Skill UI

This generator provides a comprehensive, production-ready template for building a Model Context Protocol (MCP) server using Kotlin. It sets up the full Gradle structure, integrates essential dependencies (MCP SDK, Ktor, Coroutines), and includes robust placeholders for custom tools, error handling, and testing, accelerating the development of context-aware backend services.

This tool generates a complete, production-ready project scaffold for a Model Context Protocol (MCP) server written in Ruby. It includes the necessary file structure, gem dependencies, Rake tasks, and boilerplate code for defining tools, prompts, and resources, accelerating backend development for AI applications.

This comprehensive guide provides step-by-step instructions for setting up a development environment to use AWS CDK (Cloud Development Kit) with Python. It covers installing prerequisites (Node.js, AWS CLI), initializing a CDK project, managing Python dependencies, and mastering the full deployment workflow, enabling users to define and deploy scalable AWS infrastructure as code.

This skill guides the integration of Arize AX tracing into existing applications, especially complex LLM applications. It follows a structured, two-phase, agent-assisted flow: first analyzing the codebase (read-only) to understand dependencies, and then implementing instrumentation. It supports multi-language environments (Python, TypeScript, Java, Go) and integrates deeply with OpenTelemetry and various LLM providers, ensuring comprehensive observability without altering core business logic.

This skill analyzes Azure resource groups in depth, identifying all resources, their configurations, and complex interdependencies. It maps relationships—including network connections, data flows, and managed identities—to generate comprehensive, detailed Mermaid architecture diagrams. Use this when you need a clear, structured visualization and full documentation of an Azure environment's topology.

Helps produce Dockerfiles and a detailed containerization plan for ASP.NET .NET Framework projects running in Windows containers, covering configuration settings, IIS, dependencies, and deployment steps.

Discovers all projects in a .NET solution, classifies each for Oracle-to-PostgreSQL migration eligibility, and produces a persistent master migration plan. Use when starting a multi-project Oracle-to-PostgreSQL migration, creating a migration inventory, or assessing which .NET projects contain Oracle dependencies.

Automates importing live Azure environments into Terraform by discovering subscriptions, groups, or resource IDs, mapping dependencies, and generating AVM-based IaC files ready for validation and planning.

A comprehensive guide to configuring complex nodes in workflow automation platforms like n8n. Learn best practices for understanding operation-specific field requirements, managing property dependencies, and utilizing progressive disclosure techniques (Standard vs. Full detail) to ensure accurate and efficient workflow setup.

This skill provides structured procedures for managing NuGet packages in .NET projects and solutions. It strictly enforces the use of the `dotnet` CLI for adding, removing, and updating dependencies, prioritizing project integrity. It guides users through a mandatory workflow for version updates, including version verification and running `dotnet restore`, ensuring a stable and consistent development environment.

This skill generates a detailed, multi-phase plan for complex, multi-file refactoring projects. It ensures safety by first analyzing the codebase, identifying dependencies, and structuring changes in a safe sequence (e.g., Types first, then implementations, followed by tests and cleanup). It forces the AI to output a comprehensive plan, including rollback steps and verification points, and waits for user confirmation before making any actual code changes.

A comprehensive tool that analyzes complex codebases to generate detailed, structured architectural blueprints. It automatically detects and documents the entire technology stack, including primary languages (.NET, Java, Python, etc.), dependencies, versions, licensing, and implementation patterns. The output provides actionable documentation covering coding conventions, usage examples (API, data access), and visual architecture maps, ensuring consistency across guided software development projects.