Query ten scholarly databases in parallel and return structured paper metadata.
npx skills add https://github.com/aleph23/Natasha --skill paper-lookup-aleph23
Please help me install this Agent Skill. Skill: paper-lookup Source: https://github.com/aleph23/Natasha/tree/main/skills/paper-lookup Command: npx skills add https://github.com/aleph23/Natasha --skill paper-lookup-aleph23
Researchers often need to locate scholarly papers across multiple databases, verify metadata, DOIs/PMIDs, and OA/full-text availability. This skill provides a unified workflow to query biomedical and multidisciplinary databases, gather results, and present raw responses along with source databases. It aims to streamline comprehensive literature discovery, citation checks, and open-access verification.
Ask me to search for papers on a topic and I will fetch results from PubMed, PMC, OpenAlex, Crossref, arXiv, bioRxiv/medRxiv, Semantic Scholar, and Unpaywall in parallel and return structured metadata.
High-intent search queries and answers about installing and using this skill.
Searching for scholarly papers across multiple databases is done by running parallel queries against ten sources including PubMed, OpenAlex, Crossref, arXiv, bioRxiv, medRxiv, Semantic Scholar, and Unpaywall to return consolidated structured metadata for your topic.
Yes, DOI and PMID lookups retrieve open access status and surface direct OA PDF or full-text links by querying databases like Unpaywall alongside metadata sources, returning both citation details and open access availability.
The best way to verify open access availability for academic articles is to query Unpaywall and other scholarly databases in parallel, which identifies OA PDFs, full texts, and surfaces direct open access links when available.
Consolidating metadata like authors, publication venues, and dates from different scholarly sources is achieved by applying database-specific search strategies across ten databases in parallel and returning structured metadata along with the raw API responses.
Yes, cross-database scholarly search works for biomedical preprints and multidisciplinary topics by querying arXiv, bioRxiv, medRxiv, PubMed, OpenAlex, and Semantic Scholar simultaneously to gather and compare structured results across all sources.
A limitation of unified scholarly search across multiple APIs is that results depend on each database's specific search strategies and API response structures, meaning raw responses and metadata fields may vary in completeness across the ten queried sources.
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