Google ADK Python Skill

Develop and deploy Python-based AI agents on Vertex AI and Cloud Run.

1|Updated Feb 17, 2026

Search Tags:#deployment #python #llm #ai agents #agent development #orchestration #google adk

Ready to run

npx skills add https://github.com/chef0111/physthink --skill google-adk-python-skill

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: Google ADK Python Skill
Source: https://github.com/chef0111/physthink/tree/main/.agents/skills/google-adk-python
Command: npx skills add https://github.com/chef0111/physthink --skill google-adk-python-skill

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve?

This Skill simplifies the creation, evaluation, and deployment of AI agents, especially those requiring complex orchestration, tool integration, and multi-agent coordination.

Core Features & Use Cases

Agent Development: Build LLM-powered agents (LlmAgent) and workflow agents (SequentialAgent, ParallelAgent, LoopAgent).
Tool Integration: Seamlessly integrate pre-built tools (like Google Search, code execution) or custom Python functions.
Multi-Agent Systems: Design hierarchical agent structures for complex task delegation.
Deployment: Deploy agents to Vertex AI Agent Engine, Cloud Run, or custom infrastructure.
Use Case: Develop an AI research assistant that can search the web, summarize findings, and draft reports, all orchestrated by ADK.

Quick Start

Install the Google ADK Python library by running pip install google-adk.

Frequently Asked Questions about Google ADK Python Skill

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

FAQPage Schema

How do I build and deploy AI agents with Python using Google ADK?▼

Google ADK lets you build and deploy AI agents in Python by supporting LLM-based and workflow-driven agents with integrated tools and multi-agent architectures. You can deploy them directly to Vertex AI Agent Engine or Cloud Run.

What are multi-agent architectures in Google ADK?▼

Multi-agent architectures in Google ADK involve designing hierarchical agent structures for complex task delegation. You can orchestrate these systems using workflow agents like SequentialAgent, ParallelAgent, and LoopAgent.

Can I use custom Python functions for tool integration in my AI agent?▼

Yes, you can integrate tools into your AI agent by using pre-built options like Google Search and code execution, or by seamlessly integrating your own custom Python functions for specific tasks.

Do I need a specific Python version to develop LLM agents with Google ADK?▼

Yes, developing LLM agents with Google ADK requires Python 3.8 or higher. You must also adhere to the framework's code-first development principles to create and orchestrate your agents.

What is the best way to orchestrate complex tasks like an AI research assistant?▼

The best way to orchestrate complex tasks like an AI research assistant is using ADK to coordinate web search, summarization, and report drafting. ADK facilitates multi-agent coordination and workflow orchestration for these delegations.