Conciseness

The body is dense and checklist/table-driven with almost no padding — hypothesis template, weak/strong example, test-type table, checklists, interpretation tables. Only minor instances of over-explaining what Claude already knows: '95% confidence = p-value < 0.05 / Means <5% chance result is random' and 'The Peeking Problem' paragraph restating the DON'T list. This fits anchor 4 (efficient, minor instances that could be trimmed) rather than anchor 3, since the textbook-statistics asides are a small fraction of 300 otherwise-earning-their-place lines.

Actionability

Guidance is largely concrete — copy-paste calculator commands ('python3 scripts/sample_size_calculator.py --baseline 0.05 --mde 0.20 --json'), a fill-in hypothesis template, explicit DO/DON'T lists, and a 6-item analysis checklist — but the centerpiece executable instruction ('Use this skill's own calculator — don't eyeball it') targets a script that does not exist in the bundle, so running it verbatim fails. This sits between anchor 3 (concrete but incomplete, missing key details) and anchor 4; the broken primary tool tips it to 3 rather than 4.

Workflow Clarity

The sections sequence a full lifecycle (assess → hypothesis → design → sample size → implement → run → analyze → document) with explicit checkpoints in the Pre-Launch Checklist, the DO/DON'T during-test rules, and the ordered Analysis Checklist ('Reach sample size?', 'Statistically significant?', 'Guardrail concerns?'). Anchor 5 requires explicit error-recovery feedback loops, which are absent (e.g., no 'if tracking verification fails, fix before launch' loop), so anchor 4 (clear sequence, most checkpoints, minor validation gaps) is the best fit.

Progressive Disclosure

Structure is good on paper: quick-reference tables inline, detailed material delegated one level deep and clearly signaled ('For detailed sample size tables and duration calculations: See references/sample-size-guide.md', 'For templates: See references/test-templates.md'). However, the referenced files — references/sample-size-guide.md, references/test-templates.md, and scripts/sample_size_calculator.py — do not exist in the bundle, so the promised navigation dead-ends. Well-signaled but non-functional references place this at anchor 3 rather than anchor 4.

Specificity

The description names the domain and the actions 'plan, design, or implement an A/B test or experiment', but these are generic verbs — it never enumerates the skill's concrete capabilities (hypothesis framing, sample-size calculation, variant design, results analysis). This matches anchor 3 (domain plus 1-2 actions, not comprehensive) better than anchor 4, which expects several specific listed actions; it also exceeds anchor 2 since the domain is named precisely.

Completeness

Both what and when are explicit: the what ('plan, design, or implement an A/B test or experiment') and the when ('When the user wants to...' plus 'Also use when the user mentions...' followed by concrete trigger phrases). It parallels the anchor-5 example structure exactly; anchor 4 would require the when to be less explicit, which it is not.

Trigger Term Quality

Comprehensive natural-term coverage with synonyms: "A/B test," "split test," "experiment," "test this change," "variant copy," "multivariate test," "hypothesis," "conversion experiment," "statistical significance," and "test this" — phrases a user would naturally say. This matches anchor 5 (comprehensive coverage including synonyms) and clearly exceeds anchor 4 (a few terms missing).

Distinctiveness Conflict Risk

The A/B-testing niche is clear with distinct triggers, but broad phrases like "test this," "experiment," and "hypothesis" could overlap with code-testing or general analytics skills (minor overlap risk), matching anchor 4. The explicit boundary handoff ('For tracking implementation, see analytics-tracking') reduces conflict, keeping it above anchor 3 but below anchor 5's minimal-conflict bar.