paper-lit-search

To search for academic papers across multiple sources, this Skill applies multi-source queries across arXiv, Semantic Scholar, and your local library simultaneously. It automatically deduplicates and ranks the combined results by relevance, recency, and citations to streamline your literature review.

The best way to deduplicate and rank literature search results is using an automated multi-source query approach. This Skill evaluates relevance, recency, citations, and project alignment to surface the most valuable papers, eliminating manual error-prone deduplication efforts across different academic databases.

To save literature search results, the Skill automatically generates a search artifact at resources/papers/searches/{YYYY-MM-DD}-{slug}.md. This markdown file captures your curated top hits and summarized metadata, providing a persistent record for tracking and review workflows.

Yes, you can include your local library when finding research papers. The Skill performs multi-source discovery by querying arXiv, Semantic Scholar, and the local library together, ensuring your existing local collection is integrated into the deduplication and ranking process.

Candidate papers are ranked by evaluating multiple dimensions including relevance, recency, citations, and project alignment. This ensures that the surfaced academic papers directly match your specific topic requirements, providing summarized top hits optimized for your current research goals.

Duplicate entries occur because arXiv and Semantic Scholar index overlapping academic papers. This Skill resolves the issue by applying automated deduplication across all queried sources, ranking the unique results by citations and recency to streamline your literature review.