What problem does it solve?
Product teams struggle to choose a single customer-centric North Star, break it into actionable input metrics, and design dashboards and alerts that align engineering, product, and business goals; this Skill structures that process end-to-end. It also addresses the special measurement needs of AI-enabled features by adding model-quality and operational metric layers alongside product and business impact metrics.
Core Features & Use Cases
- North Star selection & validation: Proposes 2–3 NSM candidates and evaluates each against clear criteria (customer value, leading indicator, measurability, actionability, resistance to gaming).
- Four-layer metrics framework: Produces NSM, 3–5 MECE input metrics, 3–5 health guardrails, and 1–2 counter-metrics with precise definitions, data sources, visualizations, targets, and alert thresholds.
- Dashboard & cadence design: Provides a recommended dashboard layout, alert severity levels, and review cadences (daily/weekly/monthly/quarterly).
- AI metrics stack (optional): Adds model quality, operational, product-level, and business-impact metrics for ML/LLM features, plus degradation detection and monitoring suggestions.
Quick Start
Define a complete metrics framework for my product or feature including a recommended North Star, 3–5 input metrics, health and counter-metrics, dashboard layout, and alert thresholds.