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ADK Developer

Guide AI agent development with the Google Agent Development Kit.

Updated May 13, 2026
Search Tags:#deployment#LLM integration#ADK#AI agent development#toolset#Google Agent Development Kit#Agent orchestration
One-click install
npx skills add https://github.com/hpuri/salus-a2ui --skill adk-developer
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: ADK Developer
Source: https://github.com/hpuri/salus-a2ui/tree/main/skills/adk_developer
Command: npx skills add https://github.com/hpuri/salus-a2ui --skill adk-developer

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires google-adk, google-genai, llama-index, and includes scripts (resource) and references (resource) components.

What problem does it solve?

This Skill provides a comprehensive guide to building, orchestrating, and deploying AI agents using the Google Agent Development Kit (ADK), addressing the complexities of agent development and deployment.

Core Features & Use Cases

  • ADK Best Practices: Offers best practices and guidelines for ADK development.
  • Agent Development: Provides a step-by-step guide to building LLM and custom agents.
  • Orchestration: Explains how to use Workflow agents for deterministic control flow.
  • Multi-Agent Systems: Describes communication mechanisms and the A2A Protocol.
  • Model Integration: Details integration of various LLMs like Gemini and LiteLLM.
  • Tools: Lists and explains tools for agent capabilities, including FunctionTools, LangChainTool, and OpenAPIToolset.
  • Deployment Strategies: Covers local development, Vertex AI Agent Engine, and Cloud Run deployment.
  • Evaluation and Safety: Discusses agent evaluation and safety considerations.
  • Debugging and Logging: Provides guidance on debugging, logging, and observability.
  • Performance Optimization: Offers tips for optimizing agent performance.
  • General Best Practices: Lists common pitfalls and best practices in ADK development.
  • Official API & CLI References: Includes references to Python API, CLI, and REST API.

Quick Start

Start a new ADK project by initializing a virtual environment and installing dependencies with uv.

Frequently Asked Questions about ADK Developer

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I build and orchestrate AI agents using Google Agent Development Kit?▼

To build AI agents with Google Agent Development Kit, you orchestrate LLM and custom agents using Workflow agents for deterministic control flow and the A2A Protocol for multi-agent communication.

Can I integrate external LLMs like LiteLLM with ADK agents?▼

Yes, ADK supports model integration with various LLMs including Gemini and LiteLLM, enabling you to connect external models to power your custom agents.

How do I deploy ADK agents to cloud environments?▼

ADK agents can be deployed using local development setups, Vertex AI Agent Engine, or Cloud Run, providing flexible strategies for cloud deployment.

What tools can I use to add capabilities to my ADK agents?▼

ADK agents can use tools like FunctionTools, LangChainTool, and OpenAPIToolset to extend their capabilities and interact with external systems.

Do I need Python and virtual environment setup to start ADK development?▼

Yes, ADK development requires Python and familiarity with the framework. You initialize a new project by setting up a virtual environment and installing dependencies using uv.

What are the limitations and debugging strategies for ADK multi-agent systems?▼

ADK provides guidelines for debugging, logging, and observability to address performance optimization and safety considerations, helping identify common pitfalls in multi-agent systems.

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