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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

85%

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SecuritybySnyk

Low

Low-risk findings worth noting

SKILL.md
Quality
Evals
Security

Quality

Content

70%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 and workflow sequencing with QC gates is excellent, but the skill front-loads implementation detail — full output schemas, scoring formulas, and seed tables — into SKILL.md that belongs in reference files, hurting both token efficiency and progressive disclosure. Fixing the script-path inconsistency in the run examples would close the main actionability gap.

Suggestions

Move the full JSON output contract, figure contract, scoring rules, and default-seed table into references/ files (e.g., OUTPUT_CONTRACT.md, SCORING.md) and link to them, keeping SKILL.md as a lean overview plus quick-start.

Fix the run-command path to match the actual bundle layout (scripts/map_locus_to_gene.py rather than locus-to-gene-mapper-skill/scripts/...), and collapse the duplicated run/quick-start examples into one.

Replace the signature-only public-interface stub with either a real usage example or a pointer to the script's argparse help.

DimensionReasoningScore

Conciseness

The body is mostly contractual and free of concept explanations Claude already knows, but ~350 lines re-specify material the bundled script already implements — a full inline JSON output contract (~60 lines), the deterministic scoring formula, default-seed tables, and a phase-by-phase pipeline contract. This matches anchor 3 ('mostly efficient but includes some... could be tightened') rather than 4, since large blocks could be trimmed or moved rather than minor instances.

3 / 5

Actionability

Guidance is mostly executable: copy-paste run commands with flags, a quick-start path requiring no input file, a minimal input JSON example, and a real bundled entrypoint (scripts/map_locus_to_gene.py exists). It stops short of anchor 5 because the run command uses the path 'locus-to-gene-mapper-skill/scripts/...' which is inconsistent with the actual bundle layout, and the public interface snippet is a signature-only stub rather than usable code.

4 / 5

Workflow Clarity

The pipeline is explicitly sequenced (Phase 0–5) with an error-recovery feedback loop ('If it returns No anchors remained, rerun once with a built-in default seed rsID') and a Phase 5 QC gate list enumerating concrete failure conditions. This matches anchor 5: clear sequence, explicit validation steps, and feedback loops for error recovery.

5 / 5

Progressive Disclosure

Section headers are clear and the primary detail (execution) is properly delegated to the bundled script, but there are no reference files at all, while large contract blocks (output JSON schema, figure contract, seed table, scoring rules) sit inline in SKILL.md where they belong in one-level-deep references. This matches anchor 3 ('some structure but could be better organized; content that should be separate is inline') rather than 4, because the split is missing rather than a minor gap.

3 / 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: concrete third-person capability statement, explicit 'Use when' trigger clause with specific input conditions, and domain-accurate terminology. The only weakness is slightly thin synonym coverage of adjacent phrasings users might employ.

Suggestions

Add one or two user-voice synonyms (e.g., 'gene prioritization', 'colocalization', 'post-GWAS fine-mapping') to broaden natural trigger matching.

Optionally mention input file types or output formats (JSON/markdown report) users might ask for by name.

DimensionReasoningScore

Specificity

The description lists multiple concrete actions — 'Map GWAS loci to ranked candidate genes', 'deterministic multi-skill chain (EFO -> GWAS -> coordinates -> Open Targets L2G/coloc -> eQTL -> burden/coding context)', 'reproducible tables and optional figures' — with comprehensive coverage of what the skill produces. It exceeds anchor 4 ('lists several specific actions; minor gaps') because the action set plus outputs and evidence chain are fully enumerated in third person.

5 / 5

Completeness

It explicitly answers both what ('Map GWAS loci to ranked candidate genes... with reproducible tables and optional figures') and when ('Use when a user provides a trait/EFO term and/or lead variants and needs locus-to-gene prioritization for downstream biology decisions'). This matches anchor 5 exactly: a concrete 'what' plus an explicit 'Use when' clause with concrete trigger conditions.

5 / 5

Trigger Term Quality

Natural domain terms are present — 'GWAS loci', 'trait/EFO term', 'lead variants', 'locus-to-gene prioritization', 'candidate genes' — which a genetics user would actually say. It falls short of anchor 5 ('comprehensive coverage of natural terms including synonyms') because common variants like 'colocalization', 'fine-mapping', or 'gene prioritization' phrasings are only covered via the parenthetical skill chain, not as standalone trigger words.

4 / 5

Distinctiveness Conflict Risk

The GWAS locus-to-gene niche is clear with distinct triggers (trait/EFO terms, lead variants, L2G/coloc/eQTL) that no generic skill would match, satisfying anchor 5's 'clear niche with distinct triggers; minimal conflict risk'. Not 4 because it does not merely overlap with related skills — the chained evidence types uniquely identify this skill.

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.

Validation — 16 / 16 Passed

Validation for skill structure

No warnings or errors.

Repository

openai/plugins

Path

plugins/life-science-research/skills/locus-to-gene-mapper-skill/SKILL.md

Reviewed

Table of Contents

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