pdf

Extract text and tables from PDF documents using Python libraries.

Updated Jan 11, 2026

Search Tags:#pdf #python #document-processing #text-extraction #table-extraction #data-automation

Ready to run

npx skills add https://github.com/ehoyos007/SKILL.md --skill pdf-ehoyos007

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: pdf
Source: https://github.com/ehoyos007/SKILL.md/tree/main/pdf
Command: npx skills add https://github.com/ehoyos007/SKILL.md --skill pdf-ehoyos007

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

PDF processing often requires manual, repetitive steps to extract text, pull tables, and generate new documents or fill forms. This skill provides a programmable toolkit to automate these tasks at scale.

Core Features & Use Cases

Extract text from PDFs using libraries such as pypdf and pdfplumber.
Extract tables and convert them into structured formats like CSV or Excel.
Create, merge, rotate, and fill forms in PDFs to automate document workflows.

Quick Start

Run a sample workflow to extract all text and tables from a PDF document and save the results to text and CSV files.

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 using Python?▼

To extract text and tables from PDF documents, this skill uses Python libraries like pypdf and pdfplumber to parse content and save structured table data into formats such as CSV or Excel files.

Can I automate PDF form filling and document generation programmatically?▼

Yes, you can automate PDF form filling and document generation programmatically using the reportlab library to create, merge, rotate, and fill forms within your document workflows.

What is the best way to convert PDF tables into structured CSV files?▼

The best way to convert PDF tables into structured CSV files is using pdfplumber for table extraction, which identifies tabular data and exports it directly into structured formats for analysis.

Does this PDF extraction approach work for archival data management and document analysis?▼

Yes, this PDF extraction approach works for archival data management and document analysis by programmatically reading and parsing text to automate repetitive data extraction tasks at scale.

Do I need any specific Python libraries to parse PDFs and extract tables?▼

You need Python libraries like pypdf, pdfplumber, and reportlab to parse PDFs and extract tables, as these dependencies handle text reading, table parsing, and document manipulation respectively.