metrics-tracking

Define North Star and tiered product metrics with review cadences.

Updated Jun 19, 2026
One-click install
npx skills add https://github.com/MuhammadUA/Axe --skill metrics-tracking-muhammadua
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: metrics-tracking
Source: https://github.com/MuhammadUA/Axe/tree/main/.kortix/opencode/skills/GENERAL-KNOWLEDGE-WORKER/metrics-tracking
Command: npx skills add https://github.com/MuhammadUA/Axe --skill metrics-tracking-muhammadua

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Product teams often rely on inconsistent, vanity metrics that fail to reflect actual user value or product health, leading to misaligned goals, wasted effort, and poor strategic decisions. This Skill eliminates that problem by providing a proven, structured framework for defining, tracking, and acting on meaningful, actionable product metrics.

Core Features & Use Cases

  • Tiered Metrics Framework: Guides teams to define a single North Star metric aligned with core user value, 5-7 L1 health indicators mapped to the full user lifecycle (acquisition, activation, engagement, retention, monetization, satisfaction), and L2 diagnostic metrics for root cause analysis of metric shifts.
  • Goal Setting & Review Workflows: Includes OKR best practices, data-informed target setting guidance, and structured weekly, monthly, and quarterly review cadences to keep teams aligned on progress and adjust strategy based on metric trends.
  • Dashboard & Alerting Design: Provides actionable principles for building effective product dashboards that surface the most impactful metrics, avoid vanity traps, and include appropriate alerting to catch issues early.
  • Use Case: A product manager launching a new SaaS collaboration feature can use this Skill to define their North Star metric, set L1 health targets, build a launch dashboard, and run weekly check-ins to track performance against goals and iterate quickly.

Quick Start

Use the metrics-tracking skill to build a complete product metrics framework and dashboard for your new feature launch, including North Star definition, L1 health indicators, and a weekly review schedule.

Frequently Asked Questions about metrics-tracking

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I define a North Star metric and tiered framework for product metrics?

To define a North Star metric and tiered framework, establish a single metric reflecting core user value, map 5-7 L1 health indicators across the user lifecycle, and set L2 diagnostic metrics for root cause analysis of shifts.

What is the best way to structure OKR and product review cadences for metric tracking?

The best way to structure OKR and product review cadences involves implementing data-informed target setting alongside structured weekly, monthly, and quarterly performance reviews to keep teams aligned and adjust strategy based on trends.

How do I build a product dashboard that avoids vanity metrics?

To build a product dashboard that avoids vanity metrics, apply actionable design principles that surface impactful L1 and L2 metrics, eliminate non-actionable data, and include appropriate alerting to catch issues early.

Can I use this metrics framework for SaaS, marketplace, and collaboration tools?

Yes, you can use this standardized metrics framework for SaaS, marketplace, content, and collaboration tools to guide metrics framework design, OKR setting, performance review cadences, and dashboard development across these specific product types.

Why are my product metrics inconsistent and causing misaligned team goals?

Product metrics are inconsistent and cause misaligned goals when teams rely on vanity metrics that fail to reflect actual user value, a problem solved by adopting a standardized, structured metrics framework with health indicators and diagnostic metrics.

When do I need L2 diagnostic metrics for product performance analysis?

You need L2 diagnostic metrics for product performance analysis when investigating the root causes of metric shifts, allowing your team to move beyond top-level L1 health indicators and North Star metrics to execute targeted iterations.