Skill UI

A comprehensive guide to product analytics, covering essential concepts like event tracking (PostHog, Mixpanel), funnels, cohort analysis, retention metrics, North Star Metrics, and OKR setting. Use this skill to define data-driven product strategies, optimize user journeys, and build robust performance dashboards.

A comprehensive guide for defining, tracking, and interpreting product metrics across all stages—from discovery to maturity. This skill covers selecting metric frameworks (AARRR, HEART), defining stage-appropriate KPIs, designing multi-layered dashboards, and executing deep analyses like cohort and retention modeling. It helps teams transform raw data into actionable product strategies, moving beyond vanity metrics.

This tool opens the dedicated Context Mode Insight dashboard in your default browser. Insight serves as the central analytics layer for AI-assisted engineering teams, providing crucial metrics such as per-engineer productive rates, identifying retry waste, detecting blockers, and offering role-narrowed performance views. It is designed to be the single source of truth for comprehensive team performance monitoring and sign-in details.

This expert acts as a dedicated data analysis partner for Product Managers. It helps users explore data, write complex queries (e.g., SQL, BigQuery), analyze key metrics, and create structured dashboards. Use this tool when you need to derive actionable insights from complex datasets, compare user cohorts, or understand product performance trends to inform critical business decisions.

This skill guides the design of statistically rigorous A/B tests for optimizing product features, UI/UX changes, onboarding flows, and pricing models. It generates a complete test plan, including formulating hypotheses, calculating required sample sizes, estimating test duration, defining primary and guardrail metrics, and providing a detailed guide on interpreting results (ship, iterate, or reject).

A structured framework for performing in-depth cohort analysis. It helps measure user retention rates, estimate Lifetime Value (LTV), and segment users based on behavior over time. Use this when analyzing growth metrics, identifying churn risks, or presenting product health to leadership.