Skill UI

This skill provides comprehensive guidance for building scalable, maintainable, and production-ready backend applications using Node.js. It covers modern architectural patterns, best practices, and implementation details for REST APIs, GraphQL servers, microservices, authentication, real-time WebSockets, and complex database integrations (SQL/NoSQL).

This comprehensive guide helps developers make critical architectural decisions in modern Node.js development. It covers framework selection (Fastify, Hono, Express), implementing layered architecture, mastering async patterns, robust error handling, and essential security protocols. The focus is on teaching architectural thinking and problem-solving skills, ensuring the development of scalable, high-performance, and maintainable backend APIs.

Expert guidance on designing highly scalable, distributed NoSQL databases, specifically covering Apache Cassandra and Amazon DynamoDB. This skill emphasizes the 'Query-First' modeling approach, teaching best practices like partitioning, denormalization, single-table design, and avoiding common anti-patterns (e.g., hot partitions, joins) to ensure optimal read/write performance at massive scale.

Expert skill in designing and implementing comprehensive observability stacks for enterprise microservices. Covers advanced monitoring (Prometheus, Grafana), distributed tracing (Jaeger, OpenTelemetry), centralized logging (ELK, Splunk), and defining SLIs/SLOs. Ideal for ensuring high availability, mastering incident response, and performing reliability engineering on large-scale, distributed applications.

Implements advanced Role-Based Access Control (RBAC) for collaborative Obsidian workspaces. This system allows administrators to define granular permissions (read, write, delete, manage) for different user roles (Admin, Editor, Viewer) across specific folders or paths within a shared vault. It is achieved via a custom plugin that intercepts file operations, ensuring data integrity and proper collaboration control in enterprise team environments. Ideal for managing large, secure knowledge bases.

This skill provides a comprehensive guide to setting up isolated development, testing, and production vaults within Obsidian. It covers advanced techniques like symlinking plugin sources for hot reloading, implementing environment-specific configuration logic (e.g., managing debug modes and feature flags), and creating standardized vault templates for team onboarding, ensuring a robust and scalable development lifecycle.

This guide provides the best-practice reference architecture for developing complex Obsidian plugins. It details a highly modular project structure, enforcing separation of concerns by implementing dedicated layers for commands, views, and services (e.g., vault operations). Use this when designing a new plugin, reviewing existing project structure, or establishing standardized development practices for maintainable and scalable Obsidian extensions.

This skill automates the setup and configuration of Ollama, allowing users to deploy Large Language Models (LLMs) locally. It performs system assessment (OS, GPU, RAM), selects optimal models based on hardware availability, and handles installation across macOS, Linux, and Docker. Use this when you require free, self-hosted AI alternatives, need offline inference capabilities, or wish to eliminate reliance on costly hosted API services.

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.

A comprehensive guide on implementing failover and fallback mechanisms for Large Language Models (LLMs) when using OpenRouter. This skill covers native model fallbacks, provider routing strategies, and advanced client-side fallback chains. Use this pattern when building mission-critical or highly resilient systems that must maintain service availability even if a primary model or an entire provider goes offline. It ensures robust API integration and graceful degradation.

This skill demonstrates advanced techniques for managing high-volume API calls to LLM services via OpenRouter. It implements multi-key round-robin strategies, incorporating health checks and circuit breakers to distribute load across multiple API keys. It also covers concurrent request processing using asyncio and provider-level failover, ensuring high availability and maximizing throughput when facing rate limits.

This skill provides comprehensive tools to monitor the real-time availability, status, and performance of various large language models (LLMs) accessed via OpenRouter. It supports active health probes, catalog checks, and scheduled monitoring via Python and Bash, ensuring robust fault detection and failover logic for production systems that rely on external AI APIs.