Skill UI

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.

Design scalable AWS architectures for startups with guided workflows covering requirement gathering, architecture pattern selection, IaC template generation, cost analysis, and deployment/validation using Lambda, API Gateway, ECS, Aurora, and optimization scripts.

Design scalable AWS architectures for startups with guided workflows covering requirement gathering, architecture pattern selection, IaC template generation, cost analysis, and deployment/validation using Lambda, API Gateway, ECS, Aurora, and optimization scripts.

Orchestrate Ayrshare operations through the Composio Ayrshare toolkit via Rube MCP, covering tool discovery, connection checks, schema compliance, and multi-tool execution flows for reliable social publishing automation.

Orchestrate Ayrshare operations through the Composio Ayrshare toolkit via Rube MCP, covering tool discovery, connection checks, schema compliance, and multi-tool execution flows for reliable social publishing automation.

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.

This is a high-level SDK designed for managing the complete lifecycle of AI projects within Azure AI Foundry. It provides comprehensive tools in TypeScript to create, manage, and evaluate sophisticated AI agents, handle resource connections, process datasets, deploy models, and build custom search indexes.

This is a high-level SDK designed for managing the complete lifecycle of AI projects within Azure AI Foundry. It provides comprehensive tools in TypeScript to create, manage, and evaluate sophisticated AI agents, handle resource connections, process datasets, deploy models, and build custom search indexes.

This SDK provides a comprehensive interface for managing application configuration within Azure App Configuration using Python. It enables centralized management of settings, allows controlling feature flags for gradual rollouts, and facilitates version control through configuration snapshots. It supports various authentication methods, including connection strings and Entra ID, making it ideal for robust, dynamic microservices deployment.

This SDK provides a comprehensive interface for managing application configuration within Azure App Configuration using Python. It enables centralized management of settings, allows controlling feature flags for gradual rollouts, and facilitates version control through configuration snapshots. It supports various authentication methods, including connection strings and Entra ID, making it ideal for robust, dynamic microservices deployment.