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ngs-dna-variant-calling

Dispatch WGS, WES, or targeted DNA variant requests to germline, somatic, or UMI-panel skills, then plan public nf-core/sarek, GATK4, DeepVariant, samtools, or bcftools workflows.

65

Quality

77%

Does it follow best practices?

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SecuritybySnyk

Passed

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tessl review fix ./plugins/ngs-analysis/skills/ngs-dna-variant-calling/SKILL.md
SKILL.md
Quality
Evals
Security

Quality

Content

72%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 well-structured, actionable dispatcher body with concrete executable commands and clean sectioning. The main weaknesses are minor prose verbosity and the lack of an explicit validation feedback loop for batch calling.

Suggestions

Trim the resource-artifact prose in the Local Execution Package section to the essential flags and artifact names.

Add an explicit validate→fix→retry checkpoint (e.g. 'run preflight, resolve any install-plan gaps, then re-run preflight before kickoff') to lift workflow clarity to 3.

DimensionReasoningScore

Conciseness

Mostly lean and well-organized, but the Local Execution Package prose about resource_plan.json/resource_manifest.tsv artifacts and the dispatch narrative could be tightened; it is not fully token-minimal.

2 / 3

Actionability

Provides fully executable, copy-paste-ready commands — the preflight script invocation, the run_dna_variant_calling.py call with concrete flags, and the nextflow/sarek kickoff skeletons.

3 / 3

Workflow Clarity

A clear preflight-first sequence exists, but batch variant-calling operations lack an explicit validate→fix→retry feedback loop, so workflow clarity is capped at 2 per the guideline.

2 / 3

Progressive Disclosure

A single self-contained file with well-signaled sections (Essential Inputs, Dispatch, Preflight, Kickoff, Guardrails) and one-level-deep structure; no nested references and no bundle files to navigate.

3 / 3

Total

10

/

12

Passed

Description

82%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 specific, well-triggered dispatcher description that distinguishes itself from its subtype skills. Its main gap is the absence of an explicit 'Use when...' trigger clause, which caps completeness.

Suggestions

Append an explicit trigger clause such as 'Use when handling WGS, WES, or targeted DNA variant-calling requests from FASTQ/BAM/CRAM' to lift completeness to 3.

Mirror the natural phrasing a user would type (e.g. 'variant calling', 'germline/somatic variants') to keep trigger terms aligned with real requests.

DimensionReasoningScore

Specificity

Lists multiple concrete actions — 'Dispatch WGS, WES, or targeted DNA variant requests to germline, somatic, or UMI-panel skills, then plan public nf-core/sarek, GATK4, DeepVariant, samtools, or bcftools workflows' — naming both routing behavior and specific tools.

3 / 3

Completeness

It clearly states what the skill does (dispatch and plan workflows) but lacks an explicit 'Use when...' trigger clause, so per the guideline completeness is capped at 2.

2 / 3

Trigger Term Quality

Natural terms a genomics user would say are well covered: WGS, WES, targeted DNA, germline, somatic, UMI-panel, plus the named workflow tools.

3 / 3

Distinctiveness Conflict Risk

It carves a clear dispatcher niche (DNA variant calling by sample model) with distinct triggers unlikely to overlap with the subtype skills it routes to.

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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