How does it help with flaky UI tests?

It identifies patterns like cold start issues or async timing and suggests fixes such as registering IdlingResources, disabling animations, or using explicit waits to stabilize Espresso tests.

What is pass@k in mobile testing?

Pass@k is the proportion of test iterations that pass over a set number of runs (k). It helps identify flaky tests that might pass once but fail under different conditions, such as timing issues or resource contention.

Can I use this for Jetpack Compose projects?

Yes, the skill includes specific strategies and recommended thresholds for Compose tests, aiming for a 90% pass@k reliability score while handling recomposition timing.

What are the different verification levels available?

The skill offers four levels: Quick (k=2) for fast feedback, Standard (k=3) for confidence, Thorough (k=5) for refactors, and Release (k=10) for maximum production confidence.

Does it integrate with my Git workflow?

Yes, you can target specific modules or classes based on your Git diff to verify only the changes made before committing or pushing code.

Mobile Test Verification

Name: Mobile Test Verification
Author: ahmed3elshaer

byahmed3elshaer

•

Mobile Development

Automates mobile testing workflows using pass@k metrics to detect flaky tests and ensure high-reliability Android applications.

The Mobile Verification skill enhances Claude Code by implementing a robust testing strategy specifically designed for the complexities of mobile development. It utilizes pass@k metrics to run tests multiple times, providing a statistical measure of reliability that identifies intermittent failures often missed by single-run CI pipelines. By supporting JUnit, Espresso, and Jetpack Compose, it helps developers pinpoint async timing issues and resource leaks across unit, UI, and integration tests, ensuring production-ready code through tiered verification levels.

주요 기능

01Context-aware reliability thresholds for different test types

02Advanced flaky test detection and diagnostic pattern identification

03Native support for JUnit, Espresso, and Jetpack Compose frameworks

0427 GitHub stars

05Automated pass@k metric calculation for statistical test reliability

06Tiered verification levels ranging from Quick (k=2) to Release (k=10)

사용 사례

01Monitoring reliability trends during large-scale mobile code refactoring

02Identifying intermittent UI failures in Espresso tests before a production release

03Verifying the stability of complex asynchronous coroutines in ViewModels

What are Skills?·How to Install

Install with 🐟 Skill.Fish

npx skillfish add ahmed3elshaer/everything-claude-code-mobile mobile-verification

For use in Claude.ai and ChatGPT

Download Skill