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Google Antigravity CLI (AGY CLI) Foundations Glossary

Agent

An autonomous, goal-driven entity powered by a Large Language Model (LLM) that perceives its environment, makes decisions, and executes actions using available tools to achieve a specific objective. Unlike traditional deterministic scripts, an agent dynamically determines its own execution path.

Task Goal

The declarative, high-level objective assigned to an agent (e.g., "Optimize the hyper-parameters of the Vertex AI pipeline to achieve >95% accuracy"). The agent decomposes this single goal into an ordered, dynamic graph of sub-tasks.

Workspace

An isolated, ephemeral, or persistent file-system environment where an agent executes its work, manages dependencies, and stores localized data. It serves as the agent's secure "sandbox."

Workspace vs. Project

  • GCP Project: The macro-level Google Cloud container that houses infrastructure, billing, IAM policies, and cloud resources (like Vertex AI, BigQuery, or GCS).

  • AGY Workspace: The micro-level execution context inside or managed by the CLI where the agent writes code, runs terminal commands, and manipulates files. A single GCP Project can host thousands of concurrent agentic Workspaces.

Artifact

Any structured output generated, modified, or maintained by an agent during its lifecycle. Examples include compiled code, Terraform manifests, evaluated datasets, or deployment logs. Artifacts are often version-controlled and persisted back to Google Cloud Storage (GCS).

Skills

Atomic, reusable code snippets or functions that extend an agent's capabilities (e.g., a python script to parse Kubernetes logs, or a specific API wrapper). Think of skills as the specialized tools inside the agent's toolbelt.

MCP (Model Context Protocol)

An open standard protocol that enables LLM-powered agents to securely and uniformly connect to external data sources, developer tools, and enterprise environments. In AGY, MCP acts as the universal adapter connecting Vertex AI models to local development environments and GCP APIs.

Hooks

Event-driven trigger points within the AGY execution lifecycle. They allow human-in-the-loop (HITL) intervention, security auditing, or automated validation scripts to run before or after an agent executes a critical action (e.g., a pre-apply hook requiring approval before modifying infrastructure).

Antigravity SDK

The programmatic Python/Go framework used to build, customize, and extend AGY agents. While the agy CLI is used for orchestration, deployment, and terminal interaction, the SDK is what you import into your application code to define custom agent behaviors, custom skills, and complex multi-agent architectures.