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Adk Python

Organization
VectorSpaceLab
adk-python

Use Google ADK Python to build agents, Workflow graphs, tools, runtime services, CLI apps, evaluations, deployments, and ADK repository changes.

Overview

PublisherVectorSpaceLab
RepositoryAREX-Skill
Skill nameadk-python
Stars
341
Forks
26
Bundled files
33
LicenseApache-2.0
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • 33 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by VectorSpaceLab on GitHub. Read the source before you install it.

Installation

Install the Adk Python AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/VectorSpaceLab/AREX-Skill/tree/main/skills/repositories/repo-skills/adk-python
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/VectorSpaceLab/AREX-Skill.git /tmp/AREX-Skill
mkdir -p .claude/skills
cp -r /tmp/AREX-Skill/skills/repositories/repo-skills/adk-python .claude/skills/adk-python
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Adk Python in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Adk Python on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Adk Python is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

ADK Python

Use this repo skill when a task involves Google Agent Development Kit for Python (google-adk / google.adk), ADK 2.0 Agent and Workflow APIs, ADK CLI commands, tool integrations, runtime services, evaluation/debugging, or modifying the ADK Python repository itself.

Start Here

  • Install the package with pip install google-adk on Python 3.10+.
  • For optional integrations, install the narrow extra for the task instead of all by default, such as google-adk[db], google-adk[mcp], google-adk[eval], google-adk[gcp], or google-adk[extensions].
  • Verify the base install with python -c "import google.adk; print(google.adk.__version__)" and adk --help.
  • Run check_adk_install.py for a safe diagnostic covering imports, CLI command availability, package version, and optional-extra signals.
  • Read Repository Provenance before deciding whether this skill is current for a checkout; refresh if commit, dirty state, package version, or major evidence paths changed.

Route by Task

  • Build Python agents: Use agent-construction for Agent/LlmAgent, instructions, model settings, callbacks, schemas, task/single-turn modes, sub-agents, and multi-agent delegation.
  • Build Workflow graphs: Use workflow-orchestration for Workflow, BaseNode, function nodes, graph edges, JoinNode, dynamic nodes, parallel worker, HITL, retry, checkpoint/resume, and event flow.
  • Add tools or integrations: Use tools-and-integrations for FunctionTool, ToolContext, toolsets, confirmation/long-running tools, auth, MCP, OpenAPI, Google API/cloud integrations, A2A, and optional extras.
  • Configure runtime services: Use runtime-services for Runner, App, sessions, memory, artifacts, plugins, telemetry, code executors, environments, event persistence, and service lifecycles.
  • Use CLI/config/deployment: Use cli-configuration-deployment for adk run, adk web, adk api_server, adk test, adk eval, adk deploy, app discovery, YAML config, service URIs, and safe CLI/schema inspection.
  • Evaluate or debug behavior: Use evaluation-debugging for eval sets, JSON test fixtures, adk test, adk eval, event summaries, traces, session inspection, flaky evals, and assertion design.
  • Modify this repository: Use repo-development for ADK Python source edits, style, tests, docs, samples, generated schema, review gates, and repository-specific validation.

Shared References

  • Capability Map maps common user request families to sub-skills, bundled scripts, and validation expectations.
  • Troubleshooting covers cross-cutting install/import, optional dependency, CLI, credential, server, and repository-staleness failures.
  • Repository Routing Metadata is structured metadata used by DisCo's managed repo-skills-router during import.

Safe Defaults

  • Prefer import/signature checks, --help, and dry-run diagnostics before starting servers, deployments, cloud calls, model-backed evals, or database migrations.
  • Do not assume optional extras are installed in base google-adk; diagnose missing modules and install only what the selected workflow requires.
  • Do not put API keys, OAuth secrets, service-account JSON, production database URLs, or cloud project credentials into examples or YAML files.
  • For repository-maintenance tasks, run focused tests first and avoid remote/cloud/credentialed tests unless the user explicitly asks and the environment is configured.

Minimal Examples

Create a simple agent:

python
from google.adk import Agent

root_agent = Agent(
    name="greeter",
    model="gemini-2.5-flash",
    instruction="Greet the user and answer briefly.",
)

Create a simple workflow:

python
from google.adk import Workflow

root_agent = Workflow(
    name="fruit_flow",
    edges=[("START", pick_fruit, explain_benefit)],
)

Run local checks:

bash
python scripts/check_adk_install.py --json
adk --help
adk run path/to/my_agent --help

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Adk Python AI skill do?

Use Google ADK Python to build agents, Workflow graphs, tools, runtime services, CLI apps, evaluations, deployments, and ADK repository changes.

Why use Adk Python on TypingMind?

Because you install it once and use it with any model. Adk Python is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Adk Python in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/VectorSpaceLab/AREX-Skill/tree/main/skills/repositories/repo-skills/adk-python. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Adk Python?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Adk Python?

As many as you like. As long as a model supports skills, you can use Adk Python with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Adk Python AI skill free?

Yes. It is published on GitHub by VectorSpaceLab under the Apache-2.0 license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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