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openalex-database

Query and analyze scholarly literature using the OpenAlex database. This skill should be used when searching for academic papers, analyzing research trends, finding works by authors or institutions, tracking citations, discovering open access publications, or conducting bibliometric analysis across 240M+ scholarly works. Use for literature searches, research output analysis, citation analysis, and academic database queries.

62

Quality

75%

Does it follow best practices?

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Adds up to 20 points to the overall score

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SecuritybySnyk

Low

Low-risk findings worth noting

Fix and improve this skill with Tessl

tessl review fix ./backend/cli/skills/databases/openalex-database/SKILL.md
SKILL.md
Quality
Evals
Security

Quality

Content

61%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.

A thorough, example-rich body that is highly actionable for common OpenAlex queries, supported by well-signaled reference files. It is held back by content redundancy between sections and the absence of explicit validation checkpoints in its batch and large-scale extraction workflows.

Suggestions

Consolidate the duplicated guidance (two-step pattern, per-page=200, batch_lookup, sampling) into a single 'Best Practices' section and reference it from the numbered capabilities instead of repeating each pattern twice.

Add explicit verification checkpoints to batch and large-scale workflows, e.g. after paginate_all confirm the returned count matches expected totals and after batch_lookup report any IDs that failed to resolve.

Move the Common Filter Patterns, Entity Types, and External IDs sections into references/api_guide.md, leaving SKILL.md as a concise overview that links out, to tighten token budget and improve progressive disclosure.

DimensionReasoningScore

Conciseness

Mostly concrete code with little concept over-explanation, but noticeable redundancy: the two-step pattern, per-page=200, batch_lookup, and sample usage each appear in both the numbered capabilities and the 'Critical Best Practices' section.

3 / 5

Actionability

Abundant copy-paste-ready examples across the common cases, with only minor gaps such as the citation example bypassing the client via raw requests and the manual two-step relying on the private client._make_request method.

4 / 5

Workflow Clarity

Sequences like the two-step entity lookup and troubleshooting error recovery are clear, but batch and large-scale operations (batch_lookup, paginate_all up to 10k+, sample_works >10k) lack explicit validation/verification checkpoints, capping this dimension at 3 per the batch-operation rule.

3 / 5

Progressive Disclosure

Good structure with clearly signaled one-level-deep references to the real references/api_guide.md and references/common_queries.md (plus scripts), though a fair amount of filter-pattern and entity-type detail that could live in those references is inlined in SKILL.md.

4 / 5

Total

14

/

20

Passed

Description

88%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.

A strong, well-structured description that concretely states capabilities and gives explicit use-when guidance with natural trigger phrases. Its only weakness is mild overlap risk with adjacent scholarly-literature skills and a few missing common synonyms.

DimensionReasoningScore

Specificity

Lists multiple concrete actions — 'searching for academic papers, analyzing research trends, finding works by authors or institutions, tracking citations, discovering open access publications, ... conducting bibliometric analysis' — giving comprehensive coverage rather than vague abstractions.

5 / 5

Completeness

Explicitly answers both what ('Query and analyze scholarly literature using the OpenAlex database') and when ('This skill should be used when...' plus 'Use for literature searches, research output analysis, citation analysis, and academic database queries').

5 / 5

Trigger Term Quality

Strong natural keywords ('academic papers', 'research trends', 'citations', 'open access publications', 'literature searches'), but a few common synonyms a user might say ('find papers', 'scholarly articles', 'research papers') are absent.

4 / 5

Distinctiveness Conflict Risk

The named OpenAlex niche and bibliometric framing are distinctive, but broad triggers like 'academic papers' and 'citation analysis' could overlap with other scholarly-database skills (PubMed, Semantic Scholar).

4 / 5

Total

18

/

20

Passed

Validation

87%

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

Validation14 / 16 Passed

Validation for skill structure

CriteriaDescriptionResult

metadata_version

'metadata.version' is missing

Warning

frontmatter_unknown_keys

Unknown frontmatter key(s) found; consider removing or moving to metadata

Warning

Total

14

/

16

Passed

Repository
synthetic-sciences/openscience
Reviewed

Table of Contents

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