tooluniverse-kegg-disease-drug

KEGG-based disease-drug-variant network research. Connects diseases to causal genes, drugs to molecular targets, and variants to pathways using KEGG's editorially curated databases (KEGG Disease, Drug, Network, Variant, Pathway). Use for drug repurposing via shared pathways, mechanistic disease-gene-drug networks, and pathway-based target discovery. Distinguishes direct (binding) vs indirect (pathway co-membership) drug-target relationships.

Quality

80%

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Securityby

Low

Low-risk findings worth noting

Quality

Content

68%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.

The content is highly actionable with executable examples and a clear phased workflow, but is hampered by repeated conceptual explanation across sections and a lack of explicit validation checkpoints in the workflow. Structure is good for a single-file skill with no bundle references.

Suggestions

Trim redundant conceptual explanation: the direct-vs-indirect drug-target distinction and KEGG-coverage caveats appear in both the Reasoning Strategy and Interpretation Guidance sections — consolidate once.

Add explicit validation/verification steps to the workflow phases (e.g., confirm retrieved IDs are non-empty, verify converted IDs before downstream queries) to raise workflow clarity.

Condense the Interpretation Guidance prose into the Evidence Grading table and Synthesis Questions, removing restated biology Claude already knows.

Dimension	Reasoning	Score
Conciseness	Mostly efficient with executable examples, but the Reasoning Strategy and Interpretation Guidance sections restate concepts Claude likely knows and repeat the direct-vs-indirect and KEGG-coverage caveats across multiple sections.	3 / 5
Actionability	Provides copy-paste ready, fully executable Python across the tool inventory, per-phase examples, ID conversion, and a complete end-to-end BRAF example covering common cases.	5 / 5
Workflow Clarity	The five-phase pipeline is sequenced but phases are described thinly and lack explicit validation checkpoints or feedback loops, even though operations are read-only.	3 / 5
Progressive Disclosure	No bundle files exist; the single SKILL.md is well-organized into clear sections (When to Use, Tool Inventory, Workflow, Example, ID Conversion, Integration, Reasoning Framework, Output) with good navigation, though some inline guidance could be trimmed.	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.

The description is specific, complete, and distinctive, clearly stating concrete capabilities and explicit use-case triggers tied to KEGG's curated databases. Trigger term coverage is strong but slightly short of comprehensive synonym/variation coverage.

Dimension	Reasoning	Score
Specificity	Lists multiple concrete actions ('Connects diseases to causal genes, drugs to molecular targets, and variants to pathways'; 'Distinguishes direct (binding) vs indirect (pathway co-membership)') with comprehensive coverage, matching the anchor for multiple specific concrete actions.	5 / 5
Completeness	Explicitly answers what ('Connects diseases to causal genes, drugs to molecular targets...') and when ('Use for drug repurposing via shared pathways, mechanistic disease-gene-drug networks, and pathway-based target discovery') with concrete trigger phrases.	5 / 5
Trigger Term Quality	Includes natural terms like 'KEGG disease', 'KEGG drug', 'disease genes', and 'drug targets', but some common variations and synonyms a user might say are missing, placing it just below comprehensive coverage.	4 / 5
Distinctiveness Conflict Risk	Occupies a clear niche tied to specific KEGG curated databases with distinct triggers, minimizing conflict risk with other skills.	5 / 5
	Total	19 / 20 Passed

Validation

93%

Warnings & errors only

Checks the skill against the spec for correct structure and formatting. All validation checks must pass before discovery and implementation can be scored.

Validation — 15 / 16 Passed

Validation for skill structure

Criteria	Description	Result
frontmatter_unknown_keys	Unknown frontmatter key(s) found; consider removing or moving to metadata	Warning

	Total	15 / 16 Passed

Repository: mims-harvard/ToolUniverse
Path: plugins/tooluniverse/skills/tooluniverse-kegg-disease-drug/SKILL.md
Commit: 1b02920

Reviewed: 1 day ago

Table of Contents

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