Search 9 academic sources and output ranked candidate papers to candidates.csv.
npx skills add https://github.com/gy-hou/trendr --skill paper-scout
Please help me install this Agent Skill. Skill: paper-scout Source: https://github.com/gy-hou/trendr/tree/main/skills/paper-scout Command: npx skills add https://github.com/gy-hou/trendr --skill paper-scout
This Skill automates the discovery and screening of scholarly papers from multiple open sources, dramatically reducing manual triage time for literature reviews.
Run paper-scout to search for papers on your topic and output a ready-to-review candidates.csv.
High-intent search queries and answers about installing and using this skill.
You can search academic papers across arXiv, Semantic Scholar, OpenAlex, PubMed, CrossRef, DBLP, Europe PMC, bioRxiv, and Papers with Code simultaneously to assemble a ranked set of candidates for your literature review.
This Skill applies source-aware filtering and ranking across all 9 sources, including arXiv and PubMed, while robustly handling rate limits and error recovery to ensure complete search results.
The output is a ready-to-review candidates.csv structure containing deduplicated candidate papers with all necessary metadata fields for your research management workflow.
It manages rate limits and errors automatically across all 9 integrated academic sources, preventing incomplete data retrieval when scoping a topic for a literature review.
The generated candidates.csv includes lightweight metadata and relevance scores from sources like bioRxiv and Europe PMC, directly supporting rapid triage and decision-making for your research.
While it searches 9 open sources like Papers with Code and arXiv comprehensively, the final candidate set depends on each source's available metadata and current API availability.
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