Agent skill · software engineering · samhvw8
google-adk-python
Google Agent Development Kit (ADK) for Python. Capabilities: AI agent building, multi-agent systems, workflow agents (sequential/parallel/loop), tool integration (Google Search, Code Execution), Vertex AI deployment, agent evaluation, human-in-the-loop flows. Actions: build, create, deploy, evaluate, orchestrate AI agents. Keywords: Google ADK, Agent Development Kit, AI agent, multi-agent system, LlmAgent, SequentialAgent, ParallelAgent, LoopAgent, tool integration, Google Search, Code Execution, Vertex AI, Cloud Run, agent evaluation, human-in-the-loop, agent orchestration, workflow agent, hierarchical coordination. Use when: building AI agents, creating multi-agent systems, implementing workflow pipelines, integrating LLM agents with tools, deploying to Vertex AI, evaluating agent performance, implementing approval flows.
Why this skill is useful
Provides executable scripts and patterns for building and deploying AI agents with specific integrations and workflows that are not commonly known.
What it needs
Requires google-adk installed locally. About 4k tokens when loaded. Last updated 2025-12-09. 10 stars on the source repository.
What this skill does
Google ADK Python Skill You are an expert guide for Google's Agent Development Kit (ADK) Python - an open-source, code-first toolkit for building, evaluating, and deploying AI agents. When to Use This Skill Use this skill when users need to: Build AI agents with tool integration and orchestration capabilities Create multi-agent systems with hierarchical coordination Implement workflow agents (sequential, parallel, loop) for predictable pipelines Integrate LLM-powered agents with Google Search, Code Execution, or custom tools Deploy agents to Vertex AI Agent Engine, Cloud Run, or custom infrastructure Evaluate and test agent performance systematically Implement human-in-the-loop approval flows for tool execution Core Concepts Agent Types LlmAgent: LLM-powered agents capable of dynamic routing and adaptive behavior Define with name, model, instruction, description, and tools Supports sub-agents for delegation and coordination Intelligent decision-making based on context Workflow Agents: Structured, predictable orchestration patterns SequentialAgent: Execute agents in defined order ParallelAgent: Run multiple agents concurrently LoopAgent: Repeat execution with iteration logic BaseAgent: Foundation for custom agent implementations Key Components Tools Ecosystem: Pre-built tools (googlesearch, codeexecution) Custom Python functions as tools OpenAPI specification integration Tool confirmation flows for human approval Multi-Agent Architecture: Hierarchical agent composition Specialized agents for specific domains Coordinator agents for delegation Installation Implementation Patterns Single Agent with Tools Multi-Agent System Custom Tool Creation Sequential Workflow Parallel Workflow Human-in-the-Loop Deployment Options Cloud Run Deployment Vertex AI Agent Engine Custom Infrastructure Model Support Optimized for Gemini: gemini-2.5-flash gemini-2.5-pro gemini-1.5-flash gemini-1.5-pro Model Agnostic: While optimized for Gemini, ADK supports other LLM providers through standa …
How to use it
Reference it in AdaL, Claude Code, Cursor or any coding agent — nothing to install:
@skills samhvw8/google-adk-python