Measure Instrumentation Spec

You know that frustrating moment when you launch a feature and realize you can't answer basic questions because nobody tracked the right events? This spec template prevents that. It walks you through defining analytics events, their triggers, properties, and user attributes before engineering starts work. The structure enforces consistency with naming conventions, maps events to actual questions you need answered, and includes a testing checklist for QA. The real value is in treating instrumentation as a contract between product and engineering rather than an afterthought. Works across triple-diamond, lean-startup, and design-thinking frameworks, which basically means it's useful whenever you need to measure what users actually do.

skills.sh installs: 792
GitHub stars: 794
last updated: Aug 21, 2026

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Install

$ npx -y skills add product-on-purpose/pm-skills --skill measure-instrumentation-spec --agent claude-code

Installs into .claude/skills of the current project.

Files

Instrumentation Spec

An instrumentation spec defines what analytics events to track, when to fire them, and what properties to include. It serves as a contract between product and engineering, ensuring consistent data collection that enables accurate measurement. Good instrumentation specs prevent the "we can't answer that question because we didn't track it" problem.

When to Use

Before engineering implements a new feature
When defining analytics requirements for experiments
When auditing existing tracking for gaps or inconsistencies
When onboarding a new analytics tool
Before launch to ensure measurement is in place

When NOT to Use

You are specifying the dashboard built on top of the events -> use measure-dashboard-requirements
You need experiment-specific metrics and variants, not product-wide tracking -> use measure-experiment-design
The feature itself is not yet specified (no flows to instrument) -> use deliver-prd first
You are analyzing data you already collect -> use measure-experiment-results or measure-survey-analysis