Enhances academic paper metadata by extracting table of contents, conclusions, and abstracts using LLMs.
The Scholar Paper Enricher skill is a specialized tool for the Scholar All-In-One (scholaraio) research terminal that automates the deep analysis of academic papers. It utilizes Large Language Models to intelligently extract structural data such as the Table of Contents (TOC) and critical research conclusions, as well as backfilling missing abstracts through markdown parsing or DOI-based web fetching. This skill is ideal for researchers who need to transform a raw collection of PDFs into a structured, searchable, and highly informative digital library without manual data entry.
主な機能
01Inspection mode to debug and verify extraction details in real-time
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03LLM-driven conclusion (L3) extraction to highlight key research findings
04Intelligent abstract backfilling via markdown analysis or publisher DOI fetching
05Automated Table of Contents (TOC) extraction for better document navigation
06Batch processing support for entire libraries using the --all flag
ユースケース
01Repairing incomplete metadata records for papers imported from Zotero or EndNote
02Summarizing the main outcomes of multiple studies simultaneously for literature reviews
03Generating structured outlines for a large library of newly imported research papers
