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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".

77

Quality

96%

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SecuritybySnyk

Low

Low-risk findings worth noting

SKILL.md
Quality
Evals
Security

Quality

Content

92%Weight 40%Scale 1-5

Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.

Excellent instruction-only skill body: executable commands with real endpoints, well-sequenced workflows with genuine validation and feedback loops, and proper routing of per-database detail into verified one-level-deep reference files. The single weakness is minor redundancy in failure-mode documentation, which costs it the top conciseness score.

Suggestions

Deduplicate the HTTP-200 failure catalog: keep one canonical list (either the intro paragraph or Error Recovery step 1) and cross-reference it from the other location instead of repeating the PMC/arXiv/Europe PMC examples verbatim.

State the bioRxiv/medRxiv no-keyword-search fact once (e.g., in the selection guide note) rather than three times across the selection table, preprint paragraph, and Available Databases table.

Convert the 'Fully open (no key)' prose paragraph into a column in the API Keys table (or move it to a reference file) so rate limits sit in one lookup structure instead of two.

DimensionReasoningScore

Conciseness

The body is dense and nearly every line is actionable (rate limits, encoding traps, exit codes), but there is trimmable redundancy: the HTTP-200-failure catalog (PMC no-<body>, arXiv 'Error' entry, Europe PMC errCode) appears both in the intro paragraph and again in Error Recovery step 1, and bioRxiv/medRxiv having no keyword search is stated three times. This matches 'efficient; minor instances of over-explanation that could be trimmed' rather than the lean-every-token-earns-its-place 5, and it is clearly above level 3 since nothing is concept-explanation padding Claude already knows.

4 / 5

Actionability

Copy-paste-ready commands cover the common cases: a full curl with --data-urlencode for Europe PMC, header-auth curl for Semantic Scholar, and four executable curl|python3 script pipelines (efetch→jats_to_text, arXiv→arxiv_atom, OpenAlex→openalex_abstract, paginate.py walk), plus exact env var names, rate limits, and per-script exit codes. This is fully executable with specific examples covering common cases; a 4 would require missing key details, which are instead pushed properly into --help and reference files.

5 / 5

Workflow Clarity

A 7-step core workflow with ask-don't-guess checkpoints ('If a constraint that affects correctness is missing... ask rather than guess'), a 5-step error recovery loop starting with 'Check whether it actually failed', and a count-first → paginate → reconcile → fail-visible sequence with script exit codes as explicit validation. This matches the anchor: clear sequence with explicit validation steps and feedback loops; the batch/pagination operations all carry validation (count reconciliation, exit code 4), so the workflow-clarity cap does not apply.

5 / 5

Progressive Disclosure

The body is an overview that routes per-database detail to 18 clearly-signaled one-level-deep files in references/ (all verified to exist, with no nested .md links) via selection-guide and Available Databases tables, and parsing logic to four scripts/ files. The only wrinkle is a mention of tests/paper-lookup/ which does not exist in the bundle, but it is phrased as an instruction for future additions, not a navigation reference. Structure and navigation match the anchor-5 example.

5 / 5

Total

19

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20

Passed

Description

100%Weight 40%Scale 1-5

Based on the skill's description, can an agent find and select it at the right time? Clear, specific descriptions lead to better discovery.

An exemplary description: third-person, dense with concrete actions, all 18 databases enumerated, and an explicit 'Use when' clause with verbatim natural-language trigger phrases. Every token carries information with no padding or over-claims.

DimensionReasoningScore

Specificity

The description lists multiple concrete actions — "Searches 18 scholarly APIs for papers, preprints, citations, open-access full text, repository records, and journal OA status, and returns results with reproducible provenance" — and enumerates all 18 covered databases by name (PubMed, PMC, Europe PMC, bioRxiv, medRxiv, arXiv, OpenAlex, Crossref, Semantic Scholar, CORE, Unpaywall, OpenCitations, PubTator3, Zenodo, Figshare, ROR, BioStudies, DOAJ), matching the comprehensive-coverage anchor. It is not a 4 because the action list has no material gaps, and it uses third person ("Searches", "Covers") throughout.

5 / 5

Completeness

Both questions are answered explicitly: the first two sentences state what the skill does, and "Use when searching for papers, citations, DOI/PMID/arXiv lookups..." plus "Triggers on mentions of any supported database or requests like 'find papers on X'" state when, with concrete trigger phrases. This matches the anchor-5 example structure exactly; a 4 would require the 'when' clause to be less explicit than it is.

5 / 5

Trigger Term Quality

Natural user phrases are included verbatim — "find papers on X", "look up this DOI", "who cites this paper", "get me the PDF" — plus broad synonym coverage ("papers, citations, DOI/PMID/arXiv lookups, abstracts, full text, open-access PDFs, preprints, citation graphs, author publications"). It is not a 4 because no commonly used natural term for this domain is missing.

5 / 5

Distinctiveness Conflict Risk

It carves out a clear niche (scholarly-literature retrieval across named academic APIs) with database-specific triggers (ROR IDs, Zenodo/Figshare/BioStudies deposited records, PubTator3 annotations) unlikely to fire for unrelated skills. It is not a 4 because the named-database enumeration and domain-specific triggers leave minimal overlap risk.

5 / 5

Total

20

/

20

Passed

Validation

100%

Checks the skill against the spec for correct structure and formatting. All validation checks must pass before discovery and implementation can be scored.

Validation — 16 / 16 Passed

Validation for skill structure

No warnings or errors.

Repository
K-Dense-AI/scientific-agent-skills
Reviewed

Table of Contents

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