What problem does it solve?
Procedural generation often produces inconsistent results, hard-to-reproduce bugs, and unbalanced content when randomness isn’t controlled; this Skill helps you build repeatable generation pipelines for games and simulations.
Core Features & Use Cases
- Seed-based reproducibility: Uses a deterministic RNG approach so the same seed yields the same maps, layouts, and loot.
- Noise & terrain generation: Produces continuous fields (e.g., height/biome/moisture maps) using Perlin/Simplex-style techniques and normalizes outputs for tile decisions.
- Dungeon and cave layout generation: Creates grid-aligned dungeons via BSP partitioning and organic cave regions via random walk variants.
- Weighted randomness for content: Supports loot tables and probability-weighted picks, including multi-drop selections without repeats.
- Wave Function Collapse basics: Builds tile layouts constrained by adjacency rules using entropy-driven collapse with weighted choice.
- Content placement & difficulty scaling: Adds natural spacing with Poisson disk sampling and ramps parameters over progression using difficulty profiles.
Use case example: You want a daily challenge mode where the terrain, dungeon structure, and loot are all consistent for a given date, but still vary across days and scales difficulty as the player advances.
Quick Start
Implement a seed-driven generator that derives separate sub-seeds for terrain, dungeons, and loot, then render the produced grid/positions/placements into your game world.
