pmprompt/claude-plugin-product-management/ab-test-designer

Claude Code and agent skill by pmprompt/claude-plugin-product-management

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Design robust A/B test experiments. Use when testing a new feature, validating a hypothesis, or optimizing conversion rates.

Install

npx vskill@latest install pmprompt/claude-plugin-product-management/ab-test-designer

SKILL.md

Domain Context

This skill implements a proven product management framework. The approach combines best practices from industry leaders and is designed for practical application in day-to-day PM work.

Input Requirements

  • Context about your product, feature, or problem
  • Relevant data, research, or constraints (recommended but optional)
  • Clear articulation of what you're trying to achieve

A/B Test Designer

When to Use

  • Testing a new feature or design variation
  • Validating a hypothesis before full rollout
  • Optimizing conversion rates or key metrics
  • Choosing between multiple design approaches
  • Need to make a data-driven decision on a change

What This Skill Does

Helps you design rigorous A/B tests with clear hypotheses, success metrics, sample size calculations, and analysis plans.

Instructions

Help me design an A/B test for [feature/change]. Include:

  1. Hypothesis
  • Current situation and metrics
  • Proposed change
  • Expected impact and why
  1. Test Design
  • Primary success metric
  • Secondary metrics
  • Sample size needed
  • Test duration
  • User segments to include/exclude
  1. Variants
  • Control (A): current experience
  • Variant (B): new experience
  • Any additional variants (C, D, etc.)
  1. Risks and Controls
  • Potential negative impacts
  • Guardrail metrics
  • When to stop the test early
  1. Analysis Plan
  • Statistical significance threshold
  • How to handle edge cases
  • Decision criteria

Feature context: [Add context about the change you want to test]

Best Practices

  • Start with a clear, falsifiable hypothesis
  • Choose one primary metric to avoid multiple comparison issues
  • Calculate sample size upfront based on expected effect size
  • Run tests for full weekly cycles to account for day-of-week effects
  • Set a minimum test duration (usually 1-2 weeks)
  • Define success criteria before running the test
  • Monitor guardrail metrics (revenue, errors, performance)

Example

Input: Testing new onboarding flow vs current 3-step process Output: Hypothesis (new 1-step flow will increase co...

Security

  • Security scanPassed, 100 of 100Pattern checks on the skill's files.
  • Model reviewNot runA model review is scheduled for the next rescan.

Quality evaluation

  • Task evaluationNot runNo evaluation yet. Run one in Skill Studio.

Source

Popularity

Repository stars
56
Repository forks
15
7-day trend score
16

Stars and forks are for the whole GitHub repository, not this skill alone. Refreshed 8 Apr 2026, 7 months ago.

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