Skill UI

This is a production-grade reference architecture for building scalable video generation platforms powered by Kling AI. It details the complete pipeline, from the API gateway and job queuing (Redis/SQS) to the worker pool, object storage, and CDN delivery. Use this guide when designing high-throughput, resilient, and scalable AI video systems.

This guide provides comprehensive techniques to optimize LangChain applications for production environments. Learn how to measure baseline latency, implement efficient caching strategies (in-memory, Redis, SQLite), utilize batch processing with concurrency control, and maximize perceived speed through streaming. Furthermore, it covers prompt optimization and strategic model selection to ensure high throughput and low costs.

This guide provides advanced techniques for optimizing API integration performance with MaintainX. It covers essential concepts such as connection pooling, implementing multi-level caching (L1/L2 using Redis), batch data loading via DataLoaders, efficient cursor-based pagination, and request deduplication. Use this skill when optimizing slow API responses or improving overall system data throughput.

A comprehensive guide to implementing robust, multi-layered API response caching using distributed stores like Redis and Memcached, alongside CDN integration. Learn advanced strategies such as tag-based cache invalidation, read-through/write-through patterns, TTL management, and serving stale-while-revalidate content to drastically boost application performance and scalability.

A comprehensive guide and expertise source for developing robust, high-performance Minecraft server plugins using Bukkit, Spigot, and Paper APIs. Covers advanced topics including event handling, NMS internals, performance profiling, architecture design (SOLID), and ecosystem integration (Redis, Docker). Ideal for complex, production-grade plugin development.

This skill provides comprehensive strategies for implementing robust caching mechanisms for OpenRouter API calls. It covers in-memory caching using Python, persistent caching with Redis for scalability, and utilizing provider-specific features like Anthropic prompt caching. By implementing deterministic key generation and managing Time-To-Live (TTL), developers can significantly reduce API costs and improve application latency when handling repetitive or similar LLM queries, making it ideal for RAG systems and high-volume applications.

Helps analyze and enhance application caching strategies by reviewing TTLs, key structures, hit rates, and invalidation policies to boost Redis or Memcached performance.

This skill provides a comprehensive framework for implementing robust API rate limiting. It supports advanced algorithms like sliding windows, token buckets, and fixed counters, backed by Redis for distributed state. Use it to protect endpoints from excessive requests, enforce tiered quotas (Free, Pro, Enterprise), and prevent abuse like brute-force attacks by setting per-user, per-endpoint, or per-API-key limits.

Automates redis cache manager workflows by recommending backend patterns, generating production-ready code, and validating configurations for node.js, python, go, and microservice architectures.

Provides reusable Redis patterns for caching, rate limiting, pub/sub, streams, Lua scripts, and distributed locking to build scalable, resilient data services.

Specialist workflow for building resilient WebSocket and Socket.IO systems, covering authentication, rooms, Redis pub/sub scaling, sticky sessions, and monitoring for chat and presence applications.

Explains building secure real-time communication with WebSocket servers, Socket.io rooms, SSE, Redis scaling, and resilient clients for multi-server Node.js apps.