Conciseness

The body is noticeably verbose and padded: the description is repeated verbatim in both "When to Use" and "Key Features", the Overview re-explains what volcano plots are, and large generic boilerplate sections (Output Requirements, Response Template, Risk Assessment, Lifecycle Status) add little skill-specific value; not a 1 because there are useful parameter tables and concrete commands mixed in.

Actionability

It provides concrete executable guidance — an "Audit-Ready Commands" block (`python -m py_compile scripts/main.py`, `python scripts/main.py --input deg_results.csv --output volcano_plot.png`), a full parameters table with defaults, and a real packaged `scripts/main.py`; not a 5 because the "Usage" code fence is misformatted (a shell command inside a python block) and a few minor execution details are left implicit.

Workflow Clarity

The "Workflow" section gives a clear 5-step sequence with explicit checkpoints ("stop early if the task would require unsupported assumptions", fallback path on failure) and the "Quick Check" / "Audit-Ready Commands" supply concrete validation; not a 5 because the workflow steps are largely generic process boilerplate rather than volcano-plot-specific, leaving minor validation specificity gaps.

Progressive Disclosure

Structure is good and references are real and one-level-deep: `scripts/main.py`, `assets/example_volcano.R`, and `references/` (best_practices.md, example_deg_data.csv, markers.txt) all exist and are signaled in the body; not a 5 because substantial content (security checklist, lifecycle, test cases) is inlined in SKILL.md that could be split out, leaving minor organization gaps.

Specificity

Names the domain and several concrete deliverables — "Generate R/Python code for volcano plots", "p-value vs fold-change scatter plots", "publication-ready figures" — which is several specific actions with only minor coverage gaps; not a 5 because the actions are overlapping variants of one plot-generation task rather than multiple distinct capabilities.

Completeness

It explicitly answers both halves — "what" (Generate R/Python code for volcano plots from DEG results) and "when" ("Triggered when user needs visualization of gene expression data, p-value vs fold-change scatter plots, publication-ready figures"), matching the 5 anchor pattern of concrete trigger phrases; voice is correctly third person with no penalty.

Trigger Term Quality

Good natural-term coverage for the audience ("volcano plots", "DEG", "gene expression data", "publication-ready figures", "bioinformatics"), but it is missing common synonyms and file extensions like "RNA-seq", "differential expression", or ".csv", keeping it just below the comprehensive 5 anchor.

Distinctiveness Conflict Risk

Volcano plots from DEG analysis is a clear niche with distinct triggers and low conflict risk, but there is minor overlap with broader bioinformatics plotting/visualization skills, so it sits at the mostly-distinct 4 anchor rather than the minimal-conflict 5.