Skill UI

This skill provides comprehensive reference architectures for building production-grade AI applications using OpenRouter as a unified LLM gateway. It covers three scaling patterns: simple single-service, standard microservice (with caching and budget enforcement), and enterprise event-driven systems (with message queues and workers). Use this when planning system design, reviewing complex AI pipelines, or ensuring scalability and cost control in your LLM integration.

This guide outlines best practices for building highly flexible and maintainable React components. It addresses common architectural pitfalls, such as 'boolean prop proliferation,' by recommending advanced patterns like compound components, state lifting, and context providers. Use this when refactoring large component libraries, designing robust APIs, or reviewing component architecture, including considerations for React 19 APIs.

A comprehensive guide to modern React UI patterns. It covers best practices for managing application states, including determining when to use skeleton loaders vs. spinners, implementing robust error handling hierarchies (inline, toast, banner), and designing effective empty states. Essential for building high-quality, user-friendly components that handle asynchronous data gracefully.

This skill provides comprehensive patterns for data handling and integration with Retell AI. It is designed for developers building advanced voice agents, automating phone calls, or working with complex telephony systems. The guide covers SDK usage, agent listing, and robust error handling, ensuring reliable implementation of voice AI applications.

Expert skill for writing, reviewing, and debugging idiomatic Rust code, focusing on memory safety and zero-cost abstractions. Specializes in advanced concepts like ownership patterns, explicit lifetime management, trait-based API design, and building concurrent async applications using Tokio. Use this when developing high-performance, reliable, systems-level software in Rust.

Provides authentication, authorization, encryption, secrets, and hardening patterns for designing secure auth flows, managing tokens, configuring CORS, and implementing best practices around API keys, JWT, OAuth, and rate limiting.

An expert architect specializing in designing and optimizing service mesh using industry leaders like Istio and Linkerd. This skill provides deep knowledge of cloud-native networking patterns, enabling secure, reliable microservices communication. It covers advanced topics including zero-trust networking, mTLS configuration, sophisticated traffic management (e.g., canary and blue-green deployments), observability integration, and multi-cluster federation.

This comprehensive guide outlines the best practices and structured methodology for developing specialized skills for AI coding agents. It provides detailed instructions on integrating Azure SDKs and Microsoft Foundry services, covering crucial topics like secure authentication patterns (DefaultAzureCredential), modular workflow design, and maintaining concise, effective knowledge context for optimal agent performance.

This skill provides comprehensive guidelines for architecting and developing high-quality, maintainable software. It is deeply rooted in Clean Architecture and Domain-Driven Design (DDD) principles. It covers best practices for code decomposition, naming conventions, separation of concerns, and avoiding common anti-patterns. Use this skill when designing, analyzing, or developing complex, domain-specific software systems.

Automates guidance for sorting parameter handlers in API development, covering REST, GraphQL, OpenAPI, authentication, and design patterns, with step-by-step best practices and production-ready validation.

Guides Java engineers through Spring Boot backend architecture, REST API design, service layering, repository patterns, caching, async handlers, logging, middleware, and resilience practices for scalable production services.

This skill provides systematic patterns and best practices for transforming slow database queries into high-performance operations. It covers techniques like proper indexing, query plan analysis (e.g., using EXPLAIN), schema design improvements, and resolving common issues like N+1 query problems. Use it to debug performance bottlenecks, reduce database load, and ensure scalable application backends.