AgentSkillsCN

google-adk-python

为Python用户提供Google Agent Development Kit(ADK)的专业指导。当用户询问如何构建代理、使用工具、进行流式传输、处理回调、学习教程、部署应用,或在Python中运用Google ADK进行高级架构设计时,可使用此技能。

SKILL.md
--- frontmatter
name: google-adk-python
description: Expert guidance on the Google Agent Development Kit (ADK) for Python. Use this skill when the user asks about building agents, using tools, streaming, callbacks, tutorials, deployment, or advanced architecture with the Google ADK in Python.

Google ADK (Python) Skill

This skill provides comprehensive documentation and Python examples for the Google Agent Development Kit (ADK). It maps documentation topics to their corresponding Python code snippets.

How to Use

Identify the user's specific interest or task and refer to the relevant reference file below. Each reference file contains links to the official documentation (Markdown) and the corresponding Python examples (raw code).

Topics

1. Getting Started

For installation, quickstarts, and basic agent setup.

2. Agents & Models

For creating different types of agents (LLM, Workflow, Loop, Parallel, Sequential) and configuring specific models (Gemini, Anthropic, etc.).

3. Tools (Basic & Advanced)

For integrating tools like Google Search, Code Execution, BigQuery, third-party services (GitHub, Jira, etc.), MCP, and Grounding.

4. Streaming

For building real-time, low-latency streaming agents (audio/video).

5. Callbacks

For hooking into agent lifecycle events (before/after agent, model, tool execution).

6. Runtime & Architecture

For deep dives into the Runtime, Sessions, Memory, Context, Events, Artifacts, and Plugins.

7. Deployment & Operations

For deploying agents (Cloud Run, GKE) and observability (Logging, Tracing, Evaluation).

8. Tutorials & Samples

For end-to-end tutorials and complete agent samples (e.g., YouTube Shorts Assistant, Weather Agent).

9. API Reference

For REST API details.

10. General Information

For project info, community, release notes, and limitations.

Instructions

  • When a user asks about a specific topic, load the corresponding reference file to get the URLs for the documentation and code.
  • You can read the content of the linked files using web_fetch or run_shell_command with curl if you need to provide the actual content to the user.
  • Always prefer providing the Python example code when explaining a concept.