From pm-advanced
Designs A/B tests from hypotheses with sample size calculations, success criteria, risks; interprets results for statistical/practical significance and recommendations.
npx claudepluginhub mohitagw15856/pm-claude-skills --plugin pm-advancedThis skill uses the workspace's default tool permissions.
Produce rigorous experiment designs from product hypotheses, and interpret
Designs controlled experiments (A/B, multivariate, quasi) with hypothesis, success metrics, sample size, and statistical power. For validating features via /design-experiment or phrases like 'design experiment'.
Formulates testable hypotheses, designs A/B experiments with metrics and guardrails, interprets results, and recommends shipping decisions for Product Managers validating assumptions.
Designs complete A/B test plans from hypotheses, including structured hypothesis, primary/guardrail metrics, variants, sample size, duration, success criteria, and risks.
Share bugs, ideas, or general feedback.
Produce rigorous experiment designs from product hypotheses, and interpret results with statistical and practical significance — so you can defend every decision to a sceptical engineering lead or data scientist.
Required inputs: hypothesis, primary metric, current baseline, minimum detectable effect (MDE), available sample size per day.
Output:
Required inputs: control results, variant results, p-value or raw numbers, run duration, any anomalies observed.
Output: