메뉴
Scaffold a new Google ADK (Agent Development Kit) Python project. Use when creating a new ADK agent project from scratch — sets up directory structure, __init__.py, agent.py, pyproject.toml, and .env template.
Codex 또는 Claude로 설치 이 Prompt를 복사해 Codex, Claude 또는 다른 어시스턴트에 붙여 넣으면 Skill 페이지를 검토하고 설치를 진행할 수 있습니다.
SOC 직업 분류 기준
ADK Agent-to-Agent (A2A) protocol integration. Use when building remote agent communication — exposing ADK agents as A2A servers or connecting to external A2A agents as clients.
ADK App pattern with plugins, event compaction, and resumability. Use when you need plugins (context filtering, debug logging), event summarization, or resumable long-running operations.
ADK artifact services for file storage. Use when agents need to save/load files, images, or binary data — InMemory, File, and GCS artifact backends.
ADK authentication and credentials. Use when adding auth to tools — API keys, bearer tokens, OAuth2 flows, OpenID Connect, service accounts, and credential storage services.
Catalog of all ADK built-in tools. Use when looking for pre-built tools to add to agents — search, memory, artifacts, transfer, grounding, and user interaction tools.
Implement ADK agent and tool callbacks. Use when adding lifecycle hooks — before/after agent execution, before/after tool calls, for logging, validation, conditional execution, or response modification.
| name | google-adk-scaffold |
| description | Scaffold a new Google ADK (Agent Development Kit) Python project. Use when creating a new ADK agent project from scratch — sets up directory structure, __init__.py, agent.py, pyproject.toml, and .env template. |
uv package manager (install: curl -LsSf https://astral.sh/uv/install.sh | sh)GOOGLE_API_KEY) or Vertex AI credentialsADK CLI (adk web, adk run) auto-discovers agents via this structure:
my_project/
├── my_agent/
│ ├── __init__.py # MUST contain: from . import agent
│ ├── agent.py # MUST define: root_agent = Agent(...)
│ └── tools.py # Optional: custom tool functions
├── .env # GOOGLE_API_KEY or GOOGLE_CLOUD_PROJECT
└── pyproject.toml
from . import agent
from google.adk.agents import Agent
root_agent = Agent(
name="my_agent",
model="gemini-2.5-flash",
description="Brief description of what this agent does.",
instruction="You are a helpful assistant that...",
tools=[],
)
from google.adk.agents import Agent
from google.adk.apps import App
root_agent = Agent(
name="my_agent",
model="gemini-2.5-flash",
instruction="You are a helpful assistant.",
tools=[],
)
app = App(
name="my_app",
root_agent=root_agent,
plugins=[],
)
[project]
name = "my-adk-agent"
version = "0.1.0"
description = "ADK agent project"
requires-python = ">=3.10"
dependencies = [
"google-adk>=1.0.0",
]
[project.optional-dependencies]
dev = [
"pytest>=7.0",
]
GOOGLE_API_KEY=your-api-key-here
# Or for Vertex AI:
# GOOGLE_CLOUD_PROJECT=your-project-id
# GOOGLE_CLOUD_LOCATION=us-central1
# Create venv
uv venv --python "python3.11" ".venv"
source .venv/bin/activate
# Install dependencies
uv sync
# Run agent (interactive CLI)
adk run my_agent/
# Launch web UI
adk web my_agent/
# Start API server
adk api_server my_agent/
| Model | Use Case |
|---|---|
gemini-2.5-flash | Fast, cost-effective (default) |
gemini-2.5-pro | Complex reasoning |
gemini-2.0-flash | Legacy, still supported |
my_project/
├── coordinator/
│ ├── __init__.py
│ ├── agent.py # root_agent with sub_agents=[]
│ ├── researcher.py # Sub-agent definitions
│ └── writer.py # Sub-agent definitions
├── .env
└── pyproject.toml
google-adk-llm-agent — Agent configuration and parametersgoogle-adk-function-tool — Creating custom toolsgoogle-adk-app — App pattern with pluginsgoogle-adk-deploy — Deploying to production