Skill UI

Automatically detects and loads specialized agent instructions from the `AGENTS.md` file in the current working directory. This skill seamlessly integrates project-specific rules and behavioral guidelines into the AI's session context, ensuring the AI operates according to project standards without manual intervention. It is crucial for maintaining specialized agent behaviors across different development tasks and directory changes.

A comprehensive guide detailing best practices for optimizing Angular applications. It covers critical topics like change detection strategies (OnPush, Signals), managing asynchronous data flows (avoiding waterfalls), optimizing bundle size via lazy loading and tree shaking, and improving rendering efficiency with modern features like @defer and trackBy. Use this when building, reviewing, or refactoring complex Angular components for peak performance.

Modern Angular UI patterns that coordinate loading spinners, skeletons, error states, empty states, and progressive data display; designed for component builders managing async data, optimistic updates, and graceful degradation.

Guides how to create routes in Next.js App Router using the app/ directory, including route files, layouts, loading/error states, dynamic routes, metadata, and organizational patterns for robust navigation.

Guides how to create routes in Next.js App Router using the app/ directory, including route files, layouts, loading/error states, dynamic routes, metadata, and organizational patterns for robust navigation.

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.

This is a high-level Software Development Kit (SDK) designed for managing the full lifecycle of AI projects within Azure AI Foundry. Built for Java, it provides robust client interfaces for core AI operations, including managing connections to Azure resources, uploading and managing datasets, creating and updating search indexes, running model evaluations, and handling deployments. It streamlines complex AI workflow orchestration.

This is a high-level Software Development Kit (SDK) designed for managing the full lifecycle of AI projects within Azure AI Foundry. Built for Java, it provides robust client interfaces for core AI operations, including managing connections to Azure resources, uploading and managing datasets, creating and updating search indexes, running model evaluations, and handling deployments. It streamlines complex AI workflow orchestration.

A comprehensive Python SDK for interacting with Azure Container Registry (ACR). This tool allows developers to manage the full container lifecycle, including listing repositories, handling tags, manipulating manifests, downloading artifacts, and managing container images within Azure's cloud environment. Ideal for implementing robust CI/CD pipelines and container automation.

A comprehensive Python SDK for interacting with Azure Container Registry (ACR). This tool allows developers to manage the full container lifecycle, including listing repositories, handling tags, manipulating manifests, downloading artifacts, and managing container images within Azure's cloud environment. Ideal for implementing robust CI/CD pipelines and container automation.

A comprehensive guide for building applications that interact with Azure Blob Storage using the Azure SDK for Java. Covers essential patterns including client initialization (via connection string or credentials), uploading/downloading data from files or streams, listing blobs, and managing containers. Ideal for developers building scalable cloud data storage solutions.

This SDK provides a comprehensive Python interface for interacting with Azure Blob Storage, Microsoft's scalable object storage service. It enables users to perform core object storage operations, including uploading, downloading, listing, deleting blobs, managing containers, and setting custom metadata. The library supports both synchronous and asynchronous workflows, making it ideal for building robust data pipelines, data lakes, or cloud-native applications that require reliable, scalable file storage.