Skill UI

Specializes in the expert deployment and orchestration of production-grade multi-agent systems using Google's Agent Development Kit (ADK). This skill manages the complex lifecycle, including AgentCard discovery, A2A protocol communication, state management via Memory Bank, and secure execution within the Code Execution Sandbox. Ideal for setting up robust, enterprise-level AI workflows on the Vertex AI Agent Engine, especially during CI/CD pipelines.

A comprehensive toolkit for designing, architecting, and evaluating complex multi-agent systems. It provides structured patterns—including Supervisor, Swarm, and Pipeline—for system architecture, defines agent roles (Coordinator, Specialist), and covers best practices for communication (Event Sourcing, Message Passing), tool design, and safety guardrails, ensuring robust and scalable AI workflows.

A comprehensive SDK for building real-time, bidirectional voice AI applications using Azure AI services within the .NET framework. This library facilitates seamless voice interactions, supporting WebSocket communication, advanced features like function calling, and handling audio/text streaming events for developing sophisticated virtual assistants.

This SDK enables the development of real-time, conversational AI applications using Azure Cognitive Services. It supports bidirectional communication via WebSockets, allowing for continuous audio streaming (mic input) and receiving synthesized speech output. Ideal for building voice assistants, IVR systems, and interactive voice experiences.

This skill provides capabilities for bidirectional audio processing using fal.ai models. It supports Text-to-Speech (TTS), converting written text into natural-sounding speech, and Speech-to-Text (STT), accurately transcribing spoken audio into readable text. Use this skill for applications requiring high-quality audio input analysis or synthetic voice generation, such as virtual assistants, content digitization, or multilingual communication tools.

This skill provides implementation patterns for building enterprise-grade AI voice agents and automating complex phone call workflows using the Retell AI platform. It covers SDK integration, resource management, and handling common telephony APIs errors, making it ideal for developers building conversational AI applications and advanced communication systems.

This comprehensive guide demonstrates how to build and test a voice agent using the Retell AI SDK in TypeScript. It walks through configuring the underlying LLM with a custom persona, creating the voice agent instance, and finally initiating both outbound phone calls and web calls through the API. This is essential for integrating AI-powered voice communication into customer service platforms, call centers, or telephony automation systems.

This skill provides implementation patterns and guidance for optimizing Retell AI-powered voice agents and telephony applications. It covers SDK usage, agent listing, and essential error handling (like rate limiting and unauthorized access), ensuring robust and reliable voice communication workflows for enterprise use.

This skill provides implementation patterns for managing API rate limits when integrating Retell AI for voice agents and telephony systems. It guides developers on handling common API errors (such as 429 Rate Limited) and implementing robust backoff strategies, ensuring stable and scalable operation for complex voice and communication applications.

This skill provides implementation patterns for building robust and reliable AI voice agents and telephony automation systems using the Retell AI SDK. It covers best practices for handling common communication errors (like rate limiting or invalid API keys) and ensures stable interaction flow for voice-based applications and phone call automation scenarios.

A comprehensive protocol defining communication rules and orchestration patterns for multi-agent C-suite teams. It structures complex cross-functional analyses, simulates board meetings, and enforces hard rules—such as depth limits and loop prevention—to ensure consistent, verifiable, and non-circular business insights.

This skill guides the generation of a complete, production-ready Model Context Protocol (MCP) server using C# and .NET. It covers advanced architectural patterns, including Host builder setup, proper dependency injection, structured logging, and implementing robust functional tools. Ideal for developers building sophisticated AI agents or backend services that require standardized communication and tool invocation capabilities.