Individual skill
paper-lookup
Searches 18 scholarly APIs for papers, preprints, citations, open-access full text, repository records, and journal OA status, and returns results with reproducible provenance. Covers PubMed, PMC, Europe PMC, bioRxiv, medRxiv, arXiv, OpenAlex, Crossref, Semantic Scholar, CORE, Unpaywall, OpenCitations, PubTator3, Zenodo, Figshare, ROR, BioStudies, and DOAJ. Use when searching for papers, citations, DOI/PMID/arXiv lookups, abstracts, full text, open-access PDFs, preprints, citation graphs, author publications, biomedical entity annotations, deposited records (Zenodo, Figshare, BioStudies), institution ROR IDs, or any scholarly literature query. Triggers on mentions of any supported database or requests like "find papers on X", "look up this DOI", "who cites this paper", or "get me the PDF".
skills/paper-lookup/SKILL.md
Source commit 2d2065fb4520fa3f3f2bcf61cff26ec8b7eba4b5
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- Matches the observed repository HEAD
- Yes
- Scanner rules are current
- No
- Repository scan complete
- No
- Skill scan complete
- No
- Observed behavior
- Not checked yet
- Last checked
- Nov 10, 2026
These are observations at the recorded commit, not a guarantee of safety. Review the source before running it.
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Repository context
- Repository stars (not skill ratings)
- 56,923
- Repository last updated
- Nov 9, 2026
- License
- MIT
Observed agent integration: No specific integration evidence. Standard SKILL.md installation does not imply verified compatibility.
- ai-scientist Repository topic
- bioinformatics Repository topic
- chemoinformatics Repository topic
- claude Repository topic
- claude-skills Repository topic
- claudecode Repository topic
- clinical-research Repository topic
- computational-biology Repository topic
- data-analysis Repository topic
- drug-discovery Repository topic
- research Derived category
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- data-databases Derived category
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Browse files
SKILL.mdcore · 26,136 bytesSKILL.mdcore · 26,136 bytesSKILL.mdcore · 26,136 bytesSKILL.mdcore · 26,136 bytesSKILL.mdcore · 26,136 bytesreferences/arxiv.mddoc · 12,155 bytesreferences/biorxiv.mddoc · 6,836 bytesreferences/biostudies.mddoc · 4,049 bytesreferences/core.mddoc · 4,757 bytesreferences/crossref.mddoc · 5,642 bytesreferences/doaj.mddoc · 4,348 bytesreferences/europepmc.mddoc · 9,215 bytesreferences/figshare.mddoc · 3,125 bytesreferences/medrxiv.mddoc · 5,155 bytesreferences/openalex.mddoc · 5,635 bytesreferences/opencitations.mddoc · 4,734 bytesreferences/pmc.mddoc · 7,288 bytesreferences/pubmed.mddoc · 4,654 bytesreferences/pubtator.mddoc · 4,657 bytesreferences/ror.mddoc · 4,348 bytesreferences/semantic-scholar.mddoc · 7,220 bytesreferences/unpaywall.mddoc · 3,572 bytesreferences/zenodo.mddoc · 3,928 bytesscripts/_common.pyruns · 8,377 bytesscripts/arxiv_atom.pyruns · 8,188 bytesscripts/jats_to_text.pyruns · 11,304 bytesscripts/openalex_abstract.pyruns · 6,425 bytesscripts/paginate.pyruns · 19,657 bytes
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# Paper Lookup
This skill gives you 18 scholarly APIs with documented endpoints. Your job is to turn the user's intent into a reproducible retrieval: pick the authoritative database(s), make bounded and rate-limited calls, and return an answer with enough provenance (endpoints, parameters, identifiers, access date) that a human or another agent can repeat it.
A literature lookup is only as trustworthy as it is repeatable. Prefer explicit identifiers and documented endpoints over broad guessing, report what you queried, and say plainly when a result is partial or a database came back empty — a silent gap reads as "nothing exists" when it may just mean "not indexed here."
Endpoint contracts were reviewed against official documentation on 2026-09-30. Response examples are illustrative shapes or explicitly dated historical captures; counts, prices, availability, and status values are not current lookup results. Selected public smoke calls and offline parser tests do not establish authenticated full-text access.
**These APIs can fail with HTTP 200.** That is the recurring hazard, and the reason for most of the rules below. PMC eFetch returns a well-formed article with no `<body>` when the publisher forbids redistribution. arXiv returns `totalResults: 1` and one entry titled `Error` for a malformed parameter, and silently rewrites an unknown field prefix to `all:`. Europe PMC puts `errCode` in a 200 body. bioRxiv treats cursors as absolute offsets, so an incorrect step skips records. Figshare `GET /articles?search_for=` ignores the query and still 200s. OpenCitations answers an unknown DOI with `[{"count": "0"}]`. None of these raise, and every one of them produces a confident, wrong answer. Verify the shape of what you got, not just the status code.
## Core Workflow
1. **Define the retrieval contract** — What is the user after? A specific paper by DOI/PMID/arXiv ID? Papers on a topic? An author's publications? A citation graph? An open-access PDF? Full text? Note any constraints that change the answer: date range, field of study, open-access-only, exhaustive list vs. a few top hits. If a constraint that affects correctness is missing (e.g., "recent" with no year, or an author name with many namesakes), ask rather than guess.