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eqtl-catalogue-skill

Submit compact eQTL Catalogue API requests for association retrieval and documented metadata endpoints. Use when a user wants concise public eQTL Catalogue summaries

68

Quality

81%

Does it follow best practices?

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SecuritybySnyk

Low

Low-risk findings worth noting

SKILL.md
Quality
Evals
Security

Quality

Content

87%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 compact, well-structured, highly actionable body that leverages a real bundle script and concrete examples. The only notable gap is the absence of an explicit error-recovery feedback loop for the documented upstream 400/500 failures.

Suggestions

Add a short validate/retry loop for the documented 400/500 failures (e.g. retry once on timeout, then surface the error verbatim) to turn fragile-API guidance into a complete feedback workflow.

Note when re-running is preferred over surfacing the error (line 13 mentions re-running in long conversations) and tie it explicitly to the 400/500 recovery path.

DimensionReasoningScore

Conciseness

The body is lean and assumes Claude's competence: required/optional fields, concrete stdin JSON examples, and exact endpoint paths, with no teaching of concepts Claude already knows; the API-fragility caveats are skill-specific operational knowledge, not padding.

3 / 3

Actionability

Provides fully executable guidance: a copy-paste `echo '...' | python scripts/rest_request.py` command, concrete input JSON examples, and exact versioned paths, all copy-paste ready.

3 / 3

Workflow Clarity

The single-task Input→Output→Execution flow is unambiguous, but the API is flagged as fragile with documented 400/500 failures and the guidance only says to 'surface' errors verbatim, giving no validate→fix→retry feedback loop for recovery.

2 / 3

Progressive Disclosure

At ~40 lines with clearly organized sections and a single real, existing bundle reference (scripts/rest_request.py) explicitly flagged as the only needed file, navigation is one level deep and well-signaled.

3 / 3

Total

11

/

12

Passed

Description

75%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 concise, third-person description that clearly states capability and an explicit usage trigger, with a distinctive niche. It scores slightly lower on specificity and trigger coverage because it centers on a single capability and omits common keyword variations.

Suggestions

Broaden action specificity beyond the single 'submit requests' capability (e.g. add 'fetch associations', 'list studies', 'query metadata' as distinct concrete actions) to reach full specificity.

Add common trigger-term variations users might say (e.g. 'eQTL summary statistics', 'GWAS-eQTL lookups', 'eQTL study metadata') for fuller keyword coverage.

DimensionReasoningScore

Specificity

Names the domain and concrete actions ('Submit compact eQTL Catalogue API requests for association retrieval and documented metadata endpoints') but does not list multiple distinct concrete actions like the score-3 anchor, so it stops at 'names domain and some actions'.

2 / 3

Completeness

Explicitly answers both 'what' (submit API requests for association retrieval and metadata endpoints) and 'when' via an explicit 'Use when a user wants concise public eQTL Catalogue summaries' trigger.

3 / 3

Trigger Term Quality

Includes domain-natural keywords ('eQTL Catalogue', 'association retrieval', 'metadata endpoints') that a genomics user would say, but lacks common variations (e.g. 'eQTL summary statistics', 'GWAS') so coverage is partial rather than broad.

2 / 3

Distinctiveness Conflict Risk

'eQTL Catalogue' is a highly specific niche with distinct triggers, making it very unlikely to fire for unrelated skills.

3 / 3

Total

10

/

12

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.

Validation16 / 16 Passed

Validation for skill structure

No warnings or errors.

Repository
openai/plugins
Reviewed

Table of Contents

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