Skill UI

This expert skill guides advanced integration with Atlassian products (Jira and Confluence) using the MCP protocol. It covers full lifecycle management, including setting up OAuth/API token authentication, designing complex JQL/CQL queries, automating sprint workflows, syncing documentation, and robust debugging of API calls. Ideal for system architects and developers building cohesive enterprise workflows.

A comprehensive platform designed for building, deploying, and managing continuous, autonomous AI agents. Users can create complex, multi-step automation workflows using a visual, drag-and-drop node editor, or extend functionality using a dedicated developer toolkit. Ideal for implementing persistent agents triggered by webhooks, schedules, or manual input, enabling sophisticated, end-to-end AI automation pipelines.

A comprehensive platform designed for building, deploying, and managing continuous, autonomous AI agents. Users can create complex, multi-step automation workflows using a visual, drag-and-drop node editor, or extend functionality using a dedicated developer toolkit. Ideal for implementing persistent agents triggered by webhooks, schedules, or manual input, enabling sophisticated, end-to-end AI automation pipelines.

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.

The Azure AI Projects SDK enables developers to build and manage sophisticated, end-to-end AI applications directly on Microsoft Foundry. It provides comprehensive client operations for managing agents, datasets, model deployments, and indexes. Key features include integrating diverse tools (like code interpreters and file search) and handling complex conversational flows, making it ideal for building production-grade AI workflows.

The Azure AI Projects SDK enables developers to build and manage sophisticated, end-to-end AI applications directly on Microsoft Foundry. It provides comprehensive client operations for managing agents, datasets, model deployments, and indexes. Key features include integrating diverse tools (like code interpreters and file search) and handling complex conversational flows, making it ideal for building production-grade AI workflows.

A comprehensive Java SDK for building robust, server-side call automation workflows using Azure Communication Services (ACS). It allows developers to implement sophisticated IVR systems, dynamic call routing, interactive media playback (Text-to-Speech, audio files), speech and DTMF recognition, call recording management, and participant handling. Ideal for building sophisticated customer service bots or automated notification systems.

A comprehensive Java SDK for building robust, server-side call automation workflows using Azure Communication Services (ACS). It allows developers to implement sophisticated IVR systems, dynamic call routing, interactive media playback (Text-to-Speech, audio files), speech and DTMF recognition, call recording management, and participant handling. Ideal for building sophisticated customer service bots or automated notification systems.

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 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.

This SDK provides comprehensive Python support for Azure Data Lake Storage Gen2. It enables developers to interact with hierarchical file systems, performing essential big data operations such as creating, listing, uploading, downloading, and managing metadata for files and directories. Ideal for building data analytics pipelines and cloud-based data processing workflows.