Skill UI

Automates generation and execution of API endpoint tests for REST and GraphQL services, covering CRUD operations, authentication workflows, OpenAPI contract validation, and response verification (status, headers, body).

A comprehensive guide detailing best practices for creating modern, clean, and highly maintainable user interfaces using Avalonia and Zafiro.Avalonia. It emphasizes leveraging semantic containers, defining shared styles, and utilizing generic components to dramatically reduce XAML redundancy and improve code structure. Learn to adopt patterns like Behaviors over Converters, and prevent deep nesting for optimal developer experience.

Provides expert AWS architecture, security, and implementation guidance backed by MCP tooling, helping teams choose services, migrate workloads, and troubleshoot production issues.

Provides canonical AWS serverless patterns covering Lambda handlers, DynamoDB single-table modeling, CDK infrastructure, and S3 event processing along with anti-patterns and a checklist for production-ready deployments.

A comprehensive guide covering advanced offensive techniques for AWS cloud environments. Techniques include detailed IAM enumeration, privilege escalation paths, SSRF exploitation targeting metadata endpoints (IMDSv1/v2), S3 bucket exploitation, and Lambda function code extraction. Essential for security professionals and red team operations conducting authorized cloud vulnerability assessments.

This comprehensive guide covers the best practices for building production-ready, scalable serverless applications on Amazon Web Services (AWS). Learn to leverage core services like Lambda, API Gateway, and DynamoDB, and implement advanced patterns such as event-driven architectures (SQS/SNS). The content emphasizes performance optimization, robust error handling, structured logging, and deploying infrastructure using SAM/CDK.

This comprehensive guide covers the best practices for building production-ready, scalable serverless applications on Amazon Web Services (AWS). Learn to leverage core services like Lambda, API Gateway, and DynamoDB, and implement advanced patterns such as event-driven architectures (SQS/SNS). The content emphasizes performance optimization, robust error handling, structured logging, and deploying infrastructure using SAM/CDK.

This skill provides comprehensive guidance and established patterns for developing applications on Amazon Web Services (AWS). It focuses specifically on implementing robust infrastructure automation and adhering to best-practice cloud architecture patterns, ensuring scalable, secure, and resilient cloud deployments. Use this when building enterprise-grade systems requiring modern cloud development methodologies.

This skill provides comprehensive guidance and established patterns for developing applications on Amazon Web Services (AWS). It focuses specifically on implementing robust infrastructure automation and adhering to best-practice cloud architecture patterns, ensuring scalable, secure, and resilient cloud deployments. Use this when building enterprise-grade systems requiring modern cloud development methodologies.

This is a low-level SDK for Java designed to create and manage persistent AI agents within Azure AI. It provides comprehensive tools for handling the entire agent lifecycle, including creating agents, managing conversation threads, sending messages, running agent processes, and cleaning up resources. Ideal for building robust, stateful AI applications requiring fine-grained control over agent interactions.

This is a low-level SDK for Java designed to create and manage persistent AI agents within Azure AI. It provides comprehensive tools for handling the entire agent lifecycle, including creating agents, managing conversation threads, sending messages, running agent processes, and cleaning up resources. Ideal for building robust, stateful AI applications requiring fine-grained control over agent interactions.

This is a high-level SDK for .NET that provides comprehensive client access to Azure AI Foundry services. It enables developers to manage complex AI workflows, including creating and managing conversational agents, handling data connections, uploading datasets, managing model deployments, and setting up search indexes within an Azure AI project structure. Ideal for integrating advanced AI capabilities into enterprise applications.