literature-engineer

What problem does it solve?

This Skill addresses the challenge of building a comprehensive and verifiable collection of research papers, essential for evidence-first literature surveys, by automating the expansion and normalization of metadata.

Core Features & Use Cases

• Multi-route Literature Expansion: Gathers papers from various sources, including offline imports and online APIs (arXiv, Semantic Scholar).
• Metadata Normalization: Ensures stable IDs (arXiv, DOI) and provenance tracking for each paper.
• Snowballing: Expands the paper pool by following citation links.
• Use Case: When starting a literature survey, this Skill can ingest initial seed papers and automatically find hundreds or thousands of related works, ensuring each has a unique identifier and its source is recorded, preparing a robust dataset for further analysis.

Quick Start

Use the literature-engineer skill to expand the literature pool using the provided queries.md file.