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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

66

Quality

83%

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SecuritybySnyk

Low

Low-risk findings worth noting

SKILL.md
Quality
Evals
Security

Quality

Content

92%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 tight, fully executable single-purpose skill body: concrete commands, verified field contracts, explicit error handling, and an honest minimal bundle. The only flaw is a small redundancy between the Operating rules and Execution behavior path lists.

DimensionReasoningScore

Conciseness

The body is lean, assumes Claude's competence, and explains nothing Claude already knows; every section is operational. One minor trim exists: 'Prefer these paths: studies and studies/<MTBLS accession>' in Execution behavior duplicates the Operating rules line 'Start with studies ... and studies/<MTBLS accession>', which keeps it just below 'every token earns its place'. It is clearly above level 3, which requires unnecessary explanation, not just redundancy.

4 / 5

Actionability

The Execution section gives a copy-paste-ready bash command with a fully concrete JSON payload, and the Input section supplies two more complete request patterns plus exact field contracts — all of which I verified against scripts/rest_request.py, where every documented field exists. The success/failure output contract is explicit. This matches 'Fully executable; copy-paste ready code or commands; specific examples cover the common cases'; level 4 would leave minor gaps, and none are present.

5 / 5

Workflow Clarity

This is a simple, single-task skill (issue a REST request via one script) and the single action is unambiguous: which script to use, the base_url, the preferred paths, the exact invocation, and how to interpret success and failure output are all explicit. The failure contract ('ok=false with error.code and error.message') and the paging guardrail ('Keep study discovery narrow and paged') serve as checkpoints. Per the rubric's simple-skill exception this warrants 5; it is not a destructive or batch workflow, so the level-3 cap does not apply.

5 / 5

Progressive Disclosure

The skill is under 50 lines, has no need for external references (the References section explicitly states 'No additional runtime references are required; keep the import package limited to this file and scripts/rest_request.py'), and scripts/rest_request.py — the only referenced path — exists. Sections are well-organized and appropriately scoped, matching the rubric's guidance that such skills score 5 with just well-organized sections.

5 / 5

Total

19

/

20

Passed

Description

66%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 distinct, domain-anchored description with an explicit 'Use when' clause, but its trigger vocabulary is thin and its 'when' clause is circular rather than situation-specific. Concrete improvements are available without adding length.

Suggestions

Add natural trigger terms users would actually say, especially the 'MTBLS' accession prefix (e.g., 'Use when the user mentions MetaboLights, MTBLS accessions, or wants metabolomics study metadata').

Make the 'when' clause situation-based instead of circular — name the circumstances (browsing the MetaboLights archive, looking up a specific study) rather than restating 'concise summaries'.

List one or two more concrete actions (e.g., 'browse and filter studies, fetch study metadata and sample/assay details') to raise specificity from two partial actions to several.

DimensionReasoningScore

Specificity

The description names the domain ("MetaboLights") and 1-2 concrete actions ("Submit compact MetaboLights requests for study discovery" and retrieving "study-level metabolomics metadata"), but coverage is not comprehensive — it never says what is done with the metadata or what a 'request' concretely involves. This matches the anchor 'Names domain and 1-2 concrete actions, but not comprehensive'; it is above level 2 (the actions are domain-specific, not generic) and below level 4 (only two actions are listed).

3 / 5

Completeness

Both parts are explicitly present: the 'what' ("Submit compact MetaboLights requests for study discovery and study-level metabolomics metadata") and the 'when' ("Use when a user wants concise MetaboLights summaries"). The 'when' is circular — it restates the skill's output rather than naming concrete triggering situations (e.g., mentioning an MTBLS accession or asking to browse MetaboLights) — so it does not reach level 5's 'concrete trigger phrases', but it exceeds level 3 where 'when' is missing or only implied.

4 / 5

Trigger Term Quality

Relevant keywords are present ("MetaboLights", "study discovery", "metabolomics metadata", "MetaboLights summaries") but common variations are missing — most notably the "MTBLS" accession prefix users naturally cite, plus "EBI", "database", or "browse the archive". This fits 'Some relevant keywords but missing common variations or synonyms' rather than level 4, where keyword coverage would be good with only a few natural terms missing.

3 / 5

Distinctiveness Conflict Risk

MetaboLights is a named, specific EBI resource, so the description carves out a clear niche with minimal overlap risk against generic data-retrieval or document skills. This matches 'Clear niche with distinct triggers; minimal conflict risk'; level 4 would imply minor overlap with closely related skills, which is not the case here.

5 / 5

Total

15

/

20

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.

Validation — 16 / 16 Passed

Validation for skill structure

No warnings or errors.

Repository

openai/plugins

Path

plugins/life-science-research/skills/metabolights-skill/SKILL.md

Reviewed

Table of Contents

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