Goose
Goose is an open-source autonomous AI coding agent that runs on your machine, reads your code, edits files, runs commands, and iterates with you on software tasks. It operates locally with direct filesystem access, supporting both interactive and headless modes while you maintain control over every action.
itArtificial intelligence and machine learning | OpenSkills.info
Intro
Goose
Goose is an open-source autonomous AI coding agent originally developed by Block and now maintained by the Agentic AI Foundation. It runs on your machine as a CLI or desktop application, reads your code, edits files, runs shell commands, and orchestrates multi-step development workflows while you observe and approve each action.
The mental model
Goose functions as an autonomous developer agent that can read, write, and execute on your local system. Unlike code completion tools that suggest snippets, Goose operates on your actual project files and can run tests, build tools, and shell commands.
your prompt
-> Goose reads relevant files
-> proposes changes and commands
-> you approve or reject
-> Goose applies changes
-> iterate until done
The agent maintains context across a session. It remembers earlier decisions, file contents it has examined, and the current state of your request. This enables multi-step work where each turn builds on previous actions.
Installation and setup
Goose is available as a CLI and a desktop application. The CLI provides the fastest way to get started with the full feature set.
# Homebrew (macOS, Linux)
brew install block-goose-cli
# Cargo (build from source)
cargo install goose-cli
# Desktop application
# Download from the releases page for macOS, Linux, or Windows
After installation, run goose with no arguments to start an interactive session. The first launch prompts you to configure a model provider.
Interactive and headless modes
Continue the course
This section is part of the paid course.
See pricing to subscribe, or log in if you already have access.
Where this skill leads
Relevant careers
See how this topic contributes to broader role-level skill maps.
Sources
- https://github.com/aaif-goose/goose
Supports
- Installation methods (Homebrew, Cargo, desktop app)
- CLI commands and options
- Configuration file structure
- .goosehints discovery rules
- Extension system architecture
- Running modes (interactive, headless)
- Security considerations
- https://block-goose.mintlify.app/installation
Supports
- CLI installation guide
- Desktop application setup
- Platform-specific instructions
- Initial configuration
- https://block-goose.mintlify.app/concepts/extensions
Supports
- Extension types (built-in, stdio, remote)
- MCP integration
- Tool configuration
- Extension development
- https://block-goose.mintlify.app/guides/mcp-integration
Supports
- MCP server configuration
- Authentication methods
- Tool registration
- Best practices
- https://block-goose.mintlify.app/api/extensions/builtin
Supports
- Built-in extension capabilities
- File operations
- Shell execution
- Code editing
- https://modelcontextprotocol.io/
Supports
- MCP architecture and concepts
- Server configuration
- Protocol integration
- Tool and resource definitions
- https://github.com/shakahl/aaif-goose/blob/main/documentation/docs/guides/context-engineering/using-goosehints.md
Supports
- .goosehints file format
- Context engineering patterns
- Project instruction examples
- Discovery mechanism
- https://formulae.brew.sh/formula/block-goose-cli
Supports
- Installation command
- Version history
- Dependencies
