Experiment skills
These Agent Skills take an A/B test from idea to decision, all from your AI agent. Install the plugin and run /growthbook:gb-setup first.
The example prompts can be typed verbatim, or your agent may run these skills automatically when it detects matching intent.
Prerequisites
- A datasource and at least one metric, configured in the GrowthBook UI. The skills reference metrics by ID. They don't create datasources or metrics.
- The experiment skills target standard A/B tests. Multi-armed bandits aren't supported yet: the skills stop and point you to the app rather than misinterpret a bandit.
The experiment lifecycle
The five skills below form a chain from ideation to decision. Each one routes to the next when you're ready.
| Skill | What it does | Example prompt |
|---|---|---|
experiment-brainstorm | Propose new test ideas grounded in your team's past stopped-experiment history. Read-only. | "What should we test next on the checkout page?" |
experiment-design | Walk through hypothesis, variations, primary metric, guardrails, and sample size to produce a launchable spec. Read-only. | "Help me design an A/B test for the new pricing page" |
experiment-launch | Create the experiment, create or reuse the feature flag, wire the experiment-ref rule, and start it. | "Launch the pricing experiment we just designed" |
experiment-analyze | Refresh the snapshot if it's stale, then interpret results: lifts, confidence intervals, guardrails, and a data-quality (SRM) check. Read-only. | "What are the results of exp_abc123?" |
experiment-stop | Stop a running experiment, optionally declaring a winner and rolling it out to 100% of eligible traffic. | "Stop the pricing test and ship the winner" |
Related concepts: Experiment configuration, Experiment results, Decision framework.
From experiment to cleanup
After you stop an experiment, the feature flag it ran through usually still needs tidying: inlining the winning value at your code sites and removing the flag. Hand off to flag-cleanup, which walks through code-site inlining and a two-step archive-then-delete.
Next steps
- Feature flag skills: create, target, and clean up the flags your experiments run on
- Agent Skills overview: install and setup
- Experimentation documentation: the underlying concepts