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Dragoș-Andrei Bobu edited this page Jul 4, 2026 · 1 revision

Machine Learning Compatible Game Engine — Organization Wiki

This wiki documents the GitHub organization infrastructure for Machine Learning Compatible Game Engine.

This is not the main engine documentation. It is the operational guide for how repositories in the organization should be created, maintained, documented, and connected to shared GitHub defaults.

Purpose

The .github repository provides shared organization-level files and templates.

It contains:

  • default contribution guidance

  • default support and security files

  • issue templates

  • pull request templates

  • workflow templates for CI/CD

  • the public organization profile

  • lightweight maintenance documentation

The goal is to keep repositories consistent without adding unnecessary bureaucracy.

Main organization areas

The organization may contain several kinds of repositories:

Repository type | Purpose -- | -- Engine repositories | Core C++ / graphics / simulation / game-engine work ML experiment repositories | Python, machine learning, agents, evaluation scripts Documentation repositories | Research notes, thesis material, architecture docs Static site repositories | GitHub Pages websites, teaching demos, public documentation Archive repositories | Older work preserved for history or reference Infrastructure repositories | Shared GitHub templates, workflows, and organization configuration

These templates are available from:

Repository → Actions → New workflow → By Machine Learning Compatible Game Engine

Recommended repository setup

When creating a new repository in this organization:

  1. Choose a clear repository name.

  2. Add a short GitHub description.

  3. Add a README.md.

  4. Choose the correct workflow template, if needed.

  5. Add repository-specific documentation only when the shared defaults are not enough.

  6. Keep experimental code separated from stable documentation.

  7. Avoid committing secrets, generated build folders, local configuration, or personal files.

Naming guidance

Repository names should be readable, specific, and boring.

Prefer:

engine-core
agent-simulation-lab
ml-navigation-experiments
opengl-engine-prototype
thesis-archive
documentation-site

Avoid:

test
new-project
special
stuff
final-version
project-2

Public vs private repositories

Use public repositories for:

  • documentation intended to be shared

  • educational material

  • public demos

  • stable examples

  • non-sensitive research prototypes

Use private repositories for:

  • unfinished personal work

  • messy migration repositories

  • code containing private notes

  • work with unclear licensing

  • repositories that may include credentials, student data, or private files

When in doubt, keep the repository private until it is cleaned.

Maintenance principles

The organization should stay:

  • understandable

  • modular

  • easy to navigate

  • safe to publish

  • useful for research, teaching, and future development

Avoid unnecessary complexity. Prefer small repositories with clear purposes over large repositories with mixed content.

Wiki pages to add later

Suggested future pages:

  • Repository Naming Guide

  • Public vs Private Repository Policy

  • How to Choose a Workflow Template

  • GitHub Pages Setup

  • C++ Engine Repository Setup

  • Python ML Repository Setup

  • Documentation Repository Setup

  • Archive and Migration Policy

  • Security Checklist

  • Roadmap

Current status

This wiki starts as a lightweight operational manual for the organization.

It can grow as the Machine Learning Compatible Game Engine ecosystem becomes more structured.

Clone this wiki locally