# mxgmn/MarkovJunior

Probabilistic language based on pattern matching and constraint propagation, 153 examples

Repository: https://github.com/mxgmn/MarkovJunior
Canonical: https://ross.abutalabs.com/products/markovjunior
Language: C#
License: MIT
License Family: permissive
Topics: algorithms, csharp, gamedev, language, probabilistic-programming, procedural-generation, voxel, markovjunior, cellular-automata
Last push: 2026-03-20T00:05:35+00:00

## Health v2 (maintenance only)
Score: 56/100 (v2, computed 2026-09-03T02:20:16.233290+00:00)
- activity 73, release rhythm 8, longevity 100
- inputs: {"age_days": 1554, "days_push": 167, "days_rel": null, "gap_med": null, "n_releases_24m": 0}
- flags: none
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 8167, forks 349 (observed 2026-08-28T04:10:13.999589+00:00)

## What it is
MarkovJunior is a probabilistic programming language based on rewrite rules and constraint propagation, implemented in C#. It ships with an interpreter and 153 example models for generating dungeons, architecture, puzzles, and simulations.

## Use cases
- generate procedural dungeons for games
- create voxel architecture procedurally
- generate mazes with a backtracking algorithm
- build puzzle generators like Sokoban
- run probabilistic simulations on grids
- learn pattern-rewriting and constraint-based generation

## When to choose
- you need procedural content generation driven by rewrite rules
- you want constraint-guided random generation of grids or voxels
- you want a large set of working generative examples to learn from

## When to avoid
- you need a production game engine or rendering pipeline
- you need general-purpose probabilistic programming with statistical inference
- you need a language with a stable spec and long-term tooling

## Facets
- artifact type: library
- maturity: active
- function: interpreter, simulation, graphics, programming-language
- domain: graphics
- platform: cpp, cross-platform
- tags: procedural-generation, markov-algorithms, constraint-propagation, voxel, probabilistic-programming, gamedev, csharp, game-development, algorithms, desktop

## Member repositories
- mxgmn/MarkovJunior (main) score 56

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:10:13.999589+00:00.
- Health v2: computed from the inputs above; adoption is never an input.
- Inferred fields (summary, facets, guidance): AI-extracted, prompt v1, taxonomy v1, on 2026-08-30T07:21:10.929020+00:00, confidence not recorded.
  - readme: https://github.com/mxgmn/MarkovJunior (fetched 2026-08-28T04:10:13.999589+00:00, sha 71cccbe35818)
- Data as of 2026-08-30T08:39:29.467469+00:00.