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 comprehensive guide outlines best practices for developing high-quality, idiomatic, and maintainable enterprise applications using Kotlin and Spring Boot. It covers architectural patterns, dependency injection using primary constructors, managing state with data classes, implementing robust RESTful APIs, handling transactions, and leveraging Kotlin features like null safety and Coroutines for asynchronous programming. It also provides guidance on modern testing strategies (Kotest, Testcontainers).

A comprehensive expert guide for utilizing the n8n-mcp toolset. This resource covers essential workflows for node discovery, configuration validation, and complex workflow management. It provides detailed guidance on tool selection, parameter formats, and best practices to master advanced automation development within n8n.

A general-purpose skill for writing and executing end-to-end (E2E) browser automation tests using Playwright. It handles complex scenarios such as login flows, form submission, responsive viewport testing, and checking for broken links. The skill automatically detects local development servers and executes custom scripts in a safe, temporary directory, providing real-time debugging and results visualization.

A powerful toolset for automating core PostHog product analytics tasks via Rube MCP. It enables developers and analysts to capture user events, list and filter event data, manage feature flags (creation, retrieval, listing), and inspect user profiles. Ideal for integrating advanced product tracking and A/B testing workflows directly into development pipelines.

This guide implements the Red-Green-Refactor cycle, the core methodology of Test-Driven Development (TDD). It teaches developers to first write a failing test (RED), then implement the minimum required code to make the test pass (GREEN), and finally improve the structure and clarity of the code without changing its behavior (REFACTOR). Use this guide when mastering TDD, ensuring robust unit test coverage, or following best practices for writing resilient software.

Performs a systematic and structured investigation to determine the true source of bugs, errors, and unexpected system behavior, rather than merely treating symptoms. This method utilizes techniques like the Five Whys, hypothesis-driven testing, stack trace analysis, and gathering evidence (logs, git diffs) across multiple phases. It is ideal for complex, intermittent, or deeply rooted technical issues in software development.

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.

Leverage AI-powered exploratory testing to thoroughly audit web applications and verify functionality. This skill simulates user interaction, detecting complex bugs, validating critical flows (like checkout or login), and checking accessibility compliance. Use it proactively after development to ensure quality before deployment.

This skill provides comprehensive guidance for building and refining applications, plugins, and function-calling flows using the Semantic Kernel framework. It supports multiple languages, including .NET and Python. Guidance emphasizes consulting the latest official documentation, adhering to best practices (like async patterns and strong typing), and correctly handling multi-ecosystem development.

A comprehensive tool that analyzes existing codebases to generate detailed, definitive architectural blueprints. It automatically detects technology stacks, identifies architectural patterns (e.g., Microservices, Clean Architecture), and documents implementation details, including dependency flow, cross-cutting concerns (security, logging), and data models. This ensures architectural consistency, aids in onboarding new team members, and guides future development efforts.

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.