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Adk Sample Creator Agent Skill

Author new samples for the ADK Python repository. Use this skill when the user wants to create a new sample demonstrating a feature or agent pattern (e.g., dynamic nodes, standalone agents, fan-out/fan-in) or when adding examples to subdirectories under `contributing/`.

1k tokens
context cost
the whole folder, loaded on every use
1
files
instructions only
0
copies elsewhere
how many repositories repackaged it
20998
stars on the repo
on the repository, not the skill itself

Install

one command, takes just this skill from the repository
npx skills add https://github.com/google/adk-python --skill adk-sample-creator

The instruction itself

11 sections, as written by the author

ADK Sample Creator

This skill helps you create new samples for the ADK Python repository. You should search for subdirectories under contributing (such as new_workflow_samples, workflow_samples, etc.) and confirm with the user which folder they want to use before creating the sample.

> [!TIP]

> Before creating samples, you can use the adk-style skill to learn about ADK 2.0 architecture knowledge and best practices.

A sample consists of:

  • A directory per sample.
  • An agent.py file defining the agent or workflow logic.
  • A README.md file explaining the sample.

Guidelines

1. Folder Name

Use snake_case for the folder name (e.g., dynamic_nodes, fan_out_fan_in).

2. agent.py Content

The agent.py should focus on demonstrating a specific feature or agent pattern. Use absolute imports for testing convenience.

> [!IMPORTANT]

> Model Selection: Do not set the model parameter explicitly (e.g., model="gemini-2.5-flash") on Agent instances in sample agents. Instead, let them default to the system-configured model, unless a specific model is explicitly requested by the user.

Choose one of the following patterns:

Pattern A: Workflows (for complex graphs)

Use this when you need multiple nodes, routing, or parallel execution.

Imports:

from google.adk import Agent
from google.adk import Context
from google.adk.workflow import node
from google.adk.workflow import JoinNode
from google.adk.workflow._workflow_class import Workflow

Anatomy:

my_agent = Agent(name="my_agent", ...)

@node()
async def my_node(node_input: str):
    return "result"

root_agent = Workflow(
    name="root_wf",
    edges=[("START", my_node)],
)
Pattern B: Standalone Agents (for single-agent or simple tool use)

Use this when you don't need a graph and the agent handles the loop.

Imports:

from google.adk import Agent
from google.adk.tools import google_search  # example

Anatomy:

root_agent = Agent(
    name="standalone_assistant",
    instruction="You are a helpful assistant.",
    description="An assistant that can help with queries.",
    tools=[google_search],
)

3. README.md Content

Each sample should have a README.md with the following structure:

  • Overview: What the sample does.
  • Sample Inputs: Examples of inputs to test with. Each prompt must be wrapped in backticks. If a prompt has an explanation, always add a blank line between the prompt and the explanation, and indent the explanation by two spaces.
  • Graph: Visualization of the graph flow (Mermaid recommended). For Workflow root agents, visualize the graph flow of nodes. For agents that orchestrate tools or sub-agents (e.g., LlmAgent, ManagedAgent), visualize the topology of the agent and its tools/sub-agents instead of internal workflow nodes. Keep it a simple topology diagram (a few nodes and edges). Do not draw a request/response data-flow sequence (e.g., user -> agent -> API -> tool -> ... -> user); those are noisy and add little value over the topology.
  • How To: Explanation of key techniques used (e.g., ctx.run_node).
  • Related Guides: Links to relevant developer guides in docs/guides/ that explain the concepts or classes used.
README Example Template:
# ADK Sample Name

## Overview

Brief description.

## Sample Inputs

- `Prompt example 1`

- `Prompt example 2`

  *Explanation or expected behavior*

## Graph

For Workflow root agents:

graph TD

START --> MyNode


For agents that orchestrate tools or sub-agents (`LlmAgent`, `ManagedAgent`, ...):

graph TD

MyAgent[my_agent] -->|calls| MyTool(my_tool)


## How To

Explain the details.

## Related Guides

- [Guide Title](../../docs/guides/path/to/guide.md) - Brief description of what the guide covers.

Examples

Dynamic Nodes

Snippet from dynamic_nodes/agent.py:

@node(rerun_on_resume=True)
async def orchestrate(ctx: Context, node_input: str) -> str:
    while True:
        headline = await ctx.run_node(generate_headline)
        # ...

Fan Out Fan In

Snippet from fan_out_fan_in/agent.py:

root_agent = Workflow(
    name="root_agent",
    edges=[("START", (node_a, node_b), join_node, aggregate)],
)

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How to use it

Copy the folder

Take google/adk-sample-creator from the repository into ~/.claude/skills for personal use, or into .claude/skills inside a project.

Check the name does not clash

The agent identifies a skill by the name field in its header. Two skills with the same name cannot sit side by side — one of them will be ignored.