finding-deleted-feature-flags

A PostHog AI plugin skill for auditing feature flags and A/B testing experiments directly from AI coding tools, providing access to 27+ PostHog tools including flag management, experiment analysis, insights queries, error tracking, and LLM analytics.

A skill provided by the official PostHog AI plugin that enables creating and managing A/B experiments directly from AI coding tools including Claude Code, Cursor, and Codex, as part of PostHog's 27+ product analytics tools.

A skill from the official PostHog AI plugin that guides AI agents through configuring experiment analytics, including A/B tests, feature flags, and event tracking in PostHog.

A bundled skill in the official PostHog AI plugin that guides experiment rollout configuration, part of 30+ task-specific skills covering PostHog best practices for A/B testing and feature flag management.

A bundled skill in the official PostHog AI plugin that helps find and analyze experiments, part of 30+ task-specific skills covering PostHog best practices for experiment creation, lifecycle management, and A/B test analysis.

A bundled skill from the official PostHog AI plugin that guides AI agents through A/B experiment creation and lifecycle management, automatically activating when requests involve creating or analyzing experiments in PostHog.

A required-reading skill for querying PostHog analytics data using HogQL/SQL, covering schema references for all core entities (insights, dashboards, cohorts, feature flags, experiments, sessions, etc.) and providing a schema-discovery workflow with query examples.

Adds PostHog SDK integration to any application with automatic framework detection, covering SDK installation, provider setup, user identification, and environment configuration. Supports 25+ frameworks including Next.js, React, Vue, Django, Flask, iOS, Android, and React Native.

Part of PostHog's official AI plugin that provides access to 27+ PostHog tools including feature flags, experiments, analytics, error tracking, and LLM analytics directly from AI coding tools.

Analyzes PostHog session replay patterns across A/B experiment variants to understand behavioral differences between control and test groups, providing qualitative insights to complement quantitative results.