Skill UI

Provides comprehensive guidelines and utilities for modern unit testing using Jest and React Native. Covers Test-Driven Development (TDD) workflows, Behavior-Driven Development (BDD) principles, advanced mocking strategies for modules and GraphQL hooks, and implementing reusable factory functions for props and data. Use this skill to write robust, maintainable, and highly structured unit tests.

This skill generates robust, production-grade End-to-End (E2E) and Component tests using the Cypress framework in JavaScript or TypeScript. It supports local execution and cloud testing environments. Use this skill when you need to write Cypress test cases, set up the Cypress environment, or utilize core commands like `cy.get`, `cy.visit`, and `cy.intercept` for functional validation.

This powerful skill provides an interactive debugger interface, allowing developers to set breakpoints, step through source code line by line, inspect live variable states, and trace the entire call stack. It is essential for diagnosing complex bugs, understanding unexpected program flow, or determining the root cause when standard logging fails. It supports various languages via the DAP protocol.

This skill provides a deep framework for validating the spatial composition and technical integrity of a UI. It moves beyond simple visual checks, emphasizing that the output must be rendered and critically assessed at various viewport sizes. Key focus areas include detecting subtle design flaws like overlaps and imbalances, and most critically, implementing mandatory horizontal overflow checks (`scrollWidth`) to ensure the layout remains flawless across all device widths.

A comprehensive guide on designing, building, and optimizing interactive developer playgrounds. Learn principles covering instant gratification, progressive complexity, and zero friction to maximize developer engagement, demonstrate core value, and convert curious visitors into active users.

A comprehensive resource containing official, managed integration examples for popular third-party services (Stripe, OpenAI, Supabase, etc.). This library provides canonical patterns for connecting external APIs into an Expo application. Users can utilize it in two primary ways: adapting the pattern into an existing project (most common) or scaffolding a new greenfield application.

EAS Observe is a comprehensive tool for monitoring performance metrics in production Expo applications. It tracks critical performance data, including app startup time, navigation performance across routes, and custom user events. Developers can integrate it into their Expo project using the `expo-observe` package and query detailed reports via the EAS CLI, ensuring optimal user experience and stability.

Use @expo/ui to build high-fidelity, native user interfaces across iOS and Android from a single React codebase. This library renders real native UI components, such as SwiftUI on iOS and Jetpack Compose on Android. It promotes a universal component layer for cross-platform consistency, while also providing controlled access to platform-specific optimizations and drop-in replacements for existing community libraries.

This skill helps developers achieve maximum AI readiness by automatically detecting the project stack and seeding context using a single, precise goal sentence. It systematically fills the essential project context (the 6 Ws), requiring the user only to answer the few remaining knowledge gaps (like the 'why' or 'when'). This creates a portable, structured context file, ensuring AI models have a complete understanding of the project before coding, minimizing guesswork and maximizing efficiency.

This skill guides users through an in-depth interview process to achieve maximum project context completeness (100% "Gold Code") for their .faf file. By systematically asking questions about project goals, architecture, and technology stack, it ensures all critical context slots are filled, making the project fully structured and highly readable by AI systems.

A portable, framework-agnostic system designed for robust field-side observability in React or React Native apps. It establishes a strongly typed event taxonomy, ensures best-effort, non-blocking data fan-out across multiple analytics providers, and enforces consent gates for all telemetry data. This system complements synthetic testing by capturing real user vitals (LCP, INP, CLS) and behavioral events in production.

Use this comprehensive skill for interacting with the Gemini API. It supports a wide range of advanced AI tasks, including text generation, multi-turn chat, multimodal understanding, image/video creation, function calling, and structured output. Provides modern SDKs for robust application development in Python and JavaScript/TypeScript.