measure-instrumentation-spec

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Translated

Specifies event tracking and analytics instrumentation requirements for a feature. Use when defining what data to collect, ensuring consistent tracking implementation, or documenting analytics requirements for engineering.

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Sourceproduct-on-purpose/pm-skills

Added on2026-04-29

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npx skill4agent add product-on-purpose/pm-skills measure-instrumentation-spec

SKILL.md Content

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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

Instructions

When asked to create an instrumentation spec, follow these steps:

Define Analytics Goals Start with the questions you need to answer. What will you measure? What decisions will this data inform? This prevents over-instrumentation while ensuring nothing important is missed.
Identify Events to Track List each user action or system event that should be tracked. Follow consistent naming conventions (typically
```
noun_verb
```
or
```
verb_noun
```
in snake_case). Each event should represent a distinct, meaningful action.
Specify Event Triggers For each event, describe exactly when it fires. Be precise: "When user clicks Submit button" vs. "When form is submitted successfully." These are different events with different meanings.
Define Event Properties List the properties (attributes) attached to each event. Include property name, data type, description, and example values. Properties provide context that makes events useful.
Document User Properties Identify persistent user-level attributes that should be associated with all events (e.g., subscription tier, account creation date). These enable segmentation in analysis.
Address PII and Privacy Flag any properties that contain personally identifiable information. Document how PII should be handled . hashing, encryption, or exclusion.
Create Testing Checklist Define how QA should verify that tracking is implemented correctly. Include steps to validate events fire at the right times with correct properties.

Output Format

Use the template in

references/TEMPLATE.md

to structure the output.

Quality Checklist

Before finalizing, verify:

Event names follow consistent naming convention
Each event has a clear, unambiguous trigger
Properties include data types and example values
PII is identified and handling is documented
Events map to the analytics questions you need to answer
Testing checklist enables QA verification

Examples

See

references/EXAMPLE.md

for a completed example.