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.
90
92%
Does it follow best practices?
Impact
81%
1.05xAverage score across 3 eval scenarios
Advisory
Suggest reviewing before use
Quality
Discovery
100%Based on the skill's description, can an agent find and select it at the right time? Clear, specific descriptions lead to better discovery.
This is an excellent skill description that hits all the marks. It provides specific capabilities, includes natural trigger terms researchers would use, explicitly states both what it does and when to use it, and carves out a distinct niche around academic literature and the OpenAlex database. The description is comprehensive yet concise.
| Dimension | Reasoning | Score |
|---|---|---|
Specificity | Lists multiple specific concrete actions: 'searching for academic papers', 'analyzing research trends', 'finding works by authors or institutions', 'tracking citations', 'discovering open access publications', 'conducting bibliometric analysis'. Also specifies the database (OpenAlex) and scale (240M+ works). | 3 / 3 |
Completeness | Clearly answers both what ('Query and analyze scholarly literature using OpenAlex database') and when ('should be used when searching for academic papers, analyzing research trends...'). Has explicit 'Use for' clause listing trigger scenarios. | 3 / 3 |
Trigger Term Quality | Excellent coverage of natural terms users would say: 'academic papers', 'research trends', 'authors', 'institutions', 'citations', 'open access', 'literature searches', 'bibliometric analysis', 'scholarly works', 'academic database queries'. These are terms researchers naturally use. | 3 / 3 |
Distinctiveness Conflict Risk | Highly distinctive with clear niche: specifically targets OpenAlex database for scholarly/academic literature. The combination of 'OpenAlex', 'scholarly', 'bibliometric', and '240M+ scholarly works' creates a unique fingerprint unlikely to conflict with general document or search skills. | 3 / 3 |
Total | 12 / 12 Passed |
Implementation
85%Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.
This is a high-quality skill with excellent actionability and clear workflow guidance. The code examples are executable and comprehensive, covering 12 distinct use cases with proper patterns. Minor verbosity in the overview and some explanatory text could be trimmed, but overall the skill effectively teaches Claude how to query OpenAlex without unnecessary padding.
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | The skill is generally efficient but includes some unnecessary explanations (e.g., 'OpenAlex is a comprehensive open catalog of 240M+ scholarly works' in the overview, explaining what entity types are). Some sections could be tightened, though most code examples are lean. | 2 / 3 |
Actionability | Excellent actionability with fully executable Python code examples throughout. Every capability includes copy-paste ready code with proper imports, parameters, and realistic usage patterns. The two-step pattern is clearly demonstrated with both helper functions and manual approaches. | 3 / 3 |
Workflow Clarity | Multi-step processes are clearly sequenced (e.g., two-step entity lookup pattern, large-scale data extraction with CSV export). The troubleshooting section provides clear feedback loops for common errors. Best practices section explicitly shows correct vs incorrect patterns with checkmarks. | 3 / 3 |
Progressive Disclosure | Well-structured with clear overview, quick start, core capabilities, and references to detailed documentation (api_guide.md, common_queries.md). Content is appropriately split between the main skill file and reference materials with clear navigation signals. | 3 / 3 |
Total | 11 / 12 Passed |
Validation
90%Checks the skill against the spec for correct structure and formatting. All validation checks must pass before discovery and implementation can be scored.
Validation — 10 / 11 Passed
Validation for skill structure
| Criteria | Description | Result |
|---|---|---|
metadata_version | 'metadata.version' is missing | Warning |
Total | 10 / 11 Passed | |
- Repository
- K-Dense-AI/claude-scientific-skills
- Commit
71add64
- Reviewed
Table of Contents
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