ngs-chip-cutrun-peaks-qc

Run or plan ChIP-seq, CUT&RUN, or CUT&Tag QC, control handling, spike-in, peak calling, broad-vs-narrow target selection, replicate, bigWig, and differential binding workflows.

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.

Highly actionable and concise content with executable commands and clean sectioning, weakened only by the absence of an explicit error-recovery feedback loop for the batch QC/peak-calling pipeline.

Suggestions

Add an explicit validate-then-proceed gate (e.g., 'Only proceed to peak calling after confirming alignment rate, duplicate rate, and FRiP meet thresholds; if not, re-run with adjusted --peak-mode or duplicate policy').

Include a feedback loop for poor replicate concordance or weak enrichment (e.g., 'If replicate concordance fails, regenerate consensus peaks or flag the sample rather than proceeding to differential binding').

Make the resource-readiness check a blocking validation step before execution when reference bundles are missing, rather than advisory by default.

Dimension	Reasoning	Score
Conciseness	The body is dense and assumes Claude's competence with no concept padding (no 'what is ChIP-seq' exposition); every line is an actionable input, command, decision point, or output spec, so it is not the level-2 'could be tightened' case.	3 / 3
Actionability	Provides fully executable, copy-paste-ready commands with real flags (e.g., run_chip_cutrun_peaks_qc.py --assay chipseq --target-class tf --peak-mode narrow --bowtie2-index ... --execute) plus concrete emitted file paths, matching the 'fully executable code/commands; copy-paste ready' anchor.	3 / 3
Workflow Clarity	The workflow is sequenced (Essential Inputs -> preflight -> runner/nf-core -> Decision Points -> Outputs) with a confirm-checklist and a QC-metric review checkpoint, but for a batch pipeline there is no explicit validate->fix->retry feedback loop, which caps clarity at 2 per the batch-operations guideline; it is not 1 because the sequence and checkpoints are clearly present.	2 / 3
Progressive Disclosure	The skill is a self-contained, well-sectioned overview (Essential Inputs, Route, Decision Points, Outputs) with no nested or deep bundle references to navigate, so the organization alone earns the top level; it is not 2 because nothing that should be separate is awkwardly 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 specific, well-targeted description with strong natural trigger terms and a clear niche, but it omits any explicit 'when to use' guidance, which caps completeness at 2.

Suggestions

Append an explicit trigger clause such as 'Use when the user is running or planning ChIP-seq, CUT&RUN, or CUT&Tag QC, peak calling, or differential binding analysis.'

Add disambiguation guidance in the description (e.g., 'Use ngs-atacseq-peaks-qc for ATAC-seq') so the skill triggers only for antibody-based enrichment assays.

Dimension	Reasoning	Score
Specificity	Lists multiple concrete capabilities in third person ("Run or plan ... QC, control handling, spike-in, peak calling, broad-vs-narrow target selection, replicate, bigWig, and differential binding workflows"), matching the 'lists multiple specific concrete actions' anchor rather than the partial level 2.	3 / 3
Completeness	Clearly states what the skill does but provides no 'Use when ...' clause or equivalent explicit trigger guidance, so per the judging guidelines completeness is capped at 2; it is not 1 because the 'what' is strong and specific.	2 / 3
Trigger Term Quality	Uses the natural terms practitioners actually say (ChIP-seq, CUT&RUN, CUT&Tag, spike-in, peak calling, bigWig, differential binding), giving good coverage of likely user phrasing.	3 / 3
Distinctiveness Conflict Risk	The antibody-targeted enrichment niche (ChIP/CUT&RUN/CUT&Tag) is a clear, distinct set of triggers unlikely to fire for unrelated skills, matching the 'clear niche with distinct triggers' anchor.	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-chip-cutrun-peaks-qc/SKILL.md
Commit: 11c74d6

Reviewed: 17 days ago

Table of Contents

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