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tooluniverse-gwas-drug-discovery

Transform GWAS signals into drug targets and repurposing opportunities. Connects GWAS-significant loci to causal genes via fine-mapping/eQTL, then to druggable proteins via DGIdb/OpenTargets, then to existing drugs via ChEMBL. Use for GWAS-to-target hypothesis generation, druggable-fraction analysis of disease loci, and human-genetics-validated drug-repurposing prioritization.

64

Quality

75%

Does it follow best practices?

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SecuritybySnyk

Low

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tessl review fix ./plugin/skills/tooluniverse-gwas-drug-discovery/SKILL.md
SKILL.md
Quality
Evals
Security

Quality

Content

65%

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

A highly actionable, domain-rich skill body with concrete code and parameter guidance. Its weak spots are redundant tool listings and a Reference Files section that points to files that are not bundled.

Suggestions

Deduplicate the tool listings: keep tools in the Workflow Steps and remove or shrink the repeated 'All Tools by Category' section.

Either create the referenced files (REFERENCE.md, EXAMPLES.md, REPORT_TEMPLATE.md, PROCEDURES.md, QUICK_START.md) or remove the dangling references.

Add inline validation checkpoints to the workflow (e.g., 'if no GWAS hits, broaden the trait before proceeding') instead of relegating all error handling to the Troubleshooting table.

DimensionReasoningScore

Conciseness

Much of the body is genuinely novel domain knowledge (gotchas, decision trees), but tools are listed two to three times (Workflow Steps, All Tools by Category, Quick Start) and the Overview re-lists steps that are expanded below, so it could be tightened.

2 / 3

Actionability

The Quick Start gives executable Python with real tool calls and inline gotcha comments, and the Parameter Gotchas table contrasts wrong vs correct usage — copy-paste ready.

3 / 3

Workflow Clarity

Six numbered steps with inputs, processes, and tools give a clear sequence, but there are no integrated validation/feedback checkpoints; error handling lives only in a separate Troubleshooting table.

2 / 3

Progressive Disclosure

In-file sections are well organized and a Reference Files list is signaled, but the five referenced files (REFERENCE.md, EXAMPLES.md, etc.) do not exist and detailed content (interpretation, examples) remains inline rather than split out.

2 / 3

Total

9

/

12

Passed

Description

85%

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 specific, third-person description with an explicit trigger clause and named tools. Its main weakness is jargon-heavy trigger phrasing that users would rarely say verbatim.

Suggestions

Rewrite the 'Use for ...' triggers in plainer user language (e.g., 'Use when turning GWAS results into drug target candidates or finding repurposing candidates backed by human genetics').

Add a couple of common natural variations such as 'GWAS to drug target' and 'drug repurposing from GWAS' alongside the technical terms.

DimensionReasoningScore

Specificity

Lists multiple concrete actions with named tools: 'Connects GWAS-significant loci to causal genes via fine-mapping/eQTL, then to druggable proteins via DGIdb/OpenTargets, then to existing drugs via ChEMBL.'

3 / 3

Completeness

Clearly answers both what (the GWAS-to-drug pipeline) and when, with an explicit 'Use for ...' trigger clause, so it is not capped at 2.

3 / 3

Trigger Term Quality

Relevant keywords (GWAS, drug targets, repurposing) appear, but trigger phrases like 'druggable-fraction analysis of disease loci' and 'human-genetics-validated drug-repurposing prioritization' are technical jargon rather than natural user utterances, and common variations are missing.

2 / 3

Distinctiveness Conflict Risk

A highly specific GWAS-to-drug-target niche with distinct triggers makes it unlikely to fire for unrelated skills.

3 / 3

Total

11

/

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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