grobid-pdf-parsing

npx skills add brycewang-stanford/Auto-Empirical-Research-Skills --skill grobid-pdf-parsing --agent claude-code

Same command for any agent — swap --agent for codex, cursor, copilot.

# GROBID PDF Parsing Guide ## Overview Academic PDFs are the primary format for distributing research, yet extracting structured data from them remains challenging. PDFs encode visual layout, not semantic structure -- headings, paragraphs, equations, tables, and citations are all just positioned text and graphics. GROBID (GeneRation Of BIbliographic Data) is the leading open-source tool for parsing academic PDFs into structured XML/TEI format, extracting metadata, body text, references, and figures with high accuracy. GROBID is used by major academic platforms including CORE, ResearchGate, and others for large-scale document processing. It combines machine learning models (CRF and deep learning) with heuristic rules to handle the diverse formatting of academic papers across publishers and disciplines. This guide covers installing and running GROBID, using its REST API for batch processing, extracting specific elements (metadata, references, body sections), and integrating GROBID output into downstream workflows such as knowledge bases, systematic reviews, and literature analysis pipelines. ## Installation ### Docker (Recommended) ```bash # Pull the latest GROBID image docker pull g

Pull the latest GROBID image
docker pull grobid/grobid:0.8.1
Run GROBID server
docker run --rm --init \
GROBID is now running at http://localhost:8070
Web console: http://localhost:8070/console
git clone https://github.com/kermitt2/grobid.git
cd grobid
Process a single PDF and get TEI XML
curl -v --form input=@paper.pdf \