Skill UI

This solution implements robust Role-Based Access Control (RBAC) and multi-tenancy for third-party AI services. By utilizing an application proxy layer, it allows organizations to manage multiple teams, assign separate API keys, enforce granular content policies (e.g., filtering prohibited terms), and track daily budgets. This ensures secure, governed, and scalable resource usage in enterprise environments.

This document provides production-grade patterns for integrating with the Ideogram API in TypeScript and Python. It addresses common challenges in API usage, including implementing singleton client management, robust exponential backoff retry logic for rate limiting, and strict response validation using libraries like Zod. Use this guide when building reliable, scalable applications that depend on external AI image generation services.

An expert guide for building scalable, cloud-native enterprise applications using the latest Java 21+ features, including Virtual Threads and Pattern Matching. Deep mastery of the Spring Boot 3.x ecosystem, Spring Cloud, and microservices architecture. Covers full development lifecycle, from JVM performance tuning (GraalVM, ZGC) to robust testing (Testcontainers) and secure DevOps practices (Kubernetes, CI/CD).

This comprehensive guide covers the entire MLOps lifecycle, specializing in building robust, scalable, and production-grade Machine Learning systems. Expertise includes orchestrating complex ML pipelines using Kubeflow, Airflow, Prefect, and cloud-native services (AWS SageMaker, Azure ML, GCP Vertex AI). It covers experiment tracking (MLflow, W&B), model versioning, model registries, infrastructure as code (Terraform), and container deployment using Kubernetes. Ideal for engineers tasked with moving ML models from research to reliable, managed production environments.

Guides teams through designing and building scalable modular monolith backends in NestJS, leveraging DDD, Clean Architecture, CQRS, and NX monorepos while planning evolution paths to microservices.

Hands-on lab guide to configuring HTTP, HTTPS, SNMP, and SMB services for pentesting, covering setup, firewall rules, enumeration tools, and log inspection in controlled environments.

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).

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.

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 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 patterns for building highly reliable applications that interact with external Large Language Model (LLM) APIs, such as Perplexity Sonar. It implements critical reliability techniques including Circuit Breakers, Model Fallback, Streaming Timeout handling, and Caching layers. Use this to ensure your application maintains high availability and graceful degradation even when external services experience intermittent failures or variable performance.