What platforms are supported by this skill?

The skill provides guidance and patterns specifically for mobile development platforms, including iOS, Android, and React Native.

How does the measurement pattern work?

It follows a TAP → START_SPAN → ASYNC WORK → END_SPAN flow, ensuring the initial tap timestamp is captured to account for the full user experience.

What is considered a 'Good' interaction speed?

Based on the skill's benchmarking thresholds, an interaction is considered 'Good' if it completes in under 300ms and 'Acceptable' if under 1 second.

What does interaction latency measure?

It measures the total duration from the moment a user taps a UI element to the moment the resulting action—such as an API call or state update—is successfully completed.

Mobile Interaction Latency Monitor

Name: Mobile Interaction Latency Monitor
Author: nexus-labs-automation

bynexus-labs-automation

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Analytics & Monitoring

Measures and optimizes the time between user taps and action completion in mobile applications.

About

The Interaction Latency skill empowers developers to track and improve mobile app responsiveness by measuring the duration from a user's tap to the final resolution of an asynchronous action. It provides standardized measurement patterns for tasks like form submissions, 'add to cart' operations, and state changes, helping development teams identify performance bottlenecks and ensure critical UI interactions stay within the recommended 300ms 'Good' threshold.

Key Features

Performance threshold benchmarking
Precise tap-to-completion timing
Multi-platform instrumentation guidance
Success and failure outcome tracking
Standardized async measurement patterns
98 GitHub stars

Use Cases

Benchmarking form submission latency
Optimizing 'Add to Cart' button responsiveness
Detecting friction in critical user journeys

About

Key Features

Performance threshold benchmarking
Precise tap-to-completion timing
Multi-platform instrumentation guidance
Success and failure outcome tracking
Standardized async measurement patterns
98 GitHub stars

Use Cases

Benchmarking form submission latency
Optimizing 'Add to Cart' button responsiveness
Detecting friction in critical user journeys