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

79%

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Securityby

Passed

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tessl review fix ./plugin/skills/tooluniverse-kegg-disease-drug/SKILL.md

Quality

Content

75%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.

Highly actionable content with concrete executable examples and a clear phased workflow. The chief weaknesses are repetition of the same caveats across multiple sections and inline placement of lengthy interpretation guidance that could be offloaded to a reference.

Suggestions

Consolidate the direct-vs-indirect and KEGG-coverage/ID-caveat points so each appears once (e.g., in Reasoning Strategy) and is referenced rather than restated in Interpretation Guidance and Synthesis Questions.

Move the detailed Reasoning Framework (Evidence Grading table, Interpretation Guidance, Synthesis Questions) into a references/ file, keeping SKILL.md as a concise overview that links to it.

Add an explicit validation checkpoint in the workflow (e.g., confirm a disease_id returned results before proceeding to gene/drug phases) to make the sequence's checkpoints explicit.

Dimension	Reasoning	Score
Conciseness	Mostly efficient and domain-specific, but key points recur across sections — direct-vs-indirect relationships and the KEGG coverage/ID caveat each appear three times (Reasoning Strategy, Interpretation Guidance, Synthesis Questions), which could be tightened.	3 / 5
Actionability	Provides copy-paste-ready Python with real IDs (H00031, D09996), a complete tool inventory table with params and returns, and an end-to-end example workflow covering the common cases.	5 / 5
Workflow Clarity	A clearly sequenced five-phase workflow with a 'LOOK UP DON'T GUESS' guardrail; the operations are read-only lookups so the destructive/batch cap does not apply, but validation checkpoints are implicit rather than explicit.	4 / 5
Progressive Disclosure	Well-organized into clear sections with no nested references, but at ~186 lines the detailed interpretation guidance and synthesis questions are inlined content that could be split into a separate reference file.	4 / 5
	Total	16 / 20 Passed

Description

83%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, specific description that names concrete capabilities and an explicit use clause within a clearly distinct KEGG niche. The main weakness is trigger phrasing framed as scenarios rather than natural user utterances.

Dimension	Reasoning	Score
Specificity	Lists multiple concrete actions (connects diseases to causal genes, drugs to molecular targets, variants to pathways) plus a distinguishing direct-vs-indirect capability, giving comprehensive coverage rather than minor gaps.	5 / 5
Completeness	Clearly answers 'what' and provides an explicit 'Use for...' clause with concrete scenarios, but the 'when' frames use-cases rather than natural user-mention trigger phrasing, so it could be more explicit.	4 / 5
Trigger Term Quality	Includes natural terms a domain user would say ('KEGG disease', 'drug targets', 'disease genes', 'drug repurposing'), but coverage is specialized with limited synonym variation, so a few natural terms are missing.	4 / 5
Distinctiveness Conflict Risk	Scoped to KEGG's specific disease-drug-variant databases with distinct triggers, creating a clear niche with minimal conflict risk against other skills.	5 / 5
	Total	18 / 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: plugin/skills/tooluniverse-kegg-disease-drug/SKILL.md
Commit: 7a0ceb2

Reviewed: 3 days ago

Table of Contents

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