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posthog_experimentlisted

Set up a sound PostHog A/B experiment or feature flag rollout — hypothesis, primary metric, exposure, and a sample-size check before launch.
Tarekkharsa/agentstack · ★ 2 · AI & Automation · score 73
Install: claude install-skill Tarekkharsa/agentstack
# PostHog Experiment > Unofficial, agentstack-authored. Not affiliated with or endorsed by PostHog. Use this skill when a team wants to test a change with a PostHog experiment or roll a feature out behind a flag, and needs the setup to actually yield a trustworthy result. ## Workflow 1. Write the hypothesis as one falsifiable sentence: "Changing X will move [primary metric] by roughly Y for [population]." If you cannot state it this way, the experiment is not ready. 2. Choose **one primary metric** that maps directly to the goal (e.g. signup conversion), plus a small set of guardrail metrics that must not regress. 3. Define the exposure point — the feature flag and the event that marks a user as enrolled. Users must be counted from the moment they could see the change, not from when they convert. 4. Estimate the needed sample size and runtime from the baseline rate and the minimum effect worth detecting. State how long the test must run; resist calling it early. 5. Set the rollout: start the flag at a safe percentage, confirm assignment is stable per user, and verify both variants render before ramping. 6. Pre-commit to the decision rule (ship / kill / iterate) and the metrics that decide it, in writing, before launch. ## Conventions - One primary metric per experiment. Multiple primaries invite cherry-picking. - Do not peek-and-stop: respect the planned runtime and sample size. - Keep the feature flag key descriptive and consistent with the e