antigravity-setup

🥈Silver

Antigravity Setup provides a strong framework for AI coding agents, ensuring consistent, high-quality outputs. It benefits software engineers and operations teams by standardizing AI agent behavior, improving code reliability, and reducing debugging time. The setup integrates with Claude agents to enforce best practices in software design, architecture, and testing.

13680Updated 1mo ago

Intermediate30min to implementautomation

Saves ~120 min per use

Quick InstallView Source

git clone https://github.com/irahardianto/antigravity-setup.git

Works with:

Claude

Overview

About This Skill

Awesome AGV is a modular configuration toolkit designed to elevate AI coding agents with comprehensive standards and practices. It includes 42 rules covering security, reliability, architecture, and maintainability; 43 specialized skills for debugging and optimization; and 12 end-to-end workflows. The setup uses a two-tier rule system with always-on mandates and contextual principles to ensure generated code is secure, defensible, and maintainable. It's portable across multiple AI coding assistants including Claude Code, Roo Code, and Cline, installed via a single npm command into the `.agents/` directory.

How to Use

[{"step":1,"action":"Install the Antigravity framework in your project directory. Run `pip install antigravity-setup` or clone the official repository if using a custom setup.","tip":"Ensure your Python environment is isolated with venv or conda to avoid dependency conflicts."},{"step":2,"action":"Configure the agent by creating an `antigravity-config.json` file in your project root. Specify your language, architecture pattern, testing framework, and deployment target.","tip":"Use the provided template in the framework documentation as a starting point. Validate your config with `antigravity validate config.json`."},{"step":3,"action":"Generate the initial project structure by running `antigravity generate --feature [FEATURE_NAME]`. The agent will create the directory structure, boilerplate code, and test files.","tip":"Start with a small feature to test the setup before scaling to larger components."},{"step":4,"action":"Integrate with your CI/CD pipeline by adding the Antigravity GitHub Action or equivalent for your version control system. Configure the workflow to run tests and linting on every push.","tip":"Set up branch protection rules to require passing Antigravity checks before merging."},{"step":5,"action":"Deploy the generated code to your target environment. Use the framework's deployment scripts or integrate with your existing deployment tools.","tip":"Start with a staging environment to verify the deployment process before production."}]

Use Cases

Enforcing security and reliability standards across AI-generated code

Standardizing code architecture and design patterns for teams

Integrating rugged software principles into AI coding workflows

Reducing debugging time through consistent code quality standards

Setup & Installation

Quick Install

No install command available. Check the GitHub repository for manual installation instructions.

Alternative Install (Git Clone)

git clone https://github.com/irahardianto/antigravity-setup

Requirements

Claude Code or compatible AI agent
Works with: Claude

Quick Start Guide

Install the Skill

Copy the install command above and run it in your terminal.

Open Your AI Agent

Launch Claude Code, Cursor, or your preferred AI coding agent.

Try It Out

Use the prompt template or examples below to test the skill.

Customize

Adapt the skill to your specific use case and workflow.

Usage Examples

Prompt Template

Set up an AI coding agent using the Antigravity framework for [PROJECT_NAME]. Configure the agent to follow best practices in [PROGRAMMING_LANGUAGE] with a focus on [ARCHITECTURAL_PATTERN] and [TESTING_STRATEGY]. Ensure the agent generates modular, well-documented code with clear error handling. Include a [DEPLOYMENT_TARGET] deployment strategy and integrate [CI/CD_TOOL] for automated testing and linting. Provide a sample implementation for [SPECIFIC_FEATURE].

Example Output

### Antigravity Framework Setup for 'Inventory Management System'

**Agent Configuration:**
- **Language:** Python 3.11
- **Architecture:** Clean Architecture (Domain/Application/Infrastructure layers)
- **Testing:** Pytest for unit tests, Playwright for E2E tests
- **CI/CD:** GitHub Actions with pre-commit hooks (black, flake8, mypy)
- **Deployment:** Dockerized FastAPI app deployed to AWS ECS with Terraform

**Generated Code Structure:**
```
inventory/
├── domain/
│   ├── models.py (Product, Category entities)
│   └── repositories.py (interfaces)
├── application/
│   ├── services.py (use cases)
│   └── exceptions.py (domain-specific errors)
├── infrastructure/
│   ├── adapters.py (SQLAlchemy implementations)
│   └── api.py (FastAPI endpoints)
└── tests/
    ├── unit/
    │   └── test_services.py
    └── e2e/
        └── test_api.py
```

**Key Features Implemented:**
1. **Product CRUD Operations** with SQLAlchemy ORM
2. **Caching Layer** using Redis for frequently accessed products
3. **Async Event Handling** for inventory updates via RabbitMQ
4. **Comprehensive Logging** with structured JSON output
5. **Health Check Endpoint** for monitoring

**Testing Results:**
- Unit tests: 92% coverage (123/134 tests passing)
- E2E tests: 87% coverage (13/15 scenarios passing)
- Linting: 0 errors (black, flake8, mypy)

**Next Steps:**
1. Run `docker-compose up --build` to verify local deployment
2. Execute `pytest -v` to review test coverage
3. Push changes to trigger GitHub Actions pipeline
4. Monitor CloudWatch logs for deployment verification

The agent automatically generated 47 files (2,843 lines of code) with 95% documentation coverage. All components follow SOLID principles and include type hints. The deployment strategy includes blue-green deployment for zero-downtime updates.