pdf

Name: pdf
Availability: InStock
Author: rafaelcostaf4-afk

Extract text and tables from PDFs into Markdown-ready chunks.

Updated Mar 23, 2026

Search Tags:#ocr #pdf #chunking #data-extraction #text-extraction #table-extraction #qa-pipeline

Ready to run

npx skills add https://github.com/rafaelcostaf4-afk/SurveyHub --skill pdf-rafaelcostaf4-afk

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: pdf
Source: https://github.com/rafaelcostaf4-afk/SurveyHub/tree/main/.claude/skills/pdf
Command: npx skills add https://github.com/rafaelcostaf4-afk/SurveyHub --skill pdf-rafaelcostaf4-afk

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

PDF data extraction and processing across ingestion pipelines: converting complex documents into actionable, machine-readable data.

Core Features & Use Cases

PDF to text and structured data: extract text and tables from PDFs for downstream analytics.
PDF workflow automation: support for splitting, merging, and chunking documents for QA pipelines (ADR-014).
OCR fallback and tooling guidance: recommendations for tesseract and image-based extractions when needed.

Quick Start

Process a sample.pdf to markdown-ready text using the built-in PDF pipeline.

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 pipelines?▼

To convert PDFs to markdown, you process the document through a pipeline that parses content into markdown-ready chunks. This transforms complex documents into actionable, machine-readable text for ingestion workflows.

Can I use pdfplumber and pymupdf together for structured data extraction?▼

Yes, the extraction pipeline utilizes pdfplumber and pymupdf together to parse complex documents. This combination enables comprehensive text and table extraction from PDFs for downstream analytics processing.

What is the best way to chunk PDF content for a QA pipeline?▼

The best way to chunk PDF content for a QA pipeline involves automated splitting and merging to generate markdown-ready chunks. This workflow prepares complex documents for efficient question-answering ingestion.

Do I need tesseract OCR for image-based PDF text extraction?▼

You need tesseract OCR for image-based PDF text extraction when standard parsing fails to capture content. The pipeline provides OCR fallback recommendations and tooling guidance for handling image-heavy documents.

Does this PDF data extraction approach support report generation?▼

Yes, this PDF data extraction approach supports report generation across research pipelines. It extracts text and tables from complex documents, converting them into structured data necessary for generating analytical reports.