Skill UI

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 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 comprehensive skill demonstrates advanced usage patterns for Formik, a popular React form handling library. It covers basic form setup, complex validation schema creation using Yup (including conditional logic), field helper utilities, and integrating form submissions with GraphQL mutations for both creation and editing scenarios.

A framework-agnostic, builder-based SEO system designed for React and React Native-for-web applications. It centralizes site identity (title, description, OG tags) in a single source of truth, ensuring all metadata, canonical URLs, and structured data (JSON-LD, sitemap, robots.txt, RSS) are consistent, machine-readable, and automatically generated for every route.

Create highly aesthetic, animation-rich HTML presentations from scratch or convert existing PowerPoint files (PPT/PPTX). This tool focuses on generating distinctive, professional web decks with fixed 16:9 ratios. It supports low-density for keynote talks or high-density for detailed reports, ensuring visual impact and zero dependencies.

Use this powerful skill to perform advanced, multi-modal video generation and editing using the official google-genai SDK. Capabilities include generating realistic videos from text prompts (Text-to-Video), animating scenes from a single input image (First-Frame-to-Video), and applying style or character references from images. It also supports complex video refinement, inpainting, and optimizing source footage for professional creative workflows.

This skill provides comprehensive access to the Hugging Face Hub ecosystem via MCP server tools. Users can search for state-of-the-art models, datasets, and research papers, retrieve detailed repository information, fetch documentation, run compute jobs on GPU/CPU, and interact with Gradio Spaces as fully functional AI tools. Ideal for ML development, research, and application prototyping.

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 generates comprehensive unit and integration tests using Jest for JavaScript and TypeScript. It supports advanced testing patterns, including deep mocking, asynchronous handling, snapshot testing, and testing React components with Testing Library. Use it when the user needs to thoroughly validate application logic and behavior.

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?"

This sophisticated skill is designed to locate the root cause of a confirmed software failure. It performs a systematic, semi-formal tracing process: first tracing backward from the observed failure point (using provided stack traces, assertions, or error messages) to identify the original premise, and then tracing forward to confirm the symptom. It outputs a highly structured report detailing the divergence, premises, and remedy.

This skill is designed to identify subtle and complex logic bugs within a single code file or function. It employs a semi-formal execution tracing methodology, systematically breaking down the suspected bug into five stages: Premises (expected state), Trace (execution path), Divergence (actual deviation), Trigger (reproduction case), and Remedy (fix). It is ideal for scenarios where users suspect code is wrong but cannot specify a concrete failure point.