Skill UI

Utilizes the Azure AI Projects SDK's ImageBasedHostedAgentDefinition to build robust, container-based AI agents deployed in Azure AI Foundry. This workflow is essential for creating production-grade agents that require custom logic, precise resource allocation (CPU/Memory), and integration of advanced tools like code interpreters.

A comprehensive guide covering best practices for designing developer-friendly REST APIs. Learn proper resource naming conventions (nouns, plural, kebab-case), effective use of HTTP methods (GET, POST, PUT, PATCH, DELETE), and semantic status codes (4xx, 5xx). The guide also details advanced topics like cursor-based pagination, field filtering, query parameter usage, and robust error handling formats.

A comprehensive guide covering best practices for designing developer-friendly REST APIs. Learn proper resource naming conventions (nouns, plural, kebab-case), effective use of HTTP methods (GET, POST, PUT, PATCH, DELETE), and semantic status codes (4xx, 5xx). The guide also details advanced topics like cursor-based pagination, field filtering, query parameter usage, and robust error handling formats.

This skill provides the Azure Resource Manager SDK for .NET, enabling developers to programmatically manage PostgreSQL Flexible Server deployments on Azure. It covers core cloud automation workflows such as creating the server, setting up databases, configuring firewall rules, and updating server parameters using C# code. Ideal for cloud infrastructure management and CI/CD pipelines.

This SDK provides the management plane interface for provisioning and managing Azure SQL resources (like servers, databases, elastic pools, and firewall rules) within the Azure Resource Manager framework. Built for .NET developers, it allows users to programmatically handle infrastructure setup and configuration, making it ideal for DevOps automation and infrastructure-as-code workflows.

This skill serves as an expert guide for writing, reviewing, and optimizing AWS CloudFormation templates. It covers foundational best practices, including utilizing parameterized environments, implementing nested stacks, managing stateful resources with deletion policies, and ensuring production-grade infrastructure consistency. Use it when building robust and maintainable Infrastructure as Code (IaC) for AWS.

This skill simulates a documentation expert, capable of generating comprehensive, maintainable technical documentation directly from source code. It analyzes codebases to produce various artifacts, including API documentation, system architecture diagrams, comprehensive user guides, and technical reference manuals. It is essential for standardizing documentation and building automated documentation pipelines in large, complex projects.

This guide provides methods to implement robust data handling, secret detection, and compliance patterns within code reviews (e.g., GDPR, CCPA). It teaches users how to configure CodeRabbit to exclude sensitive files (like .env or keys), detect hardcoded secrets, limit the review scope to active source code, and ensure that PII is properly handled during the CI/CD process.

A comprehensive, phased guide detailing how to migrate your code review process to CodeRabbit. It covers the entire journey, from assessing current tools (like SonarCloud, DeepSource, or manual reviews) and mapping existing rules, through to running a parallel pilot phase and finally achieving full adoption. Ideal for engineering managers or DevOps teams planning a major CI/CD tool transition.

This skill automatically generates comprehensive and highly structured Pull Request (PR) descriptions directly from Git diffs. It goes beyond simple summaries by automatically adding detailed change categories (e.g., source, test, config), security risk assessments, and required review checklists based on the modified file types. Use this when submitting complex code changes or when the diff is large and requires explicit structure for thorough review.

A comprehensive guide derived from C++ Core Guidelines, enforcing modern, safe, and idiomatic practices for C++17, C++20, and C++23. It emphasizes crucial principles like RAII, type safety, immutability, and proper resource ownership using smart pointers. Use this when writing new features, reviewing existing code, or making architectural decisions to ensure code quality and consistency.

A comprehensive guide to optimizing context window usage within AI coding environments like Cursor. Learn how to strategically use @-mentions, manage context pills, and leverage different context sources (codebase, documentation, web) to prevent context overflow and ensure the AI generates highly accurate, relevant, and context-aware code suggestions and answers for complex development tasks.