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tooluniverse-variant-analysis

VCF and variant analysis — parsing, annotation, classification (synonymous, missense, frameshift, stop_gained), VAF filtering, coding vs non-coding categorization, multi-condition variant comparison. Use for VCF parsing, variant fraction calculations (denominator = coding subset only, NOT all variants), and per-sample mutation profiling.

66

Quality

80%

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SecuritybySnyk

Low

Low-risk findings worth noting

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tessl review fix ./plugins/tooluniverse/skills/tooluniverse-variant-analysis/SKILL.md
SKILL.md
Quality
Evals
Security

Quality

Content

67%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 dense, domain-expert body with genuinely valuable gotchas and strong executable script invocations, undermined by redundancy (the coding-denominator rule appears three times), a CRISPR primer of background knowledge, one broken reference (QUICK_START.md), and Python pattern examples whose functions are not in the bundle. Deduplicating and moving the tool/phase tables into the existing references would lift both conciseness and progressive disclosure.

Suggestions

State the coding-only denominator rule once (in Analysis Conventions) and reference it from the script table and CRITICAL section instead of repeating it three times; same for the 2-row Excel header guidance.

Fix or remove the 'QUICK_START.md' reference in Additional Resources — the file does not exist in the bundle.

Clarify the provenance of the Python pattern functions (answer_vaf_mutation_fraction, FilterCriteria, variant_analysis_pipeline, parse_vcf) — either note they are ToolUniverse tools or provide runnable equivalents in scripts/, since none are defined in the bundled scripts.

DimensionReasoningScore

Conciseness

Mostly efficient domain-specific gotchas (ploidy defaults, 2-row VarSeq headers, coding denominators) that earn their tokens, but at ~500 lines the body is noticeably padded: the coding-only denominator rule is stated three times (PRIMARY SCRIPTS table, CRITICAL section, Analysis Conventions), multi-row Excel headers are explained twice, and the CRISPR section re-explains PAM/NGG basics Claude already knows. Fits 'mostly efficient but includes some unnecessary explanation or could be tightened'; not 2 because the bulk is genuinely non-obvious operational knowledge rather than generic filler.

3 / 5

Actionability

The three primary scripts get exact copy-paste bash invocations with flags, workdir, and named output keys to grep ('SNP_COUNT_ALLELES', 'AVERAGE_PER_SAMPLE'), which is fully executable. However, the Python pattern examples call functions (answer_vaf_mutation_fraction, variant_analysis_pipeline, parse_vcf, FilterCriteria) that are not defined in any bundled script and whose provenance (ToolUniverse tools vs local code) is never made explicit — a minor gap. Matches 'Mostly executable guidance; concrete code or commands with minor gaps'; not 5 because those examples cannot be run as written.

4 / 5

Workflow Clarity

Sequencing is clear and prioritized (RULE ZERO check-first → PRIMARY SCRIPTS → domain recipes → phase workflow) with some real checkpoints (the ~0.4 synonymous-fraction sanity check with a recompute loop, 'PLOIDY=<value>' emitted for confirmation, report-all-three-conventions sensitivity). Fits 'Clear sequence with most checkpoints present; minor validation gaps'; not 5 because there are three competing entry paths (phases, scripts-first, RULE ZERO) with no single explicit order among them, and the phase workflow itself lacks validation steps.

4 / 5

Progressive Disclosure

Good structure: four real one-level-deep reference files (references/vcf_filtering.md, mutation_classification_guide.md, annotation_guide.md, sv_cnv_analysis.md — all verified present) clearly signaled inline and in a Reference Documentation section, plus six bundled scripts documented with a usage table. Minor gaps keep it from 5: 'QUICK_START.md' is referenced under Additional Resources but does not exist in the bundle, and a fair amount of reference-grade material (full tool tables, phase-by-phase detail) is inlined in an already-long SKILL.md.

4 / 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 list plus an explicit 'Use for' trigger clause covering the skill's canonical question patterns. The only weakness is modest synonym coverage (missing '.vcf', 'SNV/indel', 'variant calling') that keeps trigger quality just below comprehensive.

DimensionReasoningScore

Specificity

Quotes like "parsing, annotation, classification (synonymous, missense, frameshift, stop_gained), VAF filtering, coding vs non-coding categorization, multi-condition variant comparison" list multiple concrete, comprehensive actions with named variant types — matching the anchor 'Lists multiple specific concrete actions; comprehensive coverage'. Not 4 because coverage has no meaningful gaps; the parenthetical SO terms make the actions unusually concrete.

5 / 5

Completeness

The 'what' is explicit and detailed ("VCF and variant analysis — parsing, annotation, classification..., VAF filtering...") and the 'when' is an explicit 'Use for' clause with concrete triggers ("Use for VCF parsing, variant fraction calculations..., and per-sample mutation profiling"). This matches the anchor 'Clearly and explicitly answers both what AND when with concrete trigger phrases'; the explicit trigger guidance also avoids the ≤3 cap.

5 / 5

Trigger Term Quality

"VCF parsing", "variant fraction calculations", "per-sample mutation profiling", and the named consequence terms are natural phrasings, but common synonyms/extensions users would say are missing — e.g. ".vcf", "SNV/indel", "variant calling". Matches 'Good keyword coverage; a few natural terms missing'; not 5 because the synonym/extension coverage is not comprehensive, and not 3 since far more than 'some relevant keywords' are present.

4 / 5

Distinctiveness Conflict Risk

"VCF", "VAF filtering", "coding vs non-coding categorization", and named SO consequence terms carve out a clear niche (variant analysis) with distinct triggers and minimal overlap with adjacent genomics skills. Not 4 because no closely related skill's triggers plausibly collide with these terms.

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

skill_md_line_count

SKILL.md is long (503 lines); consider splitting into references/ and linking

Warning

Total

15

/

16

Passed

Repository
mims-harvard/ToolUniverse
Reviewed

Table of Contents

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