ab-test-plan

Generate A/B test plans for DTC funnels using RMBC principles.

Updated May 19, 2026
One-click install
npx skills add https://github.com/mohammedburqan/es --skill ab-test-plan-mohammedburqan
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: ab-test-plan
Source: https://github.com/mohammedburqan/es/tree/main/skills/ab-test-plan
Command: npx skills add https://github.com/mohammedburqan/es --skill ab-test-plan-mohammedburqan

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes scripts (resource) and references (resource) components.

What problem does it solve?

This Skill streamlines the process of creating A/B test plans for Direct-to-Consumer funnels, ensuring they are structured, based on RMBC principles, and include a falsifiable hypothesis, control vs variant definition, and success criteria.

Core Features & Use Cases

  • Structured Test Plan Creation: Provides a template for writing A/B test plans, including hypothesis, control, variant, primary metric, sample size, and success criteria.
  • RMBC Grounded Reasoning: Ensures that every element of the test plan connects back to Research, Mechanism, Brief, or Copy phases of the RMBC methodology.
  • Use Case: For a DTC e-commerce funnel, use this Skill to create a comprehensive A/B test plan for the checkout page, outlining the hypothesis, expected outcomes, and primary success criteria.

Quick Start

Generate an A/B test plan for the checkout page using the 'checkout' page type, with a baseline conversion rate of 10%, a hypothesis about reducing checkout friction, and a traffic volume of 1000 daily visitors.

Frequently Asked Questions about ab-test-plan

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I create an A/B test plan for a DTC e-commerce funnel?▼

An A/B test plan for a DTC funnel validates changes by structuring a falsifiable hypothesis, defining control versus variant, calculating sample size, and setting primary metrics with success criteria based on RMBC principles.

What is the RMBC methodology for conversion optimization?▼

The RMBC methodology for conversion optimization structures testing around Research, Mechanism, Brief, and Copy phases. It ensures every A/B test plan element connects back to these core principles to validate Direct-to-Consumer funnel changes.

How do I calculate sample size for an A/B test on a checkout page?▼

Calculating sample size for an A/B test requires your baseline conversion rate, expected effect size, and daily traffic volume. The plan incorporates these metrics to determine statistical significance for your checkout page tests.

Do I need prior A/B testing knowledge to use RMBC principles for DTC funnels?▼

Yes, you need a foundational understanding of A/B testing and RMBC methodology. The process requires you to input valid baseline conversion rates, page types, and hypotheses to generate accurate test plans for Direct-to-Consumer funnels.

What's the best way to structure a falsifiable hypothesis for conversion optimization?▼

The best way to structure a falsifiable hypothesis is to link it directly to RMBC phases. The generated plan defines the expected outcome, primary metric, and success criteria to ensure the hypothesis is testable and measurable.