Can I use Claude models with this skill?

Yes, ADK Core supports non-Gemini models like Claude and OpenAI by using the LiteLLM prefix (e.g., anthropic/claude-sonnet-4) in your agent configuration.

How does ADK Core handle authentication?

It provides setup guidance for both Google AI Studio (using GOOGLE_API_KEY) for prototyping and Vertex AI (using GOOGLE_CLOUD_PROJECT) for enterprise-grade production environments.

Should I use YAML or Python for agent definitions?

YAML is recommended for rapid prototyping of simple agents, while Python is better for complex logic, custom agent classes, and deep integration with other libraries.

How do I start a new project with ADK Core?

Use the 'adk create' command within your terminal to scaffold a standard project structure including the core agent.py, initialization files, and environment configuration.

What is the difference between LlmAgent and BaseAgent?

LlmAgent is the standard type for AI reasoning and tool use, while BaseAgent is designed for extending with custom, deterministic Python logic without LLM overhead.

ADK Core: Google Agent Development Kit

Name: ADK Core: Google Agent Development Kit
Author: MattMagg

byMattMagg

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Data Science & ML

Bootstraps and configures intelligent AI agents using the Google Agent Development Kit (ADK) with support for multiple LLM providers.

About

ADK Core is a comprehensive skill designed to streamline the initialization and configuration of Google Agent Development Kit (ADK) projects within Claude Code. It provides a standardized workflow for setting up development environments, managing authentication via Google AI Studio or Vertex AI, and defining agents through either Python code or declarative YAML. Whether you are building reasoning-heavy LlmAgents or custom deterministic BaseAgents, this skill offers the implementation patterns and model selection guidance—including LiteLLM support for Claude and OpenAI—needed to architect robust agentic systems.

Key Features

Project scaffolding and automated workspace initialization
Multi-model support including Gemini, Claude, and OpenAI via LiteLLM
Custom agent extensibility for non-LLM logic and orchestration
Dual-mode configuration via Python code or declarative YAML
Seamless authentication setup for Google AI Studio and Vertex AI
2 GitHub stars

Use Cases

Switching agent models between Gemini and Anthropic Claude for testing
Quickly bootstrapping a new agentic project with a standardized structure
Creating custom deterministic agents for specific API orchestration tasks

About

Key Features

Project scaffolding and automated workspace initialization
Multi-model support including Gemini, Claude, and OpenAI via LiteLLM
Custom agent extensibility for non-LLM logic and orchestration
Dual-mode configuration via Python code or declarative YAML
Seamless authentication setup for Google AI Studio and Vertex AI
2 GitHub stars

Use Cases

Switching agent models between Gemini and Anthropic Claude for testing
Quickly bootstrapping a new agentic project with a standardized structure
Creating custom deterministic agents for specific API orchestration tasks