literature-search-openalex

Query the OpenAlex scholarly database for research papers, authors, institutions, topics, sources, publishers, funders, geo-locations, and keywords. Use when searching academic papers, resolving DOIs, downloading open-access PDFs, finding an author's publications, aggregating bibliometric data (citation counts, h-index, impact factor), exploring the research taxonomies, or performing DOI lookups.

Quality

100%

Does it follow best practices?

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Securityby

Passed

No findings from the security scan

Quality

Content

100%Weight 40%Scale 1-3

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

A well-structured, token-efficient skill body with executable CLI examples, clearly sequenced workflows that include validation and error-recovery feedback loops, and clean one-level progressive disclosure into real reference files. No substantive weaknesses identified.

Dimension	Reasoning	Score
Conciseness	The body is lean: it does not explain what OpenAlex, DOIs, or bibliometrics are, and uses compact tables for rate limits, costs, and error codes, so every token earns its place.	3 / 3
Actionability	Provides fully executable, copy-paste-ready commands — e.g. 'uv run scripts/openalex_cli.py resolve authors "Geoffrey Hinton"' and complete filter-to-jq pipelines — rather than pseudocode or vague direction.	3 / 3
Workflow Clarity	Multi-step workflows are clearly sequenced (resolve → filter), with explicit validation on PDF download ('verify it is not empty or corrupted') and a feedback loop in the error-handling table (401/429 → credentials protocol → retry).	3 / 3
Progressive Disclosure	The body is an overview that points to one-level-deep, clearly signaled reference files (e.g. references/works.md, references/authors.md) for per-entity filter/sort/group-by fields, all of which exist on disk.	3 / 3
	Total	12 / 12 Passed

Description

100%Weight 40%Scale 1-3

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

A strong, third-person description that concisely states concrete capabilities and gives an explicit 'Use when' trigger with broad, natural keyword coverage. It is distinctive and unlikely to conflict with other skills.

Dimension	Reasoning	Score
Specificity	Lists multiple concrete actions — querying papers/authors/institutions/topics, resolving DOIs, downloading open-access PDFs, finding an author's publications, aggregating bibliometric data — matching the 'multiple specific concrete actions' anchor.	3 / 3
Completeness	Explicitly answers both 'what' (query the OpenAlex scholarly database for the listed entities) and 'when' via an explicit 'Use when...' clause, satisfying the anchor requiring both.	3 / 3
Trigger Term Quality	Covers natural user phrasings such as 'academic papers', 'resolving DOIs', 'open-access PDFs', 'citation counts', 'h-index', 'impact factor', and 'DOI lookups', giving good coverage of terms users would actually say.	3 / 3
Distinctiveness Conflict Risk	Occupies a clear niche — the OpenAlex scholarly database — with distinct, domain-specific triggers that are unlikely to fire for unrelated skills.	3 / 3
	Total	12 / 12 Passed

Validation

100%

Warnings & errors only

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: google-deepmind/science-skills
Path: skills/literature_search_openalex/SKILL.md
Commit: 0b42509

Reviewed: 7 days ago

Table of Contents

Discovery Implementation Validation

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