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configuring-experiment-rollout

Configure experiment rollout percentages and variant splits with safety checks.

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

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve?

Guides teams to configure rollout parameters for experiments, including variant splits and overall exposure, and to disambiguate how to handle requests mentioning a specific percentage.

Core Features & Use Cases

  • Parameterized variant splits (parameters.feature_flag_variants) with a required 'control' variant and support for up to 20 variants.
  • Overall rollout control (parameters.rollout_percentage) to include or exclude users from the experiment.
  • Clear disambiguation prompts when users request a specific percentage, plus best practices for safe changes to running experiments.
  • Guidance for resolving experiments and safe-change workflows to preserve data integrity.

Quick Start

To start, configure an equal-split rollout with a 100% overall rollout across two variants.

Frequently Asked Questions about configuring-experiment-rollout

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

FAQPage Schema
How do I configure variant splits for an A/B test experiment?▼

Adjust overall experiment exposure by setting parameters.rollout_percentage, which controls the total percentage of users included or excluded from seeing the experiment's feature flag variants.

Can I change rollout percentages for an experiment that is already running?▼

Yes, you can change rollout percentages on a running experiment, but the workflow applies safety checks and cross-references resolution workflows to preserve data integrity and prevent skewed results.

What happens if I request a specific percentage for my experiment rollout?▼

When you request a specific percentage, the system triggers a clear disambiguation prompt to clarify whether you mean overall rollout exposure or an individual variant split before applying the change.

How many variants can I set up in a feature flag experiment?▼

You can set up a maximum of 20 variants in feature flag experiment configurations, but you must always include a required 'control' variant alongside your treatment variants.

How do I safely end an experiment and resolve feature flag variants?▼

To safely end an experiment, follow the guided resolution and safe-change workflows to roll out the winning variant or revert to control while preserving your historical experiment data integrity.

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