build-metric-tree

Decompose top-line metrics into quantified trees and recommend an OMTM.

142|16|Updated Mar 20, 2026
One-click install
npx skills add https://github.com/amplitude/builder-skills --skill build-metric-tree
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: build-metric-tree
Source: https://github.com/amplitude/builder-skills/tree/main/growth-skills/skills/build-metric-tree
Command: npx skills add https://github.com/amplitude/builder-skills --skill build-metric-tree

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Breaks a top-line metric into a quantified, actionable tree so teams can see the real math behind a number, avoid wishful thinking, and prioritize the changes that deliver the largest absolute impact.

Core Features & Use Cases

  • Structured Decomposition: Define a North Star, Business KPI, and OMTM and decompose the NSM into 2–3 levels of additive and multiplicative relationships.
  • Node Sizing & Leverage Math: Size every node with current values or estimates and compute absolute impacts to reveal where improvements move the needle.
  • Metric Quality Checks & Recommendations: Validate each metric for tangibility, controllability, testability, and gaming risk, and recommend the single highest-leverage OMTM for immediate focus.
  • Use Case: A PM preparing quarterly goals uses the skill to convert product telemetry and estimates into a prioritized OMTM and experiment-ready hypotheses.

Quick Start

Give me a top-line metric, any available numbers or rough estimates, and I will return a sized metric tree, leverage analysis, metric-quality flags, and a recommended OMTM.

Frequently Asked Questions about build-metric-tree

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

FAQPage Schema
How do I decompose a North Star metric into a measurable tree?

Metric tree decomposition breaks a North Star metric into 2–3 levels of additive and multiplicative relationships. By sizing each node with current values, it reveals the underlying math behind your top-line number and identifies the highest-leverage drivers for growth.

How do I find the highest-leverage KPI for product growth sizing?

Finding the highest-leverage KPI requires sizing every node in your metric tree and computing the absolute impact of potential improvements. This leverage math highlights which specific driver changes deliver the largest absolute impact on your top-line metric.

How do I choose the right One Metric That Matters (OMTM) for goal setting?

Choosing an OMTM involves validating candidate metrics for tangibility, controllability, testability, and gaming risk. After decomposing your North Star and calculating leverage, you select the single highest-impact metric that is both actionable and resistant to manipulation.

Can I build a metric tree if I only have rough estimates instead of exact telemetry?

Yes, you can build a metric tree using rough estimates. The decomposition process accepts numeric inputs or estimates for node sizing and uses arithmetic computations to calculate absolute impact, allowing you to prioritize drivers even without perfect product telemetry data.

What is the difference between additive and multiplicative metric decomposition?

Additive metric decomposition splits a top-line metric into summed components, while multiplicative decomposition breaks it into multiplied factors like conversion rates and volume. The skill requires explicit relationships to compute absolute impacts and validate metric quality accurately.

When should I avoid using a metric tree for experiment planning?

You should avoid using a metric tree when you cannot define explicit additive or multiplicative relationships between nodes, or when lacking any numeric estimates for sizing. Without these inputs, computing absolute impact and validating metric quality becomes impossible.