Skill UI

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.

This skill defines a framework-agnostic, scalable architecture pattern for React and React Native applications. It mandates feature modules, strict state separation (server vs. UI), and disciplined import rules to create predictable, maintainable, and highly scalable codebases, regardless of the chosen framework (Next.js, Remix, etc.).

This discipline establishes a portable, framework-agnostic layer for ensuring type safety at the network edge of any React or React Native application. It mandates a single, typed API client to wrap all network fetching, guaranteeing that raw wire JSON is immediately parsed into trusted, domain-specific types or standardized error objects before entering the application state. This pattern drastically reduces runtime errors and enhances code robustness.

A comprehensive discipline for managing the write path in React or React Native applications using a query/cache layer. It codifies the full optimistic update lifecycle, ensuring that UI updates feel instantaneous, rollbacks are verbatim upon failure, and the global cache remains perfectly coherent across all components and list views. This pattern is essential for complex, highly interactive user experiences.

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.

This guide details best practices for implementing robust, type-safe GraphQL queries and mutations. It covers using separate .gql files, running code generation tools, and implementing mandatory error handling (onError) and loading states. Use this when building complex, reliable data fetching layers with Apollo Client.

A comprehensive guide for developers building AI demos and GPU compute tasks on Hugging Face Spaces using ZeroGPU hardware. It covers best practices for writing and reviewing code that utilizes the `@spaces.GPU` decorator, managing runtime duration and quota, and understanding the specific CUDA availability model and process isolation rules required for reliable ML deployment.

This skill guides the structured development process for implementing new features or fixes based on Product Requirement Documents (PRDs) or predefined issues. It emphasizes best practices, including Test-Driven Development (TDD), regular type-checking, running comprehensive test suites, and completing the cycle with a formal review process.

This skill performs a deep comparison of two code versions to verify semantic equivalence, going beyond simple syntax diffing. It uses semi-formal tracing techniques to trace both versions against shared specifications and boundary conditions (e.g., null, zero, max/min). Ideal for confirming if a refactor, rewrite, or migration has unintentionally altered the code's behavior, answering the question: "Did I break anything?"