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locus-to-gene-mapper-skill

Map GWAS loci to ranked candidate genes using a deterministic multi-skill chain (EFO -> GWAS -> coordinates -> Open Targets L2G/coloc -> eQTL -> burden/coding context), with reproducible tables and optional figures. Use when a user provides a trait/EFO term and/or lead variants and needs locus-to-gene prioritization for downstream biology decisions.

68

Quality

81%

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SecuritybySnyk

Low

Low-risk findings worth noting

SKILL.md
Quality
Evals
Security

Quality

Content

77%Weight 40%Scale 1-3

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

A highly actionable and well-sequenced skill body with concrete commands, explicit scoring rules, and strong QC gates. It is held back by verbosity and weak progressive disclosure — large contract and seed-list detail belongs in reference files rather than inline.

Suggestions

Move the full JSON output contract, default seed rsID table, and figure contract into reference files (e.g. references/output_contract.md, references/default_seeds.md) and link to them one level deep from SKILL.md.

Trim the inline optional-input list to the most decision-relevant fields, deferring exhaustive defaults to the bundled script's --help or a reference doc.

Keep only a concise contract summary inline and signal where the full schema lives, reducing SKILL.md toward an overview.

DimensionReasoningScore

Conciseness

Largely efficient and free of explaining concepts Claude already knows, but the ~350-line body inlines large contracts (full JSON schema, default seed lists for seven traits, three figure specs) that do not all earn their place in SKILL.md.

2 / 3

Actionability

Provides executable run commands, a quick-start, minimal input JSON, a public interface signature, exact scoring formulas, and a verified bundled script — concrete and copy-paste ready.

3 / 3

Workflow Clarity

Clear mandatory skill-chaining order (steps 1-9) and pipeline phases 0-5 with an explicit Phase 5 QC-gate checkpoint and an autonomous retry loop on 'No anchors remained'.

3 / 3

Progressive Disclosure

Sections are well organized and the referenced bundled script (scripts/map_locus_to_gene.py) is a real file, but the heavy JSON contract, default seed table, and figure specs are inlined monolithically rather than split into one-level-deep reference files.

2 / 3

Total

10

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12

Passed

Description

85%Weight 40%Scale 1-3

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 with an explicit 'Use when...' trigger that clearly conveys both capability and invocation conditions. Its only weakness is technical jargon in the trigger terms, slightly limiting natural keyword coverage.

DimensionReasoningScore

Specificity

States multiple concrete actions — 'Map GWAS loci to ranked candidate genes', a named deterministic multi-skill chain, 'reproducible tables and optional figures' — rather than vague language.

3 / 3

Completeness

Explicitly answers both what (Map GWAS loci to ranked candidate genes) and when via an explicit 'Use when a user provides a trait/EFO term and/or lead variants...' trigger clause.

3 / 3

Trigger Term Quality

Includes relevant domain terms ('trait/EFO term', 'lead variants', 'locus-to-gene prioritization') but leans technical with limited plain-language variations users would naturally say.

2 / 3

Distinctiveness Conflict Risk

Occupies a clear niche (GWAS locus-to-gene prioritization via a named multi-skill chain) with distinct triggers 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
openai/plugins
Reviewed

Table of Contents

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