Skill UI

Guides designing robust microservices with service boundaries, event-driven communication, saga orchestration, API gateways, health checks, and anti-pattern awareness for resilient distributed systems.

This skill provides a comprehensive framework for mastering microservices architecture patterns. It covers critical aspects of building robust, distributed systems, including defining service boundaries (Domain-Driven Design), managing inter-service communication, handling distributed data transactions, and implementing various resilience patterns (e.g., circuit breaker, circuit breaker). It is essential for large-scale system decomposition.

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 guide provides a production-ready, layered architecture pattern for integrating Mistral AI into TypeScript/Node.js projects. It implements best practices including singleton client management, Zod-validated configuration, custom error handling, caching mechanisms, and robust service layer design (e.g., RAG pipelines). Use this when setting up new Mistral AI applications or needing standardized, reliable project structure.

This skill provides comprehensive guidance for building production-grade MLOps pipelines. It covers the entire machine learning lifecycle, from initial data ingestion and rigorous feature engineering to model training, advanced validation (A/B testing, performance drift), and robust deployment strategies (Canary, Blue-green). It enables the design and orchestration of scalable, reproducible, and observable ML systems using tools like Airflow and Kubeflow.

Enforces mobile-first, touch-first decisions by requiring feasibility checks, mandatory readings, and anti-pattern bans before any UI work to prevent desktop or AI-default assumptions.

This guide provides comprehensive principles for developing games specifically for mobile platforms. It covers essential technical constraints and best practices, including optimizing for touch input, managing battery life and thermal performance, adhering to platform-specific requirements (iOS/Android), and selecting appropriate monetization models. Use this when designing highly optimized, user-centric mobile gaming experiences.

An expert guide for designing, setting up, and optimizing large-scale monorepositories. Masters advanced build systems like Nx, Turborepo, Bazel, and Lerna to manage complex dependency graphs, implement efficient build caching (local and remote), and optimize slow CI/CD pipelines for multi-project development workflows.

Create structured moodboards that synthesize inspiration from trend research or site analysis, refining colors, typography, and patterns through iterative user feedback before implementation.

Simulates a highly structured, sequential peer-review process using multiple specialized AI agents (e.g., Skeptic, Constraint Guardian, User Advocate). This skill is designed to rigorously stress-test a design, surface hidden assumptions, identify potential failure modes, and enforce non-functional constraints before implementation. It transforms initial concepts into robust, validated specifications by simulating formal critique and achieving consensus via a mandatory Decision Log.

This guide details advanced architectural patterns for building complex AI systems using multiple Language Model instances (agents). It addresses the single-agent context bottleneck by distributing work, enabling parallelism, and facilitating specialization across different subtasks. Key patterns include Supervisor/Orchestrator, Peer-to-Peer/Swarm, and Hierarchical designs, providing guidelines for context isolation and effective coordination protocols.

This skill provides a comprehensive decision framework and set of patterns for architects designing cloud-agnostic applications across major providers like AWS, Azure, and GCP. It details service comparisons (Compute, Storage, DB), multi-cloud patterns (e.g., Best-of-Breed, DR), cost optimization strategies, and structured migration plans, ensuring robust and resilient enterprise deployments.