---

name: adk-python description: "Use Google ADK Python to build agents, Workflow graphs, tools, runtime services, CLI apps, evaluations, deployments, and ADK repository changes." disable-model-invocation: true metadata: disco-role: operating license: Apache 2.0

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:

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:

from google.adk import Workflow

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

Run local checks:

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