pdf

Extract text and structured data from PDF documents using pypdf and pdfplumber.

Updated Nov 3, 2025
One-click install
npx skills add https://github.com/edmar/dap-client --skill pdf-edmar
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: pdf
Source: https://github.com/edmar/dap-client/tree/main/.claude/skills/pdf
Command: npx skills add https://github.com/edmar/dap-client --skill pdf-edmar

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires pypdf, pdfplumber, pdf2image, pytesseract, reportlab, and includes scripts (resource) and references (resource) components.

What problem does it solve?

This Skill eliminates the tedious manual work of filling out PDF forms and extracting data from documents, saving you hours of repetitive effort.

Core Features & Use Cases

  • Automated Form Filling: Programmatically fill both fillable and non-fillable PDF forms.
  • Data Extraction: Pull text and structured table data from any PDF into usable formats.
  • Use Case: Imagine you have 100 vendor invoices in PDF format. Use this Skill to automatically extract the invoice number, date, and total amount from each one and compile them into a single CSV file.

Quick Start

Use the pdf skill to extract all text from the attached file 'invoice-q3.pdf'.

Frequently Asked Questions about pdf

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

FAQPage Schema
How do I extract structured table data from PDF invoices into a CSV file?

PDF data extraction pulls structured table data and text from binary PDF streams using pdfplumber and pypdf. It parses invoice numbers, dates, and total amounts from multiple documents, compiling them into a single usable CSV file automatically.

Can I automate PDF form filling for non-fillable documents?

Automated PDF form filling programmatically populates both fillable and non-fillable forms. It eliminates tedious manual data entry by applying Python scripts to overlay data onto static PDF documents without manual intervention.

What's the best way to digitize archived PDF documents for data retrieval?

Archival data retrieval from PDF documents uses pytesseract and pdf2image to process scanned images into text. This workflow applies OCR technology to digitize archived files, extracting structured data for administrative processing.

Does pdfplumber work with pypdf to parse text from binary PDF streams?

Yes, pdfplumber works with pypdf to parse binary PDF streams for text extraction. Both Python libraries are required dependencies that process PDF documents without manual intervention, pulling usable text and structured table data.

How do I process hundreds of vendor invoices in PDF format without manual data entry?

Processing vendor invoices in PDF format uses Python automation to extract invoice numbers, dates, and amounts from hundreds of files. It parses binary PDF streams automatically, compiling structured data into a consolidated CSV file.

What are the limitations of using Python for PDF form digitization?

Limitations of Python PDF form digitization include handling complex layouts and scanned images, requiring OCR via pytesseract and pdf2image. It parses binary PDF streams but may need manual verification for poorly structured documents.