What problem does it solve?
paper-extraction removes the burden of manually downloading a paper and re-parsing PDFs/LaTeX to find figures, tables, section structure, and citation metadata, by producing a standardized directory with both structural and semantic surfaces.
Core Features & Use Cases
- Standardized paper substrate: Converts an arXiv ID or DOI into a predictable
work/reference/ layout containing the paper PDF plus either arXiv LaTeX source artifacts (primary) or a Docling-derived fallback surface.
- Structural index for fast navigation: Emits
work/reference/index.json with figures, tables (as per-table .tex files on the LaTeX path), section outline with line numbers, and a citations map including resolved DOIs and full citation text when available.
- ASTRA-shaped semantic representation: Writes
work/reference/astra.yaml as a valid ASTRA artifact stub, ready for follow-on findings population with evidence-anchored quotes.
- Use Case: Prepare a reliable, shareable reading surface before deeper analysis, so other workflows can consume figures/tables/citations without re-grepping LaTeX or re-wrangling PDFs.
Quick Start
Ask the agent to run paper-extraction for a paper by providing its arXiv ID or DOI, so you get a ready-to-consume work/reference/ directory with index.json and astra.yaml.