pm-abtest

What problem does it solve?

This Skill helps you validate product or feature changes by turning vague optimization ideas into a statistically grounded A/B test plan, including hypothesis, metrics, sample size, runtime, and decision rules.

Core Features & Use Cases

• Hypothesis & Metrics Setup: Define test hypotheses plus primary/secondary/guardrail metrics to ensure you measure the right outcome without harming user experience.
• Sample Size & Test Duration Planning: Estimate required sample size and propose a realistic test period based on provided baseline parameters and traffic assumptions.
• Data Collection & Analysis Framework: Specify event/metric collection guidance and an analysis workflow (cleaning, descriptive stats, hypothesis testing, effect size, segmentation).
• Auto-generate Test Plan Docs: Write a structured A/B test方案 into docs/03-增长迭代/A-B测试/ for execution and later analysis.

Quick Start

Ask the AI to run an A/B test planning session for your optimization idea, and it will guide you to define the hypothesis, choose metrics, estimate sample size and duration, and generate the test plan document.