npx claudepluginhub anthropics/claude-plugins-official --plugin sanityThis skill uses the workspace's default tool permissions.
Principles and patterns for running effective content experiments to improve conversion rates, engagement, and user experience.
Guides planning, designing, and implementing A/B tests, split tests, multivariate experiments. Covers hypotheses, sample sizes, test types, statistical principles.
Guides A/B test planning and design with hypothesis frameworks, sample size calculations, test types, and statistical principles for valid, actionable results. Useful for experiments or split tests.
Designs A/B tests and experiments with hypothesis frameworks, sample sizes, test types, metrics, and statistical principles for valid, actionable growth results.
Share bugs, ideas, or general feedback.
Principles and patterns for running effective content experiments to improve conversion rates, engagement, and user experience.
Reference these guidelines when:
Comparing two variants (A vs B) to determine which performs better.
Testing multiple variables simultaneously to find optimal combinations.
The confidence level that results aren't due to random chance.
Making decisions based on data rather than opinions (HiPPO avoidance).
Start with the reference that matches the current problem, such as design, statistics, CMS integration, or pitfalls. See references/ for detailed guidance:
references/experiment-design.md — Hypothesis framework, metrics, sample size, and what to testreferences/statistical-foundations.md — p-values, confidence intervals, power analysis, Bayesian methodsreferences/cms-integration.md — CMS-managed variants, field-level variants, external platformsreferences/common-pitfalls.md — 17 common mistakes across statistics, design, execution, and interpretation