CtrlK
BlogDocsLog inGet started
Tessl Logo
SkillPublic

tooluniverse-population-genetics-1000genomes

Population genetics using the 1000 Genomes Project (IGSR) — superpopulation/population search, sample metadata, variant frequencies across AFR/AMR/EAS/EUR/SAS, ancestry-specific analyses. Use for ancestry comparison, population-aware allele frequency lookups, and 1000-Genomes-cohort-specific analyses (distinct from gnomAD which has different sample composition).

Quality

86%

Does it follow best practices?

Run evals on this skill

Adds up to 20 points to the overall score

View guide
SecuritybySnyk

Low

Low-risk findings worth noting

The canonical home for this skill is tooluniverse-population-genetics-1000genomes in mims-harvard/ToolUniverse

SKILL.md
Quality
Evals
Security

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.

A highly actionable, well-structured tool reference: concrete call examples for all six tools, useful factual tables, and a clear phased workflow with an error-prevention note. Its weaknesses are a verbose reasoning section that re-teaches known population-genetics concepts and some content that could be split into reference files.

Suggestions

Trim the 'Interpretation Guidance' bullets to the non-obvious calibration values (Fst > 0.3 threshold, r2 LD bands, N < 100 precision caveat) and drop the textbook definitions of Fst, LD, and stratification that Claude already knows.

Make workflow Step 4 concrete — show how to cross-reference (e.g., a short Python snippet joining GWAS rsIDs with population allele frequencies) instead of 'Cross-reference with population data for stratification analysis'.

Move the 'Reasoning Framework' and 'Common Population Codes' tables to a references/ file and link them from SKILL.md, reducing the monolithic ~230-line body and the partial duplication with the 'Tool Parameter Quick Reference'.

DimensionReasoningScore

Conciseness

The tool documentation, JSON examples, and code tables are tight and factual, but the 'Reasoning Framework for Result Interpretation' section spends ~30 lines explaining textbook population genetics Claude already knows ('Fst measures population differentiation (0 = no differentiation, 1 = complete fixation...)', 'Uncontrolled population structure in GWAS inflates false positives', 'AFR populations have shorter LD blocks'). This matches 'Mostly efficient but includes some unnecessary explanation or could be tightened'; it is not 4 because the padded conceptual explanation is a full section, not a minor instance, and not 2 because the bulk of the body is dense, non-padded reference material.

3 / 5

Actionability

Every tool gets exact parameter signatures, return shapes, and copy-paste-ready JSON call examples ('{"superpopulation": "AFR", "limit": 10}', '{"gene_symbol": "TCF7L2", "limit": 10}'), plus response examples and a worked workflow. This matches 'Fully executable; copy-paste ready code or commands; specific examples cover the common cases'; it is not 4 because there are no missing key details in the tool call guidance.

5 / 5

Workflow Clarity

The 'Workflow: Population Stratification in GWAS' section lays out a clear Steps 1-4 sequence, and the NOTE 'population takes a population code (e.g. "YRI"), not a superpopulation code' acts as an explicit error guard. It fits 'Clear sequence with most checkpoints present; minor validation gaps' — the workflow is read-only analysis so heavy validation loops are less critical, but Step 4 ('Cross-reference with population data for stratification analysis') is underspecified with no concrete method. Not 5 because there are no explicit validation/synthesis checkpoints inside the workflow itself, and not 3 because the sequence is concrete and guarded rather than leaving checkpoints merely implicit.

4 / 5

Progressive Disclosure

No bundle files exist (no references/, scripts/, assets/), so the skill is a single file; it is well-sectioned with clear headers (When to Use, NOT for, Phases 1-4, Workflow, code tables, quick reference) and easy to navigate. This matches 'Good structure; most content is appropriately placed; minor organization gaps': the reasoning framework and code tables are arguably reference-file material inlined in SKILL.md, and the trailing 'Tool Parameter Quick Reference' partially duplicates the phase sections. Not 5 because nothing is split out into clearly-signaled one-level-deep reference files; not 3 because organization is strong, references are not buried, and no content is misfiled.

4 / 5

Total

16

/

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 statements, an explicit 'Use for...' clause, and explicit boundary marking against gnomAD. The only gap is that GWAS/population-stratification use cases — prominent in the skill body — are absent from the description's trigger terms.

Suggestions

Add GWAS-related trigger terms (e.g., 'population stratification', 'GWAS ancestry analysis') to the description, since Phase 4 and the main workflow of the skill target exactly those requests.

DimensionReasoningScore

Specificity

The description lists multiple concrete actions — 'superpopulation/population search, sample metadata, variant frequencies across AFR/AMR/EAS/EUR/SAS, ancestry-specific analyses' — with comprehensive, domain-specific coverage and no vague filler. This matches the anchor 'Lists multiple specific concrete actions; comprehensive coverage'; it is not the level below because coverage of the skill's capabilities is broad rather than leaving 'minor gaps'.

5 / 5

Completeness

Both questions are explicitly answered: the 'what' is stated concretely (population/sample search, sample metadata, variant frequencies, ancestry-specific analyses) and the 'when' is an explicit 'Use for ancestry comparison, population-aware allele frequency lookups, and 1000-Genomes-cohort-specific analyses' clause with concrete trigger phrases. This matches the top anchor; it is not the level below because the 'when' is explicit and specific rather than merely present.

5 / 5

Trigger Term Quality

Natural terms users would say are well covered: '1000 Genomes', 'IGSR', 'population', 'superpopulation', 'ancestry comparison', 'population-aware allele frequency lookups', 'population genetics'. A few natural terms are missing — notably GWAS-related and population-stratification phrasing, even though the body devotes Phase 4 and a workflow to GWAS population stratification, so users asking those questions would not trigger on this description. This fits 'Good keyword coverage; a few natural terms missing' rather than the comprehensive-with-synonyms anchor.

4 / 5

Distinctiveness Conflict Risk

The description carves a clear niche (1000 Genomes / IGSR cohort) and actively de-conflicts with the nearest neighbor: 'distinct from gnomAD which has different sample composition'. Trigger terms (IGSR, 1000 Genomes, superpopulation codes) are unlikely to fire for other skills, matching the 'Clear niche with distinct triggers; minimal conflict risk' anchor.

5 / 5

Total

19

/

20

Passed

Validation

93%

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

CriteriaDescriptionResult

frontmatter_unknown_keys

Unknown frontmatter key(s) found; consider removing or moving to metadata

Warning

Total

15

/

16

Passed

Repository

mims-harvard/ToolUniverse

Path

plugins/tooluniverse/skills/tooluniverse-population-genetics-1000genomes/SKILL.md

Reviewed

Table of Contents

Is this your skill?

If you maintain this skill, you can claim it as your own. Once claimed, you can manage eval scenarios, bundle related skills, attach documentation or rules, and ensure cross-agent compatibility.