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A reusable AI engineering system for Google Antigravity featuring specialized AI skills, coding standards, architecture guidelines, security practices, testing workflows, and SaaS project templates.

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FlerkenStudio Antigravity Engineering System (FAES)

A reusable, production-minded engineering playbook for Google Antigravity. It provides global and workspace skills, always-on engineering rules, project templates, and repeatable delivery workflows.

What is included

  • AGENTS.md: always-on workspace engineering contract.
  • skills/: reusable Agent Skills (each has a SKILL.md).
  • instructions/: detailed engineering standards for humans and agents.
  • templates/: PRD, architecture, API, database, security, ADR and project starter templates.
  • workflows/: practical step-by-step delivery playbooks.
  • install/: Windows PowerShell scripts for global and workspace installation.
  • examples/: sample project configuration.

Quick start (Windows PowerShell)

  1. Extract this repository or clone it from your GitHub repository.

  2. Open PowerShell in the repository root.

  3. Install globally (available to all Antigravity workspaces):

    Set-ExecutionPolicy -Scope Process Bypass
    .\install\Install-Global.ps1 -InstallGlobalInstructions
  4. In each project, copy the workspace package:

    .\install\Install-Workspace.ps1 -ProjectPath 'C:\path\to\your-project'
  5. Restart or refresh Antigravity and inspect the Customizations/skills view. Skills can also be invoked by slash command, e.g. /backend-engineering.

Antigravity locations

  • Global skills: ~/.gemini/config/skills/<skill-name>/SKILL.md
  • Workspace skills: <project-root>/.agents/skills/<skill-name>/SKILL.md
  • Workspace instructions: <project-root>/AGENTS.md
  • Global instructions: ~/.gemini/AGENTS.md

These locations follow the current Antigravity documentation. See docs/ANTIGRAVITY-SETUP.md.

Safe usage model

FAES is an engineering guide, not a guarantee of secure or production-ready software. Agents must inspect the actual project, follow its existing conventions, run available checks, and clearly report what was not verified. Human review is required for security-sensitive changes, production migrations, credentials, payments, and deployment.

Recommended first run

Open a project in Antigravity and ask:

Read AGENTS.md and the relevant FAES skills. Inspect this repository without changing files. Summarize the architecture, stack, test commands, security-sensitive areas, and the top risks. Do not implement anything yet.

Then use workflows/new-project.md or workflows/feature-development.md.

Adapting the system

Keep global rules broadly applicable. Put stack- or product-specific requirements in the project-level AGENTS.md and .agents/skills/. Do not force one architecture, framework, database, or cloud provider on every product.

Karpathy-inspired principles and attribution

The karpathy-guidelines skill is an original, concise adaptation of four publicly described principles: think before coding, simplicity first, surgical changes, and goal-driven execution. It is not a copy of the upstream repository's complete files. Upstream: https://github.com/multica-ai/andrej-karpathy-skills (MIT license as shown by its repository at time of review). Review upstream license and attribution before redistributing any upstream files.

Versioning

Use semantic versioning for FAES releases. Record changes in CHANGELOG.md. Validate skills and scripts before distributing a new version.

About

A reusable AI engineering system for Google Antigravity featuring specialized AI skills, coding standards, architecture guidelines, security practices, testing workflows, and SaaS project templates.

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