How should I name my analytics events in Metabase?

Event names must use snake_case (e.g., 'item_created'), while their TypeScript types should use PascalCase with an 'Event' suffix (e.g., 'ItemCreatedEvent').

How do I verify that my events are firing correctly?

You can verify events by checking the browser console when SNOWPLOW_ENABLED is set to true or by using the Snowplow debugger browser extension.

Can I track Personally Identifiable Information (PII)?

No. The skill explicitly advises against tracking PII like emails or names, recommending only non-sensitive identifiers like target_id.

What is the primary event schema used in this skill?

The SimpleEventSchema is the primary schema, designed to handle approximately 90% of events including clicks, opens, and CRUD operations using standard fields.

Where should I define new tracking functions?

Tracking functions should be placed in feature-specific analytics files, such as 'frontend/src/metabase/{feature}/analytics.ts'.

Metabase Frontend Analytics Events

Name: Metabase Frontend Analytics Events
Author: metabase

bymetabase

•

45,774

분석 및 모니터링

Standardizes the implementation of product analytics events within the Metabase frontend using TypeScript schemas and Snowplow tracking.

소개

This skill provides a comprehensive framework for adding product analytics to the Metabase frontend codebase. It guides developers through the entire lifecycle of event creation—from defining strictly typed event schemas in TypeScript to implementing standardized tracking functions. By focusing on the 'SimpleEventSchema' and enforcing specific naming conventions, the skill ensures that all user interaction data is consistent, searchable, and safe from PII leaks. It is an essential tool for Metabase contributors looking to monitor feature usage, track success/failure rates of UI actions, and maintain a high standard of data integrity across the platform.

주요 기능

Feature-specific analytics function organization patterns
TypeScript-driven event type definitions and validation
Standardized SimpleEventSchema for 90% of tracking use cases
45,774 GitHub stars
Enforcement of snake_case event naming and PascalCase type naming
Pre-built patterns for tracking duration, results, and UI context

사용 사례

Standardizing analytics implementation across diverse feature teams
Tracking user interaction with new frontend features like filters or buttons
Monitoring the performance and success rates of complex asynchronous actions

소개

주요 기능

Feature-specific analytics function organization patterns
TypeScript-driven event type definitions and validation
Standardized SimpleEventSchema for 90% of tracking use cases
45,774 GitHub stars
Enforcement of snake_case event naming and PascalCase type naming
Pre-built patterns for tracking duration, results, and UI context

사용 사례

Standardizing analytics implementation across diverse feature teams
Tracking user interaction with new frontend features like filters or buttons
Monitoring the performance and success rates of complex asynchronous actions