Skill UI

This advanced prompt acts as a structured guide for generating comprehensive, enterprise-grade technical implementation plans. It forces the detailed breakdown of a feature based on a PRD, covering system architecture (Mermaid diagrams), database schema design, API specifications, frontend component hierarchy, and deployment strategies, all while adhering to a monorepo structure. Ideal for large-scale SaaS development.

This skill is designed to retrieve and display detailed usage metrics for GitHub Copilot within organizations and enterprises. Users can analyze adoption rates, total suggestions, acceptance rates, and chat interactions, broken down either by the entire organization/enterprise or on a per-user basis. It supports querying data for specific historical dates using GitHub CLI and REST API.

This comprehensive guide covers best practices for building robust database systems. It teaches crucial concepts like schema normalization, effective indexing strategies, selecting the right database (e.g., SQLite vs PostgreSQL) and ORM, and optimizing queries to prevent common performance issues like N+1 problems. It emphasizes making context-aware architectural decisions.

A comprehensive methodology guiding technical professionals through the design process before coding. It helps structure complex features by producing detailed design documents, including system overviews, data models, API specifications, multiple trade-off analyses, and implementation plans, ensuring robustness and clarity from the start.

This comprehensive guide outlines best practices for writing high-quality, scalable, and maintainable code in .NET/C#. It covers core architectural principles, including SOLID, dependency injection, and design patterns (e.g., Command Handler). Furthermore, it addresses modern challenges such as structured logging, async/await patterns, secure coding, robust testing standards, and advanced AI integration using Semantic Kernel.

A comprehensive code review tool designed for C#/.NET projects. It evaluates the implementation of key design patterns (Command, Factory, Repository) and adherence to SOLID principles. The review covers architecture, best practices (async/await, logging), security, testability, and clean code principles, providing actionable recommendations for improvement.

This comprehensive guide provides best practices for developing robust and efficient data access layers using Entity Framework Core. It covers critical areas including DbContext design, performance optimization (e.g., AsNoTracking, Select projection), secure querying techniques, migration strategies, and testing methodologies, ensuring the creation of scalable and maintainable applications.

This comprehensive guide outlines established best practices for developing robust, scalable, and high-quality enterprise applications using Spring Boot and Java. It covers structuring projects, implementing dependency injection, designing RESTful APIs, managing transactions, securing endpoints, and utilizing advanced testing strategies (Unit, Integration). Ideal for developers aiming for industry-standard code quality.

This skill performs a comprehensive security audit of Model Context Protocol (MCP) server configurations found in .mcp.json files. It is designed to identify critical vulnerabilities, including hardcoded secrets (API keys, tokens), dangerous shell injection patterns, unpinned dependencies, and compliance issues regarding approved server lists. Use this skill during security reviews, project onboarding, or pre-commit checks to ensure secure deployment.

This tool automates the entire process of creating a complete, production-ready application structure solely from an OpenAPI (Swagger) specification. It analyzes the spec to design the application architecture, generating all necessary layers including controllers, service logic, data models (DTOs), and repositories, adhering to best practices, framework conventions, and separation of concerns. The output includes unit tests, configuration files, and setup instructions, providing a robust, ready-to-use codebase.

An advanced, AI-powered agent designed to generate comprehensive and workable unit tests for virtually any programming language (e.g., Python, C#, Java, Go, TypeScript). It operates via a sophisticated multi-agent pipeline (Research → Plan → Implement → Build → Test → Fix → Lint). This ensures generated tests are not only written following project conventions but also compile, pass all tests, and effectively improve code coverage.

This library provides a complete and verified set of grep command patterns designed for auditing existing React codebases. It is essential for developers preparing for major React upgrades, specifically migration audits for React 18.3.1 or React 19. It detects deprecated APIs, removed features, unsafe lifecycle methods, batching vulnerabilities, and dependency conflicts, ensuring a smooth transition.