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creating-experiments

Guide users through a 3-step flow to create A/B test experiments with PostHog.

58|5|Updated Jan 19, 2026
Search Tags:#workflow#analytics#experiment#posthog#feature-flag#ab-test
One-click install
npx skills add https://github.com/PostHog/skills --skill creating-experiments-posthog
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: creating-experiments
Source: https://github.com/PostHog/skills/tree/main/skills/omnibus/creating-experiments
Command: npx skills add https://github.com/PostHog/skills --skill creating-experiments-posthog

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

People building experiments using PostHog often struggle to define hypotheses, rollout plans, and metrics in a consistent, repeatable way. This skill guides users through a structured 3-step flow to create new A/B test experiments from scratch, reducing misconfigurations and back-and-forth.

Core Features & Use Cases

  • Structured 3-step creation flow: Define hypothesis, feature flag details, and draft experiment in a single guided process.
  • Rollout & scope guidance: Delegates rollout decisions to the dedicated configuring-experiment-rollout and ensures 100% rollout defaults with a safe 50/50 split when unspecified.
  • Analytics planning after creation: Points to the configuring-experiment-analytics workflow for metrics setup after the draft is created, ensuring lightweight creation.

Quick Start

Provide a descriptive experiment name, hypothesis, and a feature flag key, and I will draft and create the experiment with default rollout settings.

Frequently Asked Questions about creating-experiments

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

FAQPage Schema
How do I create an A/B test experiment in PostHog?▼

PostHog A/B test creation follows a structured 3-step flow: define your hypothesis, set feature flag details, and generate a draft experiment payload with default rollout settings for immediate implementation.

What do I need to set up a PostHog feature flag experiment?▼

Setting up a PostHog feature flag experiment requires a descriptive name, hypothesis, and feature flag key. Rollout percentages default to a safe 50/50 split, and analytics metrics are configured after the draft is created.

When should I configure metrics for my PostHog A/B test?▼

Configure analytics metrics after creating the experiment draft. The creation workflow intentionally defers metric setup to a subsequent step, ensuring lightweight initial experiment creation.

Can I customize the rollout percentage for my PostHog experiment?▼

Yes, rollout percentages are customizable during creation. When rollout details are unspecified, the system defaults to a 100% rollout with a safe 50/50 variant split to ensure controlled testing.

What is the best way to structure an A/B test hypothesis and rollout plan?▼

Using a structured 3-step creation flow ensures consistent hypothesis definition, feature flag setup, and draft payload generation. This approach reduces misconfigurations and eliminates back-and-forth during experiment setup.

Why does my PostHog experiment creation defer analytics setup?▼

Analytics setup is deferred to keep experiment creation lightweight. The workflow prioritizes establishing the feature flag and rollout structure first, then points to a dedicated analytics configuration workflow for adding metrics.

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