docling-pdf

name	docling-pdf
version	1.0.0
description	Convert PDF documents to AI-accessible markdown format using IBM's Docling library. This skill should be used when the user needs to extract content from PDFs including text, figures, and tables in a structured markdown format. It handles scientific papers, technical documents, reports, and any PDF requiring content extraction for AI processing or analysis.

Docling PDF Converter

Overview

Convert PDF documents to structured markdown using IBM's Docling library. Extract complete document content including text, figures (as PNG files), and tables (as separate markdown files) in an AI-accessible format optimized for further processing and analysis.

When to Use This Skill

Use this skill when the user needs to:

• Convert PDFs to markdown for AI analysis
• Extract figures and tables from research papers or technical documents
• Process PDF content for documentation or knowledge base purposes
• Analyze document structure and content programmatically
• Extract text from complex PDFs while preserving formatting

Quick Start

Convert a PDF using the bundled script:

uv run --python 3.10 scripts/convert_pdf.py input.pdf output_folder

This produces:

• full_document.md - Complete markdown with cleaned references
• figures/ - Numbered PNG files (figure_001.png, figure_002.png, etc.)
• tables/ - Individual markdown tables (table_001.md, table_002.md, etc.)
• metadata.json - Document statistics and conversion timing

Conversion Process

Step 1: Prepare the Environment

The script uses uv to manage dependencies automatically. No manual installation required. The script's inline metadata specifies all required packages.

Step 2: Execute Conversion

Run the conversion script with the following syntax:

uv run --python 3.10 scripts/convert_pdf.py <pdf_file> <output_folder> [options]

Required arguments:

• pdf_file - Path to the input PDF file
• output_folder - Directory where output will be saved

Optional arguments:

• --image-resolution-scale F - Scale factor for extracted images (default: 2.0)

Examples:

# Basic conversion
uv run --python 3.10 scripts/convert_pdf.py paper.pdf output/

Step 3: Process Output

The conversion creates a structured output directory:

output_folder/
├── full_document.md     # Complete markdown (cleaned references)
├── figures/             # PNG images
│   ├── figure_001.png
│   ├── figure_002.png
│   └── ...
├── tables/              # Markdown tables
│   ├── table_001.md
│   ├── table_002.md
│   └── ...
└── metadata.json        # Conversion statistics

Key features:

• Figure references in markdown are automatically updated to point to figures/ directory
• Tables are exported as DataFrames converted to markdown format
• Original artifacts folders are cleaned up automatically
• Metadata includes page count, timing, figure/table counts

Script Details

The scripts/convert_pdf.py script is a standalone Python script with inline dependencies that:

Important: The script is designed to be run with uv run which handles environment creation and dependency management automatically. Do not try to run it directly with python3 without first installing dependencies.