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metabolights-skill

Submit compact MetaboLights requests for study discovery and study-level metabolomics metadata. Use when a user wants concise MetaboLights summaries

72

Quality

87%

Does it follow best practices?

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SecuritybySnyk

Low

Low-risk findings worth noting

SKILL.md
Quality
Evals
Security

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.

The body is tight, executable, and well-structured for a single-task REST-wrapper skill, with concrete examples and clear input/output contracts. No meaningful gaps for a skill of this scope.

DimensionReasoningScore

Conciseness

The body is lean and assumes Claude's competence — operating rules, exact field lists, and a single executable example with no padding or explanations of concepts Claude already knows, fitting the 'lean and efficient' anchor.

3 / 3

Actionability

Provides a copy-paste-ready bash invocation with a complete JSON payload, concrete base_url, and specific endpoint paths ('studies', 'studies/<MTBLS accession>'), matching the 'fully executable' anchor.

3 / 3

Workflow Clarity

This is a simple single-purpose skill whose one action (pipe JSON to rest_request.py) is unambiguous, and the Output section documents success/failure fields as a validation cue, so the simple-skill allowance applies.

3 / 3

Progressive Disclosure

Under 50 lines with well-organized sections and a single real referenced bundle file (scripts/rest_request.py) signaled explicitly; the References section confirms no deeper nesting is needed, fitting the simple-skill allowance for a 3.

3 / 3

Total

12

/

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.

The description is third-person, includes an explicit 'Use when' trigger, and carves out a distinctive MetaboLights niche. It is slightly held back by limited action breadth and trigger-term variation.

Suggestions

Broaden the capability list in the description to surface additional concrete actions (e.g. fetching assay/ISA metadata or factor data), not just study discovery and study-level metadata.

Add more natural trigger terms users would say, such as 'MTBLS accession', 'metabolomics study', or 'ISA metadata', to improve keyword coverage.

Consider noting the output format promise (concise summaries vs raw JSON) earlier in the description so the trigger guidance reinforces the expected result.

DimensionReasoningScore

Specificity

Names concrete actions ('Submit compact MetaboLights requests', 'study discovery', 'study-level metabolomics metadata') but only covers two capabilities rather than a comprehensive list, matching the 'names domain and some actions' anchor.

2 / 3

Completeness

Explicitly states what it does and includes an explicit 'Use when a user wants concise MetaboLights summaries' trigger, satisfying both the what and when requirements for a 3.

3 / 3

Trigger Term Quality

Natural terms like 'MetaboLights', 'study discovery', and 'metabolomics summaries' are present, but common variations a user might say (e.g. 'MTBLS', 'metabolomics study', 'ISA metadata') are missing, fitting 'some relevant keywords but missing common variations'.

2 / 3

Distinctiveness Conflict Risk

MetaboLights is a narrow, well-defined niche with distinct triggers unlikely to conflict with other skills, matching the 'clear niche with distinct triggers' anchor.

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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