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ab-test-setup

Design statistically valid A/B tests and growth experiments.

Updated Apr 4, 2026
Search Tags:#metrics#growth#hypothesis#experimentation#test-design#ab-testing#sample-size
One-click install
npx skills add https://github.com/kunalrawat425/conductor-playground --skill ab-test-setup-kunalrawat425
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: ab-test-setup
Source: https://github.com/kunalrawat425/conductor-playground/tree/main/.agents/skills/ab-test-setup
Command: npx skills add https://github.com/kunalrawat425/conductor-playground --skill ab-test-setup-kunalrawat425

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve?

Provides a structured, repeatable framework to design, run, and analyze A/B tests and growth experiments, ensuring statistically valid insights to guide product decisions.

Core Features & Use Cases

  • Define clear hypotheses and test designs (A/B, A/B/n, MVT) that isolate variables and interactions.
  • Specify primary, secondary, and guardrail metrics; estimate required sample sizes and test durations; document results for stakeholders.
  • Apply across marketing, product, and growth workflows (e.g., homepage, pricing, checkout, onboarding) to build a reusable experimentation playbook.

Quick Start

Frame a hypothesis using the observation–change–outcome formula and specify the primary metric, target sample size, and planned duration.

Frequently Asked Questions about ab-test-setup

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

FAQPage Schema
How do I design an A/B test with a valid hypothesis and sample size?▼

Design an A/B test by framing a hypothesis using the observation-change-outcome formula, then specifying primary metrics and estimating the target sample size to ensure statistically valid results.

What metrics should I track when running growth experiments on checkout flows?▼

Track primary, secondary, and guardrail metrics when running growth experiments on checkout flows, ensuring you isolate variables and protect against adverse effects on user experience.

Can I use this framework to plan multivariate tests for landing pages?▼

Yes, you can plan multivariate tests (MVT) for landing pages, as the framework supports selecting test types like A/B, A/B/n, and MVT to isolate variables and interactions.

How do I calculate the required test duration for an onboarding funnel experiment?▼

Calculate test duration by estimating the required sample size based on your onboarding funnel traffic, then dividing by daily visitors to determine the planned testing period.

What is the best way to document A/B test results for stakeholders?▼

Document A/B test results by recording the hypothesis, test design, defined metrics, and outcomes in a structured format, creating a reusable experimentation playbook for stakeholder review.

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