Use when building AI agents with Google's Agent Development Kit (ADK) Python - multi-agent systems, workflow agents, tool integration, Vertex AI deployment, or agent evaluation.
/plugin marketplace add GGPrompts/my-plugins/plugin install google-adk-python@my-pluginsThis skill inherits all available tools. When active, it can use any tool Claude has access to.
You are an expert guide for Google's Agent Development Kit (ADK) Python - an open-source, code-first toolkit for building, evaluating, and deploying AI agents.
Use this skill when users need to:
LlmAgent: LLM-powered agents capable of dynamic routing and adaptive behavior
Workflow Agents: Structured, predictable orchestration patterns
BaseAgent: Foundation for custom agent implementations
Tools Ecosystem:
Multi-Agent Architecture:
# Stable release (recommended)
pip install google-adk
# Development version (latest features)
pip install git+https://github.com/google/adk-python.git@main
from google.adk.agents import LlmAgent
from google.adk.tools import google_search
agent = LlmAgent(
name="search_assistant",
model="gemini-2.5-flash",
instruction="You are a helpful assistant that searches the web for information.",
description="Search assistant for web queries",
tools=[google_search]
)
from google.adk.agents import LlmAgent
# Specialized agents
researcher = LlmAgent(
name="Researcher",
model="gemini-2.5-flash",
instruction="Research topics thoroughly using web search.",
tools=[google_search]
)
writer = LlmAgent(
name="Writer",
model="gemini-2.5-flash",
instruction="Write clear, engaging content based on research.",
)
# Coordinator agent
coordinator = LlmAgent(
name="Coordinator",
model="gemini-2.5-flash",
instruction="Delegate tasks to researcher and writer agents.",
sub_agents=[researcher, writer]
)
from google.adk.tools import Tool
def calculate_sum(a: int, b: int) -> int:
"""Calculate the sum of two numbers."""
return a + b
# Convert function to tool
sum_tool = Tool.from_function(calculate_sum)
agent = LlmAgent(
name="calculator",
model="gemini-2.5-flash",
tools=[sum_tool]
)
from google.adk.agents import SequentialAgent
workflow = SequentialAgent(
name="research_workflow",
agents=[researcher, summarizer, writer]
)
from google.adk.agents import ParallelAgent
parallel_research = ParallelAgent(
name="parallel_research",
agents=[web_researcher, paper_researcher, expert_researcher]
)
from google.adk.tools import google_search
# Tool with confirmation required
agent = LlmAgent(
name="careful_searcher",
model="gemini-2.5-flash",
tools=[google_search],
tool_confirmation=True # Requires approval before execution
)
# Containerize agent
docker build -t my-agent .
# Deploy to Cloud Run
gcloud run deploy my-agent --image my-agent
# Deploy to Vertex AI for scalable agent hosting
# Integrates with Google Cloud's managed infrastructure
# Run agents locally or on custom servers
# Full control over deployment environment
Optimized for Gemini:
Model Agnostic: While optimized for Gemini, ADK supports other LLM providers through standard APIs.
ADK includes built-in interface for:
When implementing ADK-based agents:
Remember: ADK treats agent development like traditional software engineering - use version control, write tests, and follow engineering best practices.
This skill should be used when the user asks to "create a slash command", "add a command", "write a custom command", "define command arguments", "use command frontmatter", "organize commands", "create command with file references", "interactive command", "use AskUserQuestion in command", or needs guidance on slash command structure, YAML frontmatter fields, dynamic arguments, bash execution in commands, user interaction patterns, or command development best practices for Claude Code.
This skill should be used when the user asks to "create an agent", "add an agent", "write a subagent", "agent frontmatter", "when to use description", "agent examples", "agent tools", "agent colors", "autonomous agent", or needs guidance on agent structure, system prompts, triggering conditions, or agent development best practices for Claude Code plugins.
This skill should be used when the user asks to "create a hook", "add a PreToolUse/PostToolUse/Stop hook", "validate tool use", "implement prompt-based hooks", "use ${CLAUDE_PLUGIN_ROOT}", "set up event-driven automation", "block dangerous commands", or mentions hook events (PreToolUse, PostToolUse, Stop, SubagentStop, SessionStart, SessionEnd, UserPromptSubmit, PreCompact, Notification). Provides comprehensive guidance for creating and implementing Claude Code plugin hooks with focus on advanced prompt-based hooks API.