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tooluniverse-proteomics-data-retrieval

Find and retrieve proteomics datasets from MassIVE and ProteomeXchange. Search by species, keyword, or accession; retrieve detailed metadata (instruments, publications, species, PTMs studied). Use for locating public proteomics datasets to reanalyze, comparing instrument/protocol coverage across studies, and pre-download dataset evaluation.

70

Quality

86%

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SecuritybySnyk

Low

Low-risk findings worth noting

SKILL.md
Quality
Evals
Security

Quality

Content

72%

Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.

A well-organized, highly actionable skill body with concrete tool calls and a clear phase structure. Its main weaknesses are repetition and concept re-explanation that hurt conciseness, and missing inline validation/feedback checkpoints in the workflow.

Suggestions

Consolidate duplicated information — the species taxonomy IDs and response-format notes appear in both the phase sections and later reference tables — into a single location and link to it.

Trim the 'Domain Reasoning: Dataset Quality Assessment' paragraph, which explains DIA/DDA/TMT basics Claude already knows; keep only the tool-specific decision guidance.

Add explicit validation checkpoints inside the workflow (e.g., 'if search returns empty, apply the matching fallback row before proceeding') rather than deferring all error handling to a separate table.

DimensionReasoningScore

Conciseness

Mostly efficient and well-structured, but the body repeats information across sections (e.g., response-format notes and species IDs appear twice) and the 'Domain Reasoning' block explains DIA/DDA/TMT concepts Claude already knows, which could be tightened.

2 / 3

Actionability

Provides concrete, copy-ready tool calls with exact parameters (e.g., `MassIVE_search_datasets(page_size=20, species="9606")`), explicit return shapes, and a parameter reference table, leaving no ambiguity about what to execute.

3 / 3

Workflow Clarity

The four-phase workflow is clearly sequenced, but it lacks explicit validation/feedback checkpoints: search results are not verified for relevance, empty-result handling lives in a separate 'Fallback' table rather than inline checks, and there is no validate-then-retry loop despite batch dataset retrieval.

2 / 3

Progressive Disclosure

No bundle files exist and the skill is a single self-contained SKILL.md; content is organized into well-labeled sections (phases, tool reference, fallbacks, taxonomy IDs) with clear navigation and no nested references, which scores 3 for a reference-free skill.

3 / 3

Total

10

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12

Passed

Description

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.

A strong description that clearly states concrete capabilities, includes natural trigger terms, and provides an explicit 'Use for' clause covering when to invoke it. It is concise, distinct, and free of vague fluff.

DimensionReasoningScore

Specificity

Lists multiple concrete actions: 'Search by species, keyword, or accession' and 'retrieve detailed metadata (instruments, publications, species, PTMs studied)', matching the level-3 anchor of several specific concrete actions.

3 / 3

Completeness

Explicitly answers 'what' (find/retrieve metadata) and 'when' via the 'Use for' clause with three concrete trigger scenarios, satisfying the level-3 anchor for both what and when.

3 / 3

Trigger Term Quality

Includes natural user-facing terms like 'proteomics datasets', 'MassIVE', 'ProteomeXchange', 'PXD', 'accession', and 'species' that a researcher would naturally say, giving good coverage.

3 / 3

Distinctiveness Conflict Risk

The niche of public proteomics repositories (MassIVE/ProteomeXchange) with PXD/MSV accessions is a clear, distinct trigger space unlikely to conflict with generic data or document skills.

3 / 3

Total

12

/

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
mims-harvard/ToolUniverse
Reviewed

Table of Contents

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