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ngs-epigenomics-peaks

Dispatch ATAC-seq, ChIP-seq, CUT&RUN, or CUT&Tag requests to assay-specific QC, alignment, signal-track, peak-calling, consensus, and differential peak workflows.

60

Quality

76%

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tessl review fix ./plugins/ngs-analysis/skills/ngs-epigenomics-peaks/SKILL.md
SKILL.md
Quality
Evals
Security

Quality

Content

68%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 lean, command-heavy dispatcher body that is largely copy-paste actionable and clearly organized by assay. Its main weaknesses are implicit validation (the readiness gate is described as an output but not as a checkpoint) and a BAM/direct-MACS2 path with no concrete command.

Suggestions

Add an explicit validation checkpoint after preflight, e.g. 'Review peak_calling_readiness.json; resolve flagged samples before kickoff' with a retry loop on failure.

Provide a concrete MACS2 command example for the focused peak-calling-from-prepared-BAMs path.

Replace the changelog phrasing ('now also emit') with a plain statement of outputs, and trim the description of what the shared FASTQ package validates.

DimensionReasoningScore

Conciseness

The body is dominated by copy-paste commands and terse checklists with almost no padding, and it assumes Claude's competence (no explanation of what ATAC-seq or peak calling is). Minor trimmable spots remain: the sentence describing what the package 'validates... runs seqkit stats and FastQC/MultiQC' and the changelog-style 'now also emit' phrasing, so it sits at the 4 anchor rather than the 5 anchor where every token earns its place.

4 / 5

Actionability

Concrete executable commands throughout: the preflight invocation with flags, the run_fastq_assay_package.py call with arguments, and three complete Nextflow kickoff commands covering all assay families. It falls short of 5 because the 'direct MACS2' path for prepared BAMs has no command, and there is no example of interpreting the emitted peak_calling_readiness.json.

4 / 5

Workflow Clarity

The sequence is present and readable (confirm inputs, choose workflow by assay, preflight, FASTQ package, kickoff), but validation is implicit: peak_calling_readiness.json is mentioned as an output yet there is no explicit checkpoint or feedback loop saying what to check or what to do when preflight fails. For a batch NGS pipeline without an explicit validation checkpoint, the rubric caps this at 3; it does not reach 4 because the checkpoints are missing rather than merely having minor gaps.

3 / 5

Progressive Disclosure

Sections are well organized with a clear dispatcher role and explicit handoff to named assay-specific skills, and the body stays a lean overview rather than inlining workflow detail. It does not reach 5 because the referenced script paths (plugins/ngs-analysis/scripts/...) live outside the bundle with no local reference files, and there are no clearly signaled reference docs for the delegated assay workflows.

4 / 5

Total

15

/

20

Passed

Description

71%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, specific description that names the domain, four assays, and six concrete workflow stages with natural trigger terms. Its main weakness is the absence of an explicit 'Use when...' clause, which caps completeness, and inherent overlap with the assay-specific sub-skills it dispatches to.

Suggestions

Append an explicit trigger clause, e.g. 'Use when the user mentions ATAC-seq, ChIP-seq, CUT&RUN, CUT&Tag, chromatin accessibility, histone marks, or needs peaks/bigWigs/differential peak analysis.'

Add natural synonym terms like 'epigenomics', 'chromatin accessibility', or 'FASTQ/BAM' to broaden trigger coverage.

Clarify the dispatcher's role vs. the assay-specific sub-skills so it is distinguishable from them at trigger time.

DimensionReasoningScore

Specificity

The description lists six concrete pipeline actions ('QC, alignment, signal-track, peak-calling, consensus, and differential peak workflows') across four named assays, comprehensively covering the epigenomics peak-analysis workflow stages. This matches the 5 anchor (multiple specific concrete actions, comprehensive coverage) rather than 4, which allows minor gaps in coverage.

5 / 5

Completeness

The 'what' is clear (dispatch to assay-specific QC/alignment/peak workflows) but there is no 'Use when...' clause or equivalent explicit trigger guidance; the assay names only weakly imply when to use it. Per the judging guidelines, a missing 'Use when' clause caps completeness at 3, so it cannot reach 4 despite the strong 'what'.

3 / 5

Trigger Term Quality

'ATAC-seq, ChIP-seq, CUT&RUN, or CUT&Tag' plus 'peaks' are exactly the natural terms users would say, giving good keyword coverage. Falls short of the 5 anchor because common variations like 'epigenomics', 'chromatin accessibility', 'histone', or FASTQ/BAM file terms are missing.

4 / 5

Distinctiveness Conflict Risk

It has a clear niche (epigenomics peak analysis for four named assays) with distinct technical triggers, but as a dispatcher its trigger terms are identical to the assay-specific sub-skills it routes to (e.g. ngs-atacseq-peaks-qc), creating minor overlap risk with closely related skills. This fits the 4 anchor better than 5 (minimal conflict risk) or 3 (overlap with many similar skills).

4 / 5

Total

16

/

20

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.

Validation — 16 / 16 Passed

Validation for skill structure

No warnings or errors.

Repository

openai/plugins

Path

plugins/ngs-analysis/skills/ngs-epigenomics-peaks/SKILL.md

Reviewed

Table of Contents

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