Build multi-agent systems with ADK Python workflow graphs and tools.
npx skills add https://github.com/Fandry96/k3-agentic-skills --skill adk-python
Please help me install this Agent Skill. Skill: adk-python Source: https://github.com/Fandry96/k3-agentic-skills/tree/main/skills/adk-python Command: npx skills add https://github.com/Fandry96/k3-agentic-skills --skill adk-python
Google Agent Development Kit (ADK) for Python provides validated API patterns for building production-grade multi-agent systems. It covers workflow graphs (ADK 2.0 Beta), LlmAgent, SequentialAgent, LoopAgent, CustomAgent (BaseAgent), MCP integration via McpToolset, FunctionTool, ToolContext state, session management, context compaction, callbacks (before/after agent/model/tool), human input via RequestInput, and the App wrapper. Use when: ADK agent, workflow graph, multi-agent, MCP toolset, HITL, context compaction, session state, agent pipeline.
Install the ADK Python package, then import core components like LlmAgent, SequentialAgent, and McpToolset to begin building multi-agent pipelines.
High-intent search queries and answers about installing and using this skill.
Build production-grade multi-agent systems in Python using validated API patterns covering workflow graphs, agent types, session state, context compaction, and human-in-the-loop orchestration for scalable AI task execution.
Add human-in-the-loop capabilities to AI agent workflows by implementing RequestInput patterns, enabling human intervention during execution to ensure auditable and governance-friendly orchestration across complex tasks.
Python multi-agent tooling supports MCP integration via McpToolset, allowing developers to connect agents to external toolsets and manage ToolContext state effectively within complex agent pipelines.
Orchestrate sequential and looping agent pipelines by composing specialized agent types like SequentialAgent and LoopAgent, structuring complex workflows and managing execution flow across diverse AI tasks.
You can use workflow graphs for multi-agent orchestration in Python through ADK 2.0 Beta, enabling structured pipeline design, context compaction, and App wrapper integration for production-grade deployments.
Developing multi-agent applications requires Python 3.10 or higher, installed via pip, to support advanced features like context compaction, McpToolset integration, and human-in-the-loop session state management.
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