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README.md

Outline
layout default
title Goose Tutorial
nav_order 121
has_children true
format_version v2

Goose Tutorial: Extensible Open-Source AI Agent for Real Engineering Work

Learn how to use block/goose to automate coding workflows with controlled tool execution, strong provider flexibility, and production-ready operations.

GitHub Repo License Docs

Why This Track Matters

Goose is one of the highest-velocity open-source coding agents and combines desktop + CLI interfaces with deep MCP extension support.

This track focuses on:

  • setting up Goose quickly across desktop and terminal workflows
  • understanding the agent loop, tool execution, and context management model
  • controlling permissions, risk boundaries, and extension behavior
  • operating Goose safely for teams and production usage

Current Snapshot (auto-updated)

  • repository: block/goose
  • stars: about 51.3k
  • GitHub release reference: v1.43.0 (checked 2026-07-20; release metadata on GitHub)

Mental Model

flowchart LR
    A[Developer Request] --> B[Goose Interface UI or CLI]
    B --> C[Agent Loop]
    C --> D[Tool or Extension Calls]
    D --> E[Context Revision and Summarization]
    E --> F[Actionable Output or Code Changes]
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Chapter Guide

Chapter Key Question Outcome
01 - Getting Started How do I install and launch Goose quickly? Working baseline setup
02 - Architecture and Agent Loop How does Goose process requests and tool calls? Strong runtime mental model
03 - Providers and Model Routing How do I choose and configure providers safely? Reliable model configuration strategy
04 - Permissions and Tool Governance How do I control automation risk in daily usage? Safer execution boundaries
05 - Sessions and Context Management How does Goose sustain long-running sessions? Durable conversation and token management
06 - Extensions and MCP Integration How do I add capabilities with built-in and custom MCP servers? Extensible workflow design
07 - CLI Workflows and Automation How do I automate Goose in scripts and CI-like flows? Repeatable command-driven workflows
08 - Production Operations and Security How do teams run Goose in production responsibly? Governance and operations runbook

What You Will Learn

  • how to use Goose across desktop and CLI surfaces
  • how the Goose agent loop uses tools, extensions, and context revision
  • how to balance autonomy and safety with permission modes and tool controls
  • how to operationalize Goose for reproducible, team-scale engineering workflows

Source References

Related Tutorials


Start with Chapter 1: Getting Started.

Navigation & Backlinks

Full Chapter Map

  1. Chapter 1: Getting Started
  2. Chapter 2: Architecture and Agent Loop
  3. Chapter 3: Providers and Model Routing
  4. Chapter 4: Permissions and Tool Governance
  5. Chapter 5: Sessions and Context Management
  6. Chapter 6: Extensions and MCP Integration
  7. Chapter 7: CLI Workflows and Automation
  8. Chapter 8: Production Operations and Security

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