paper-lookup
by K-Dense-AIpaper-lookup is a research retrieval skill for Academic Research, helping you find scholarly papers, preprints, citations, DOI/PMID matches, abstracts, full text, and open access copies across 10 academic databases. Use it for paper-lookup usage when you need the right source first, not a generic web search. The paper-lookup guide points to PubMed, PMC, Crossref, OpenAlex, Semantic Scholar, CORE, arXiv, bioRxiv, medRxiv, and Unpaywall.
This skill scores 84/100, which means it is a solid listing candidate for directory users. It clearly supports a real scholarly-lookup workflow across 10 academic databases, with enough endpoint-specific guidance and trigger language that an agent can use it with less guesswork than a generic prompt.
- Strong triggerability: the frontmatter explicitly says to use it for paper search, DOI/PMID lookups, abstracts, full text, open access, preprints, citation graphs, and author searches.
- Operationally useful workflow: SKILL.md lays out a core process for choosing databases, reading reference files, making API calls, and returning results, supported by 10 database-specific reference docs.
- Good leverage across scholarly sources: includes major services like PubMed, PMC, Crossref, OpenAlex, Semantic Scholar, CORE, arXiv, bioRxiv, medRxiv, PubMed, and Unpaywall-related OA checks.
- No install command or automation scripts are included, so adoption depends on the agent correctly following the reference docs and platform-specific fetch tool.
- Some databases have important constraints noted in the references, such as bioRxiv/medRxiv lacking keyword search and CORE requiring auth for full text, which limits one-size-fits-all use.
Overview of paper-lookup skill
paper-lookup is a research retrieval skill for finding scholarly papers, preprints, citations, DOI/PMID matches, abstracts, and open access full text across 10 academic databases. It is best for users doing Academic Research who want a faster, more reliable path from a vague topic or identifier to the right paper sources.
What paper-lookup is for
Use the paper-lookup skill when the real job is not “search the web,” but “find the right academic record.” It helps with topic searches, author searches, DOI/PMID lookups, paper verification, citation tracing, and locating OA copies or full text.
Where it fits best
It is strongest when you need broad coverage plus database choice logic: PubMed and PMC for biomedical literature, arXiv and bioRxiv/medRxiv for preprints, Crossref for DOI-heavy metadata, OpenAlex for broad discovery, Semantic Scholar for citation-aware search, CORE for repository full text, and Unpaywall for OA status.
Main differentiators
The paper-lookup skill is not a generic prompt template. Its value is in choosing the right database first, then combining sources when one index is incomplete. That matters for paper-lookup install decisions because many literature tasks fail from using the wrong database, not from weak wording.
How to Use paper-lookup skill
Install and entry point
For paper-lookup install, add the skill to your Claude skills setup and then start from SKILL.md. The repository is organized around one workflow plus reference files, so the fastest path is to read the main skill file first and then open the database-specific reference only for the sources you actually need.
Turn a rough request into a usable query
paper-lookup usage works best when your prompt names the goal, the identifier type, and the preferred source if you have one. Good inputs include:
- “Find papers on long-COVID biomarkers, prioritize PubMed and OpenAlex.”
- “Look up DOI
10.1038/s41586-024-12345-xand return metadata plus OA status.” - “Find the full text for this PMC article and cite the key methods section.”
Avoid prompts like “research this” unless you also specify the field, date range, or whether you want papers, preprints, or full text.
Read the right files first
A practical paper-lookup guide starts with these files:
SKILL.mdfor the workflow and database choice logicreferences/pubmed.mdfor biomedical literature searchreferences/pmc.mdfor full-text biomedical articlesreferences/crossref.mdfor DOI and publication metadatareferences/openalex.mdfor broad discovery and author/work lookupreferences/unpaywall.mdfor open access copy checks
Read references/arxiv.md, references/biorxiv.md, or references/medrxiv.md when the query is preprint-specific.
Workflow tips that change results
Use the source that matches the question:
- Discovery: OpenAlex, Crossref, Semantic Scholar
- Biomedical abstracts and indexing: PubMed
- Full text: PMC or CORE
- OA availability: Unpaywall
- Preprints: arXiv, bioRxiv, medRxiv
If the user’s goal is ambiguous, specify the output you want in the prompt, such as “return 5 relevant papers with title, year, DOI, and why each matched.” That reduces irrelevant results and makes the paper-lookup skill more dependable.
paper-lookup skill FAQ
Is paper-lookup only for Academic Research?
No. It is especially strong for Academic Research, but it also helps when you need a DOI check, a citation trail, or a full-text lookup for a paper mentioned in another document.
When should I not use paper-lookup?
Do not use it for general news, patent search, or casual web discovery. It is a paper-lookup skill, so it is most useful when the target is a scholarly work, preprint, or database record.
Why not just ask a normal prompt?
A normal prompt cannot reliably pick the best scholarly source or handle database-specific constraints. paper-lookup is better when the input is a paper identifier, a precise topic, or a task that depends on citation metadata, abstract retrieval, or open access status.
Is it beginner-friendly?
Yes, if you can state the topic and the desired output. Beginners usually get the best results by asking for a small, specific set of papers and including one constraint, such as “recent,” “open access,” or “biomedical only.”
How to Improve paper-lookup skill
Give the skill the right search shape
The biggest quality gain comes from clearer query shape. Instead of “papers about AI safety,” try “recent review papers on AI safety governance, exclude opinion pieces, prioritize peer-reviewed sources, and include DOI.” That gives paper-lookup a better chance to choose the right databases and return usable records.
State the output you actually need
If you want to compare papers, ask for fields that support comparison: title, year, authors, DOI, venue, abstract, and OA link. If you want to verify a citation, ask for exact-matching metadata. If you want full text, say so up front so the skill can route to PMC or CORE instead of only abstract indexes.
Watch for common failure modes
The most common paper-lookup failure is mixing discovery and full-text retrieval in one vague request. Another is using a preprint database for a journal-only question, or vice versa. Improve paper-lookup usage by separating these tasks: first find the record, then fetch full text or OA status if needed.
Iterate after the first pass
If the first results are too broad, refine by date, field, article type, or source. If results are too narrow, remove overly specific terms and let OpenAlex, Crossref, or Semantic Scholar broaden the search. For paper-lookup for Academic Research, the best second prompt often adds one constraint, not ten.