aaabench: Skill for Claude Code

Procedural generation

Generate levels, terrain, and loot from compact rules and a seed. The throughline of good procgen is determinism: a single seed reproduces the same world, so bugs are repeatable and players can share seeds. This skill owns the core algorithms — noise, seeded RNG, dungeon layout, weighted tables; genres like roguelike and survival-crafting consume it.

When to use

• Use to generate maps, dungeons, terrain heightmaps, item drops, or any content you do not want to author by hand.
• Use when results must be reproducible from a seed (debugging, daily challenges, shareable worlds).
• Use to pick weighted random outcomes (loot rarity, spawn tables).

When not to use: for the engine's tile API to paint the result, use godot-tilemap or unity-tilemap-2d. For routing AI through the generated map, use game-ai. For carefully hand-paced levels, use level-design — procgen and authored design are complementary, not interchangeable.

Core workflow

1. Own your randomness. Create one seeded RNG instance and pass it everywhere. Never call the global/static random in generation code — it makes results irreproducible and order-dependent.
2. Pick the technique for the content. Continuous terrain/heightmaps → noise. Discrete rooms/corridors → space partitioning or agent-based carving. Outcomes with rarities → weighted tables.
3. Generate into a plain data grid/array first, decoupled from rendering. Generation fills int[][] or a dict; a separate pass draws it.
4. Validate before shipping the result to the player. Is every room reachable? Is the spawn safe? Is there a path to the exit? Reject or repair layouts that fail; do not hand the player a broken map.
5. Tune with the seed fixed so each parameter change is visible in isolation, then sweep seeds to check the distribution, not just one lucky map.

Patterns

1. Seeded, deterministic RNG (the foundation)

import random
rng = random.Random(seed)        # a dedicated instance — NOT the global random.*
room_count = rng.randint(5, 12)  # same seed -> same sequence, every run
# RIGHT: thread `rng` through every function that makes a choice.
# WRONG: calling random.randint(...) (global state) — order-dependent, unseedable.