| 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 referencesfigures/ - 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 fileoutput_folder - Directory where output will be saved
Optional arguments:
--image-resolution-scale F - Scale factor for extracted images (default: 2.0)
Examples:
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.
