google-adk-python
Build AI agents with Google's Agent Development Kit (ADK) Python - an open-source toolkit for building, evaluating, and deploying AI agents.
Skill by vibery-studio
Install
Works with Claude Code, Claude apps, Codex, Cursor, Gemini CLI, GitHub Copilot, VS Code, OpenCode, Goose, Windsurf. Read the repository before you give any tool access to your data.
npx agentmarket install skill/vibery-studio-google-adk-python
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About
Use cases: productivity, agent-building
Reviews
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Permissions
What this skill can do and what it asks for, from its SKILL.md. Checked Oct 25, 2026.
- Tools
- No tools found
- Secrets
- None asked for
- Install scripts
- None found
Network hosts it talks to 1
codeload.github.com· found in install command
Files it touches
~/.claude/skills/google-adk-python
What's inside
- Skill name
google-adk-python- Description
- Build AI agents with Google's Agent Development Kit (ADK) Python - an open-source toolkit for building, evaluating, and deploying AI agents. Features LlmAgent, workflow agents (sequential, parallel, loop), tool integration, multi-agent systems, and deployment to Vertex AI or Cloud Run.
- License
- MIT
- Instructions
- 124 lines in SKILL.md · view on GitHub
Files (1)
- SKILL.md
SKILL.md (first lines)
# Google ADK Python
Open-source, code-first toolkit for building, evaluating, and deploying AI agents.
## When to Use
- Build AI agents with tool integration
- Create multi-agent systems with hierarchical coordination
- Implement workflow agents (sequential, parallel, loop)
- Integrate with Google Search, Code Execution, or custom tools
- Deploy to Vertex AI Agent Engine or Cloud Run
- Implement human-in-the-loop approval flows
## Installation
```bash
pip install google-adk
```
## Agent Types
### LlmAgent
LLM-powered agents with dynamic routing and adaptive behavior.
```python
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.",
tools=[google_search]
)
```
### SequentialAgent
Execute agents in defined order.
```python
from google.adk.agents import SequentialAgent
workflow = SequentialAgent(
name="research_workflow",
agents=[researcher, summarizer, writer]
)
```
### ParallelAgent
Run multiple agents concurrently.
```python
from google.adk.agents import ParallelAgent
parallel = ParallelAgent(
name="parallel_research",
agents=[web_researcher, paper_researcher]
)
```
## Multi-Agent System
```python
# Specialized agents
researcher = LlmAgent(
name="Researcher",
model="gemini-2.5-flash",
tools=[google_search]
)
writer = LlmAgent(
name="Writer",
model="gemini-2.5-flash",
)
# Coordinator
coordinator = LlmAgent(
name="Coordinator",
model="gemini-2.5-flash",
instruction="Delegate tasks to researcher and writer.",
sub_agents=[researcher, writer]
)
```
## Custom Tools
```python
from google.adk.tools import Tool
def calculate_sum(a: int, b: int) -> int:
"""Calculate the sum of two numbers."""
return a + b
sum_tool = Tool.from_function(calculate_sum)
```
## Model Support
- gemini-2.5-flash (recommended)
- gemini-2.5-pro
- gemini-1.5-flash
- gemini-1.5-pro
## Best Practices
1. Code-first for version control and testing
2. Create specialized agents for specific domains
3. Use workflow agents for predictable pipelines
4. Implement confirmation flows for sensitive operations
5. Test agents systematically
## Resources
- GitHub: https://github.com/google/adk-python
- Docs: https://google.github.io/adk-docs/From vibery-studio/templates, MIT.
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Signals
- Stars
- 3
- Forks
- 1
- Open issues
- 0
- Last commit (this folder)
- Dec 31, 2025 (10 months ago)
- Last release
- Mar 3, 2026 (7 months ago)
From GitHub (fetched Oct 24, 2026).
Details
- License
- MIT
- Repository
- github.com/vibery-studio/templates
- First seen
- Oct 24, 2026
- Last checked
- Oct 24, 2026
- Source
- GitHubgithub-graphql
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Cite this page
google-adk-python skill. Agent Mart. https://agentmart.dev/skills/vibery-studio-google-adk-python (last updated 2026-10-24)