Can I build multi-agent systems with this skill?

Yes, it supports hierarchical coordination, where a coordinator agent can delegate tasks to specialized sub-agents, as well as sequential and parallel workflows.

Does it support human-in-the-loop workflows?

Yes, it includes patterns for implementing tool confirmation flows, ensuring sensitive operations require human approval before execution.

What is the Google Agent Development Kit (ADK)?

Google ADK is an open-source, code-first toolkit designed for building, evaluating, and deploying AI agents and multi-agent systems in Python.

Which models are best suited for Google ADK?

While model-agnostic, ADK is optimized for the Gemini family, including Gemini 1.5/2.5 Flash and Pro models.

How does this skill handle deployment?

It provides specific implementation patterns for deploying agents to Vertex AI Agent Engine, Google Cloud Run, or custom infrastructure using Docker.

Google ADK Python

Name: Google ADK Python
Author: GGPrompts

byGGPrompts

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Data Science & ML

Builds, evaluates, and deploys code-first AI agents and multi-agent systems using Google's Agent Development Kit.

About

The Google ADK Python skill provides expert guidance for architecting sophisticated AI systems using the open-source Agent Development Kit. It enables developers to implement diverse agent architectures, including dynamic LlmAgents and structured workflow patterns like sequential, parallel, or loop agents. With specialized support for tool integration, human-in-the-loop approval flows, and deployment to Google Cloud infrastructure like Vertex AI Agent Engine, this skill transforms Claude into a specialized co-pilot for professional agent engineering.

Key Features

Structured workflow patterns for sequential and parallel execution
Hierarchical multi-agent orchestration and coordination
Deployment patterns for Vertex AI and Google Cloud Run
1 GitHub stars
Custom tool integration with human-in-the-loop approval flows
Systematic agent evaluation and performance testing

Use Cases

Developing autonomous research assistants with web search and summarization capabilities
Creating complex data processing pipelines using structured Workflow Agents
Deploying production-grade AI agents to Vertex AI Agent Engine

About

Key Features

Structured workflow patterns for sequential and parallel execution
Hierarchical multi-agent orchestration and coordination
Deployment patterns for Vertex AI and Google Cloud Run
1 GitHub stars
Custom tool integration with human-in-the-loop approval flows
Systematic agent evaluation and performance testing

Use Cases

Developing autonomous research assistants with web search and summarization capabilities
Creating complex data processing pipelines using structured Workflow Agents
Deploying production-grade AI agents to Vertex AI Agent Engine