Skill UI

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.

This skill provides comprehensive scripts and workflows to automatically identify and remove unused AWS resources across multiple services (EBS, S3, EC2, EIPs). By automating the cleanup of orphaned volumes, old snapshots, and stale data, users can eliminate cloud waste, significantly optimizing their AWS expenditure and ensuring a cost-efficient infrastructure.

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.

An expert tool for generating comprehensive C4 Code-level documentation. It analyzes existing code directories to automatically extract and document critical architectural details, including function signatures, class definitions, method dependencies, and internal data flows. It supports generating various Mermaid diagrams (classDiagram, flowchart) to visualize complex system components, ensuring accurate and maintainable technical documentation.

A comprehensive skill for creating, editing, and automating complex spreadsheet workflows using LibreOffice Calc. This includes generating new ODS files, performing format conversions (XLSX, CSV, PDF, etc.), executing advanced formulas, and automating data processing through Python scripting (UNO, ezodf) or command-line interfaces. Ideal for data analysis, reporting, and batch processing tasks.

A comprehensive Python SDK for interacting with Azure Queue Storage. This tool enables reliable, asynchronous communication patterns by managing message queuing, task distribution, and data processing workflows. It supports core operations including sending, receiving, peeking, updating, and deleting messages, making it ideal for building resilient, decoupled backend systems on Azure.

Automate Benzinga workflows through the Composio toolkit by using Rube MCP tools; search schemas, verify connections, and run multi-tool executions with managed sessions and memory objects for reliable data operations.

Automates Big Data Cloud operations through Composio’s toolkit by routing discovery, connection checks, and multi-tool execution via Rube MCP commands so you always work with current schemas before running workflows.