google-adk-python

Name: google-adk-python
Availability: InStock
Author: beauschwab

Map Google ADK documentation topics to Python code examples for agent prototyping.

Updated Feb 6, 2026

Search Tags:#deployment #python #tutorials #tools #agent-development #reference-guides #google-adk

Ready to run

npx skills add https://github.com/beauschwab/airflow-dbt-datahub --skill google-adk-python-beauschwab

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: google-adk-python
Source: https://github.com/beauschwab/airflow-dbt-datahub/tree/main/.agents/skills/google-adk-python
Command: npx skills add https://github.com/beauschwab/airflow-dbt-datahub --skill google-adk-python-beauschwab

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve?

This skill provides expert guidance and ready-to-run Python references for building agents with the Google Agent Development Kit (ADK) in Python, helping developers accelerate learning and implementation.

Core Features & Use Cases

Topic-aligned references: Quick access to get-started, agents/models, tools, streaming, callbacks, runtime/architecture, deployment/operations, tutorials, API, and general information, each linking to official Markdown docs and Python examples.
Reference-driven workflow: Maps documentation topics to corresponding Python code snippets, enabling hands-on exploration and rapid prototyping across common agent tasks.
Use Case: A developer wants to prototype a multi-tool agent that uses Google Search and code execution, then deploys it on GKE with observability hooks.

Quick Start

Identify your area of interest (e.g., getting started, agents & models, or tools), and consult the corresponding reference file in references/ to view official docs and Python examples.

Frequently Asked Questions about google-adk-python

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

FAQPage Schema

How do I build AI agents with Google ADK in Python?▼

To build AI agents with Google ADK in Python, follow guided references that map documentation topics like agents, models, and tools directly to ready-to-run Python code snippets for rapid prototyping.

What is the best way to deploy a multi-tool agent using Google ADK?▼

The best way to deploy a multi-tool agent using Google ADK is by consulting deployment and operations references, which provide Python examples for deploying agents on infrastructure like GKE with observability hooks.

Can I use streaming and callbacks in a Python agent development workflow?▼

Yes, you can implement streaming and callbacks in a Python agent development workflow by accessing topic-aligned references that link official documentation to practical Python code examples for these specific features.

Does Google ADK support integrating tools like Google Search and code execution?▼

Google ADK supports integrating tools like Google Search and code execution, providing reference-driven workflows that map tool documentation to Python snippets for hands-on exploration and multi-tool agent creation.

What do I need to prototype end-to-end AI agents with Google ADK?▼

To prototype end-to-end AI agents with Google ADK, you need the Python environment and the topic-aligned reference files covering getting started, agents, tools, and deployment to facilitate rapid learning.