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scanner-pdf-analysis

Extract text, tables, sections, and metadata from PDF documents.

1|Updated Nov 11, 2025
Search Tags:#analysis#metadata#OCR#PDF#tables#summaries#sections
One-click install
npx skills add https://github.com/takemi-ohama/ai-agent-marketplace --skill scanner-pdf-analysis
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: scanner-pdf-analysis
Source: https://github.com/takemi-ohama/ai-agent-marketplace/tree/main/plugins/ndf/skills/scanner-pdf-analysis
Command: npx skills add https://github.com/takemi-ohama/ai-agent-marketplace --skill scanner-pdf-analysis

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires PyPDF2, tabula-py, pdfplumber, and includes scripts (resource) components.

What problem does it solve?

Reading and extracting structured data from PDFs is time-consuming. This Skill provides text extraction (with OCR), table detection and CSV/JSON conversion, section/heading identification, key point summarization, and metadata extraction.

Core Features & Use Cases

  • Text extraction and OCR from PDF documents
  • Table detection and conversion to CSV/JSON
  • Section and heading identification for document structure
  • Key points summarization to capture essential insights
  • Metadata extraction like page count and creation date

Quick Start

Example: python scripts/analyze-pdf.py report.pdf --extract-tables --summarize

Frequently Asked Questions about scanner-pdf-analysis

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

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

Text and table extraction from PDFs uses OCR and table detection to pull structured data. This Skill automates text extraction with OCR capability, identifies tables within documents, and converts them to CSV or JSON format for further analysis or processing.

Can I extract tables from PDFs and convert them to CSV or JSON?▼

Yes. Table detection and conversion is a core feature that identifies tables in PDF documents and exports them directly to CSV or JSON formats, preserving structure and enabling downstream data analysis or integration with other tools.

What structured data can I pull from PDF documents?▼

Structured data extraction includes text content via OCR, detected tables, document sections and headings, metadata such as page count and creation date, and automatically generated summaries of key points—all extracted from a single PDF analysis pass.

How do I automatically summarize key points from PDFs?▼

Automatic summarization identifies and condenses essential insights from PDF content into concise key points. This reduces manual review time for technical documents, reports, and academic papers while preserving the most critical information.

Does PDF analysis work with scanned documents and OCR?▼

Yes. OCR-enabled text extraction handles both digital and scanned PDFs, converting image-based content into readable, searchable text so that tables, sections, and metadata can be extracted from any PDF source.

What metadata can I retrieve from PDF files?▼

Metadata extraction retrieves document-level information including page count, creation date, and other file properties. This metadata helps organize, filter, and contextualise documents within larger workflows or data pipelines.

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