ngs-scrna-seq

Route single-cell or single-nucleus RNA-seq FASTQs to public count-generation workflows and defer post-count matrix QC, annotation, clustering, and UMAP analysis to the embedded scrna-seq-qc skill.

Quality

85%

Does it follow best practices?

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Securityby

Passed

No findings from the security scan

Quality

Content

87%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 concise, highly actionable skill body with clear sequencing and clean structure; its main weakness is the absence of an explicit validation feedback loop within the count-generation workflow.

Suggestions

Add an explicit validation checkpoint after FASTQ-to-count (e.g., check resource_readiness.md / resource_plan.json and re-run preflight if incomplete) to lift workflow_clarity to 3.

Make the preflight install-plan loop explicit: install missing requirements, then re-run preflight before kickoff.

Dimension	Reasoning	Score
Conciseness	The body is lean and assumes Claude's domain competence — it never explains what scRNA-seq, Cell Ranger, or UMAPs are, and every section earns its place, matching the level-3 anchor.	3 / 3
Actionability	Provides fully executable, copy-paste-ready bash commands with concrete flags and paths (ngs_preflight.py, run_nfcore_pipeline.py, run_scrnaseq_fastq_to_count.py) and lists the exact output artifacts each runner emits, matching the level-3 anchor.	3 / 3
Workflow Clarity	The three ordered rows give a clear sequence and the preflight acts as a readiness gate, but there is no explicit validate→fix→retry feedback loop for the FASTQ-to-count execution, so the level-3 checkpoint anchor is not fully met.	2 / 3
Progressive Disclosure	Well-organized into focused sections with only a one-level-deep reference to the embedded scrna-seq-qc skill and no nested reference chains; with no bundle files present the content is appropriately kept inline.	3 / 3
	Total	11 / 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 highly specific, well-scoped description with strong trigger terms and clear distinctiveness, but it lacks an explicit "Use when..." trigger clause, capping completeness at 2.

Suggestions

Add an explicit trigger clause such as "Use when starting scRNA-seq or snRNA-seq from FASTQs, count matrices, .h5/.h5ad/.rds files, or Cell Ranger outputs" to raise completeness to 3.

Lead with the primary action verb in third person and keep the existing deferral sentence to preserve the clean separation from the scrna-seq-qc skill.

Dimension	Reasoning	Score
Specificity	Names multiple concrete actions in a specific domain — "Route single-cell or single-nucleus RNA-seq FASTQs to public count-generation workflows and defer post-count matrix QC, annotation, clustering, and UMAP analysis" — matching the level-3 anchor that lists several specific actions.	3 / 3
Completeness	It clearly answers "what" the skill does but the "when to use it" trigger is only implied; there is no explicit "Use when..." clause, which the rubric caps at 2.	2 / 3
Trigger Term Quality	Uses natural terms a user would actually say for this domain — "single-cell", "single-nucleus", "RNA-seq", "FASTQs", "QC", "annotation", "clustering", "UMAP" — giving good coverage rather than generic jargon.	3 / 3
Distinctiveness Conflict Risk	It carves out a clear niche (FASTQ-to-count routing for sc/snRNA-seq) and explicitly defers post-count QC/annotation/UMAP to the embedded scrna-seq-qc skill, making conflict with sibling skills unlikely.	3 / 3
	Total	11 / 12 Passed

Validation

100%

Warnings & errors only

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/ngs-analysis/skills/ngs-scrna-seq/SKILL.md
Commit: 11c74d6

Reviewed: 17 days ago

Table of Contents

Discovery Implementation Validation

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