PostHog Experiment Health Diagnostics
Diagnoses anomalies, sample ratio mismatches, and data discrepancies in PostHog A/B tests and feature flag experiments.
PostHog Experiment Health Diagnostics provides automated troubleshooting and statistical health checks for PostHog A/B testing and experimentation workflows. It enables Claude to evaluate experiment configurations, identify sample ratio mismatches (SRM), detect zero-exposure or skew issues, and uncover identity resolution bugs like users showing up across multiple variants. The skill inspects raw exposure criteria, historical experiment changes, and metric definitions while guiding teams through statistical interpretation pitfalls such as peeking bias, A/A testing variances, sequential testing thresholds, and CUPED adjustments to ensure experiment results are reliable and scientifically sound.