Skill UI

A comprehensive, step-by-step guide detailing the process of upgrading Expo SDK versions in a React Native project. This resource covers dependency resolution, handling breaking changes (such as React 19 or New Architecture migrations), clearing native caches (iOS/Android), and updating deprecated packages to ensure a smooth and stable migration process.

This guide details the production-grade reference architecture for running complex GPU compute workflows on Vast.ai. It covers the foundational three-tier pattern—Orchestrator, GPU Workers, and Artifact Storage—providing blueprints for job queue management, fault-tolerant training pipelines, and robust checkpointing. Use this when designing scalable and reliable ML/AI training systems.

A comprehensive guide to implementing fault-tolerant patterns for Vercel serverless functions. Learn how to build resilient APIs using Circuit Breakers to handle external dependency failures, implementing Exponential Backoff for retries, and achieving Graceful Degradation by serving stale cache data. Essential for production-grade, highly available serverless architecture.

This skill guides the development of advanced voice agents, representing the frontier of natural human-AI interaction. It covers both low-latency Speech-to-Speech (S2S) architectures (like OpenAI Realtime API) and fully controllable STT→LLM→TTS pipelines. Key focus areas include minimizing end-to-end latency (targeting <800ms), handling conversational nuances, background noise, and managing interruptions for applications like customer support, IVR, and live translation.

This skill provides comprehensive guidance on selecting the optimal workspace architecture for Windsurf, adapting to various project scales. Whether managing small solo projects, large monorepos, or complex multi-service, polyglot systems, it outlines strategies for structuring file systems and configuring rules. The goal is to ensure that AI tools receive accurate and focused project context, maximizing developer efficiency.

This skill manages complex, large-scale refactoring operations that span hundreds or thousands of files. It provides phased execution with checkpoints, comprehensive rollback capabilities, and AI-assisted planning. Use it for codebase migrations, major architecture refactoring, or system-wide updates.

This guide outlines the Windsurf reference architecture, providing an optimal project structure for development, configuration, and AI context management. It covers rules hierarchy, workflow organization, monorepo strategies, and context pinning to maximize the effectiveness of AI assistants and development tools.

A comprehensive, multi-phase workflow for developing professional WordPress plugins. Covers foundational architecture, hooks, admin UI, database design, and REST API implementation. Crucially, it incorporates advanced WordPress 7.0 features, including Real-Time Collaboration (RTC) compatibility, AI Connector integration (OpenAI, Claude, etc.), and the Abilities API, ensuring modern, scalable, and secure plugins.

Master the architecture of reliable distributed systems using advanced workflow orchestration patterns. This guide covers fundamental design decisions, including the distinction between Workflows and Activities, and introduces critical patterns like Saga for distributed transactions, Entity Workflows, and Fan-Out/Fan-In. Learn best practices for handling long-running processes, state persistence, and failure recovery to build robust business logic.

A comprehensive guide for developing, optimizing, and standardizing skills for AI agents. This resource provides a decision tree for choosing the right architecture (Tier 1-3), incorporating best practices like CSO (LLM SEO) and Anti-Rationalization, and ensuring compliance through rigorous testing and checklists. Essential for robust AI system building.

PyHealth delivers a full-stack Python toolkit for building, evaluating, and deploying clinical machine learning models, covering EHR datasets, medical coding systems, physiological signals, and healthcare-tailored architectures such as RETAIN, SafeDrug, and Transformer-based pipelines.

Guides using SHAP to explain ML predictions, compute feature importance, generate diagnostic plots, debug models, analyze bias, and compare models across tree, deep, linear, or black-box architectures.