---

name: adk-agent-builder description: Guide for adding new agents to the ADK pipeline. Use when creating a new LlmAgent, SequentialAgent, or ParallelAgent, or when extending the pipeline with additional processing stages.

ADK Agent Builder

Quick Start

Create a new agent in 5 steps:

1. Create app/sub_agents/my_agent/agent.py
2. Define LlmAgent with instruction, tools, output_key
3. Add callbacks in app/callbacks/pipeline_callbacks.py
4. Export in app/sub_agents/__init__.py
5. Add to pipeline in app/agent.py

Agent Types

Minimal Template

Copyfrom google.adk.agents import LlmAgent
from ...config import FAST_MODEL
from ...callbacks import before_my_agent, after_my_agent

INSTRUCTION = """You are a specialized agent.

TARGET LOCATION: {target_location}
BUSINESS TYPE: {business_type}

Your task is to analyze the data and provide insights.
"""

my_agent = LlmAgent(
    name="MyAgent",
    model=FAST_MODEL,
    description="What this agent does (for orchestrator)",
    instruction=INSTRUCTION,
    tools=[],
    output_key="my_agent_output",
    before_agent_callback=before_my_agent,
    after_agent_callback=after_my_agent,
)

Key Patterns

• State injection: Use {variable} in instructions to inject state values
• Output storage: Set output_key to store agent output in session state
• Callbacks: Add before_agent_callback and after_agent_callback for logging
• Retry config: Use generate_content_config for API retry settings

Common Mistakes

• Forgetting to export in __init__.py files
• Using output_schema with tools (disables tool calling)
• Not adding agent to pipeline's sub_agents list
• Mismatched state key names between agents

[See references/agent-patterns.md for complete templates and examples]