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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.

67

Quality

80%

Does it follow best practices?

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SecuritybySnyk

Low

Low-risk findings worth noting

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tessl review fix ./plugin/skills/tooluniverse-proteomics-data-retrieval/SKILL.md
SKILL.md
Quality
Evals
Security

Quality

Content

67%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 well-structured, highly actionable tool-retrieval skill with a clear phased workflow and useful domain-specific reference material. Its main weaknesses are redundant restatements of the same API quirks and the absence of progressive disclosure into bundled reference files.

Suggestions

De-duplicate the "Response Format Notes" (stated in Phase 1, Phase 2, and the Tool Parameter Reference) and the "MassIVE has no keyword search" note (repeated in four sections) into a single canonical location.

Move stable reference material — the Common Species Taxonomy IDs table and the Tool Parameter Reference — into a bundled reference file (e.g., references/tool_reference.md) and link to it from SKILL.md to improve progressive disclosure.

Add one fenced, end-to-end worked example (e.g., keyword search → detail retrieval → synthesized report) so the workflow is copy-paste executable rather than described inline.

DimensionReasoningScore

Conciseness

Mostly efficient, but "Response Format Notes" is stated in Phase 1, Phase 2, and the Tool Parameter Reference, and "MassIVE has no keyword/text search" is repeated across Key Principles, Phase 0, Phase 1, and Limitations — clear redundancy that could be tightened.

3 / 5

Actionability

Concrete tool calls with typed parameters (e.g., `MassIVE_search_datasets(page_size=20, species="9606")`), return shapes, and a parameter reference table give executable guidance, but invocations are inline prose rather than fenced copy-paste blocks and there is no end-to-end worked example.

4 / 5

Workflow Clarity

Phases 0–3 are clearly sequenced with decision logic, parallel-call guidance, and a fallback table for error recovery, though the flow lacks explicit "validate the result" checkpoints.

4 / 5

Progressive Disclosure

Well-organized into clearly headed sections and tables with no nested references, but it is a single ~290-line file with no bundled reference files; reference-style material (taxonomy table, parameter reference) is inlined rather than split out.

4 / 5

Total

15

/

20

Passed

Description

92%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 strong description that explicitly covers both what the skill does and when to use it, with concrete actions and domain-specific trigger terms. The only gap is minor: it omits common synonyms such as "mass spectrometry"/"MS" that users may also invoke.

DimensionReasoningScore

Specificity

Lists multiple concrete actions — "Find and retrieve proteomics datasets", "Search by species, keyword, or accession", "retrieve detailed metadata (instruments, publications, species, PTMs studied)" — giving comprehensive coverage of what the skill does.

5 / 5

Completeness

Explicitly answers both what ("Find and retrieve... Search... retrieve detailed metadata") and when ("Use for locating public proteomics datasets to reanalyze, comparing instrument/protocol coverage across studies") with concrete trigger phrases.

5 / 5

Trigger Term Quality

Natural domain terms like "proteomics datasets", "MassIVE", "ProteomeXchange", "species", "keyword", and "accession" are present, but common synonyms a user would also say (e.g., "mass spectrometry", "MS datasets") are missing.

4 / 5

Distinctiveness Conflict Risk

Occupies a clear niche — proteomics dataset retrieval from MassIVE and ProteomeXchange — with repository-name triggers that are unlikely to fire for unrelated skills.

5 / 5

Total

19

/

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.

Validation16 / 16 Passed

Validation for skill structure

No warnings or errors.

Repository
mims-harvard/ToolUniverse
Reviewed

Table of Contents

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