Build and orchestrate Go AI agents with Google's Agent Development Kit.
npx skills add https://github.com/juburr/mad-skills --skill go-adk
Please help me install this Agent Skill. Skill: go-adk Source: https://github.com/juburr/mad-skills/tree/main/go-adk Command: npx skills add https://github.com/juburr/mad-skills --skill go-adk
ADK Go provides a code-first toolkit for building AI agents in Go, enabling seamless integration with Gemini or other GenAI backends and offering a rich set of orchestration patterns and tooling to compose multi-agent workflows.
Create a Gemini-backed model and instantiate an agent with llmagent.New using a basic Config, then run it with a runner.
High-intent search queries and answers about installing and using this skill.
To build AI agents in Go, use the ADK to instantiate a Gemini-backed model and configure an agent via llmagent.New, then execute it with a runner. This provides a code-first approach to defining agent names, models, and toolsets.
Multi-agent workflows in Go can be orchestrated using sequential, parallel, and loop agent patterns. These structured workflow components allow developers to compose complex multi-agent systems within the ADK runtime.
Yes, Go agent runtimes can connect local MCP servers and remote A2A agents. The ADK provides mcptoolset and agenttool integrations to facilitate communication between local and remote agents in your workflow.
Yes, agent development with Google's ADK requires Go version 1.24.4 or higher. This environment prerequisite ensures compatibility with the ADK interfaces needed to map agent names and toolsets to a runnable runtime.
For production AI agents in Go, manage memory and artifacts using the ADK's built-in memory and artifact tooling. This is complemented by dynamic instruction providers and plugin extensibility to create robust agent runtimes.
A code-first approach is ideal when you need seamless integration with GenAI backends like Gemini and require fine-grained control over tool definitions and orchestration patterns. It suits developers building structured, production-grade multi-agent workflows.
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