Conciseness

The body re-explains concepts Claude already knows — "Simpson's paradox is when 'a trend appears in several groups of data but disappears or reverses when the groups are combined'", "A 95% confidence interval gives the plausible range of the true effect", and the novelty/primacy definitions — and pads with repeated citation parentheticals ("(Nielsen Norman Group, [sources](references/sources.md))" appears 9 times; the Kohavi ISBN three times). Mostly efficient operational tables and checklists, so this fits anchor 3 rather than anchor 2's padded prose, but it could clearly be tightened.

Actionability

Concrete decision rules throughout: the CI-position table ("Entirely above zero and above MPSE | Strong positive - candidate for ship"), specific thresholds ("Minimum run time: two full weeks", "a negative segment that represents > 20% of users"), an ordered guardrail procedure with explicit stop conditions, and a fully worked numeric example ("lift = +1.2pp (95% CI: +0.3pp, +2.1pp)") covering the common case. For an instruction-only skill this is copy-paste-ready guidance; the statistical computation details are properly delegated to references/significance-check.md rather than missing.

Workflow Clarity

Six steps in explicit order with an enforced gate — "Each step has a hard stop: if a step blocks, do not proceed to the next" — plus a numbered guardrail check with "(STOP - no-ship)" checkpoints and recovery paths ("extend experiment", "accepted risk + rationale"), and a worked example that walks the same sequence. Matches anchor 5's explicit validation steps, feedback loops, and checklists; this is an analysis/decision skill, so the destructive/batch cap does not apply.

Progressive Disclosure

Good structure with clearly signaled one-level-deep links (references/significance-check.md, references/guardrails.md, references/peeking.md, references/thresholds-and-corrections.md, references/sources.md) and a References section. However, two real bundle files — references/significance-anti-patterns.md and references/significance-output-example.md — are never referenced from SKILL.md, a discoverability gap, and the ~300-line body inlines some methodology detail (Step 3 novelty detection, Step 6 anti-pattern table) that could live in references. Fits anchor 4's 'minor organization gaps', not 5.

Specificity

"Computes significance per metric with multiple-comparison correction", "reads confidence intervals", and "checks novelty, interactions, Simpson's paradox, guardrails and stop-early rules" list multiple concrete actions covering the entire interpretation workflow. Matches anchor 5's comprehensive coverage; not 4, since the action list spans every step of the skill with no coverage gaps.

Completeness

Explicit 'when' — "Use for any question about reading an A/B test or experiment result, including quick ones" — paired with an explicit 'what' listing the concrete capabilities and the ship-decision framing. Clearly matches anchor 5 (both what and when with concrete trigger phrases); not 4, since neither half is implicit or underspecified.

Trigger Term Quality

The description embeds literal natural user questions — "is it significant, should we ship variant B, why a week-one win faded" — alongside domain terms "A/B test" and "experiment result", matching anchor 5's comprehensive natural-term coverage including question-form synonyms. Not 4: the question-form triggers go beyond anchor 4's 'good keyword coverage with a few missing', covering exactly what a user would say when they need this skill.

Distinctiveness Conflict Risk

The post-hoc interpretation/ship-decision niche is well carved out, but "Use for any question about reading an A/B test or experiment result, including quick ones" is aggressive breadth that overlaps closely related skills — e.g., the companion `ab-test-validity-checklist` covering experiment harness validity, or general statistics skills. Fits anchor 4 ('mostly distinct; minor overlap risk with closely related skills'); not 5 because of that breadth, not 3 because the interpretive niche is clearly distinguishable.