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tooluniverse-population-genetics

Population genetics analysis — allele frequencies (gnomAD, 1000 Genomes), Hardy-Weinberg equilibrium testing, Fst between populations, GWAS associations, evolutionary constraint scores. Use for cross-population variant comparison, ancestry-aware allele frequency lookups, and population-level evolutionary analysis.

70

Quality

85%

Does it follow best practices?

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SecuritybySnyk

Passed

No findings from the security scan

The canonical home for this skill is tooluniverse-population-genetics in mims-harvard/ToolUniverse

SKILL.md
Quality
Evals
Security

Quality

Content

71%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 concrete tools, parameters, and formulas, and offers clear ordered workflows for the framework-based tasks. It is held back by length/redundancy and by inlining large reference-style sections that would benefit from being split into separate files.

Suggestions

Consolidate the repeated 'preferred tool / fallback script' guidance into a single section to remove redundancy and trim length.

Move the Theoretical Reasoning and trap-catalog sections into one-level-deep reference files (e.g. THEORY.md, TRAPS.md) and link to them from SKILL.md to improve progressive disclosure.

Add an explicit verification/checkpoint step to the primary lookup workflows (e.g. confirm variant_id format resolved, sanity-check allele-frequency ranges) to close the validation gap.

DimensionReasoningScore

Conciseness

The body is information-dense and avoids generic padding, but it runs ~350 lines and repeats tool-preference guidance across several sections, with some conceptual exposition that could be tightened.

3 / 5

Actionability

Provides concrete tool names with exact required parameters, executable CLI invocations (e.g. 'popgen_calculator.py --type hwe --AA N1 --Aa N2 --aa N3'), worked formula examples, and copy-paste-ready tool-chain workflows.

5 / 5

Workflow Clarity

Sequenced workflow patterns and ordered Mendelian/Hfr frameworks with explicit validation steps (e.g. 'Verify ratios sum to 1.0') and MCQ feedback loops are strong; the primary lookup workflows lack explicit post-query verification checkpoints, leaving a minor gap.

4 / 5

Progressive Disclosure

Headers give reasonable structure and the bundled script is correctly referenced, but substantial theoretical-reasoning and trap-catalog content is inlined rather than split into one-level-deep reference files.

3 / 5

Total

15

/

20

Passed

Description

100%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 concrete, action-oriented, and explicitly pairs a 'what' capability list with a 'Use for...' trigger clause, hitting all four dimensions at the top anchor. It uses third-person voice and natural domain terminology without fluff.

DimensionReasoningScore

Specificity

Lists multiple concrete actions — allele frequencies, Hardy-Weinberg testing, Fst, GWAS associations, evolutionary constraint scores — plus concrete use-cases, giving comprehensive coverage of capabilities.

5 / 5

Completeness

Explicitly answers both what (the capability list) and when via 'Use for cross-population variant comparison, ancestry-aware allele frequency lookups, and population-level evolutionary analysis.'

5 / 5

Trigger Term Quality

Covers the natural terms population-genetics users actually say — gnomAD, 1000 Genomes, Hardy-Weinberg, Fst, GWAS, ancestry-aware allele frequency lookups — with near-comprehensive synonyms and dataset names.

5 / 5

Distinctiveness Conflict Risk

Occupies a clear population-genetics niche with triggers tied to named datasets and metrics, making overlap with unrelated skills minimal.

5 / 5

Total

20

/

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.

Validation16 / 16 Passed

Validation for skill structure

No warnings or errors.

Repository
mims-harvard/ToolUniverse
Reviewed

Table of Contents

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