimul22
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: pdf
Source: https://github.com/mdnaimul22/human-skills/tree/main/skills/pdf
Command: npx skills add https://github.com/mdnaimul22/human-skills --skill pdf-mdnaimul22

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes scripts (resource) and references (resource) and assets (resource) components.

What problem does it solve?

This skill removes the time-consuming work of manually extracting text, tables, and form data from PDFs by giving you reliable, repeatable automation for common PDF tasks.

Core Features & Use Cases

  • Extract text and tables from PDFs (including layout-aware text and table extraction).
  • Create and transform PDFs by merging, splitting, rotating, watermarking, encrypting, and image extraction workflows.
  • Handle scanned PDFs with OCR to make image-only content searchable.
  • Fill PDF forms by detecting fillable fields or annotating non-fillable documents with correctly positioned text.

Quick Start

Tell the assistant: “Use the pdf skill to extract all text from my document.pdf and also extract any tables into structured output.”

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 a scanned PDF using OCR?

To extract text and tables from scanned PDFs, this solution uses OCR to make image-only content searchable, then applies layout-aware parsing to isolate and structure the extracted data into usable output.

What is the best way to automate PDF form filling for non-fillable documents?

Automating PDF form filling for non-fillable documents is achieved through coordinate-aware annotation, accurately positioning and overlaying text directly onto the PDF layout without requiring native fillable fields.

Can I merge, split, and transform PDFs programmatically in Python?

Yes, you can programmatically transform PDFs in Python to merge, split, rotate, watermark, and encrypt documents, providing reliable and repeatable automation for operational document workflows.

Does this PDF extraction approach work for both digitally generated and scanned files?

Yes, the PDF extraction approach works for both digitally generated PDFs and scanned files, utilizing direct text parsing for digital content and OCR rendering for scanned image-only documents.

What are the limitations of automated table extraction from PDF documents?

Automated table extraction from PDF documents depends heavily on layout clarity; complex or heavily merged cell structures may require coordinate-aware parsing adjustments to produce accurately structured output.