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gemini-antigravity-cli

Run terminal-based AI chat with Gemini and Antigravity models.

4|Updated May 16, 2026
Search Tags:#code generation#slash commands#gemini#mcp server#antigravity#terminal ai#context-aware coding
One-click install
npx skills add https://github.com/Aradotso/devtools-skills --skill gemini-antigravity-cli
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: gemini-antigravity-cli
Source: https://github.com/Aradotso/devtools-skills/tree/main/skills/gemini-antigravity-cli
Command: npx skills add https://github.com/Aradotso/devtools-skills --skill gemini-antigravity-cli

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Developers need a fast, context-aware way to interact with Gemini/Antigravity models and generate coding help directly in their terminal, without constantly switching tools.

Core Features & Use Cases

  • Terminal AI chat with slash commands: Use built-in commands to manage help, model selection, context, saving/loading conversations, and configuration.
  • Context-aware coding with file/directory context: Attach relevant source files or project folders so the model can reason over real code and produce actionable changes.
  • MCP server integration: Connect MCP servers (e.g., filesystem, GitHub) to fetch or operate on workspace data as part of your prompts.

Quick Start

Set your GOOGLE_API_KEY environment variable, then run the CLI and ask it to review or improve your code using a specific prompt and optional /context.

Frequently Asked Questions about gemini-antigravity-cli

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I use terminal AI to chat with Gemini and review code?▼

Terminal AI chat with Gemini lets you interact with models directly from your command line to speed up coding and troubleshooting. You can use slash commands to manage model selection, save conversations, and attach file context for codebase reasoning.

What do I need to configure before using terminal AI for context-aware coding?▼

Context-aware coding requires a configured Google API key set as an environment variable. You must also integrate MCP server configuration to enable the tool requests and context-driven responses needed for your project directories.

Can I connect an MCP server to manage workspace data in my terminal?▼

Yes, you can connect MCP servers like filesystem or GitHub to manage workspace data. This integration allows the terminal AI to fetch and operate on codebases or diffs directly as part of your prompts.

How do slash commands work for managing AI conversation context?▼

Slash commands provide built-in operations to manage help, switch models, save conversations, and load configuration. They enable command-driven workflows so you can quickly adjust context and model parameters without leaving the terminal.

Does terminal AI support generating code changes based on attached source files?▼

Yes, terminal AI supports context-aware coding by allowing you to attach relevant source files or project folders. The model reasons over your real code to produce actionable changes and troubleshooting suggestions.

What are the limitations of using command-driven workflows for terminal coding assistance?▼

Command-driven terminal workflows require a configured Google API key and MCP server setup to function properly. Without integrating these configurations, the tool cannot enable context-aware responses or operate on workspace data.

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