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Godot Genre Roguelike

Community
thedivergentai
godot-genre-roguelike

Expert blueprint for roguelikes including procedural generation (Walker method, BSP rooms), permadeath with meta-progression (unlock persistence), run state vs meta state separation, seeded RNG (shareable runs), loot/relic systems (hook-based modifiers), and difficulty scaling (floor-based progression). Use for dungeon crawlers, action roguelikes, or roguelites. Trigger keywords: roguelike, procedural_generation, permadeath, meta_progression, seeded_RNG, relic_system, run_state.

Overview

Publisherthedivergentai
RepositoryGD-Agentic-Skills
Skill namegodot-genre-roguelike
Stars
727
Forks
43
Bundled files
23
LicenseLGPL-3.0
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • 23 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by thedivergentai on GitHub. Read the source before you install it.

Installation

Install the Godot Genre Roguelike AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/thedivergentai/GD-Agentic-Skills.git /tmp/GD-Agentic-Skills
mkdir -p .claude/skills
cp -r /tmp/GD-Agentic-Skills/skills/godot-genre-roguelike .claude/skills/godot-genre-roguelike
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Godot Genre Roguelike in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Godot Genre Roguelike on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Godot Genre Roguelike is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

NEVER Do (Expert Anti-Patterns)

Generation & RNG

  • NEVER make runs dependent on pure RNG; strictly provide mitigation (rerolls, shops, pity timers) to ensure every run is winnable.
  • NEVER use unseeded RNG for world generation; strictly initialize isolated RandomNumberGenerator with a predictable seed for daily runs/debugging.
  • NEVER rely on @GlobalScope.randi() for critical logic; strictly use local RNG instances to prevent global state pollution.
  • NEVER use Array.pick_random() for critical content drops; strictly use a Shuffle Bag to prevent statistically unfair streaks.
  • NEVER generate massive dungeons on the main thread; strictly use WorkerThreadPool.add_task() or add_group_task() to distribute generation across cores and prevent frame freezes.
  • NEVER interact with the SceneTree from a background thread; strictly generate dungeon data in a thread-safe Array/PackedByteArray before parsing on the main thread.

Data & State

  • NEVER allow Save Scumming; strictly delete mid-run save files immediately upon loading to enforce permadeath.
  • NEVER allow the player to see the "Edge of the World"; strictly use Fog of War or limited vision cones to maintain the mystery of the unknown.
  • NEVER evaluate complex "Director" heuristics every frame; strictly use Frame-Slicing (Engine.get_process_frames()) to run heavy pacing logic only once every 60-120 frames for CPU efficiency.
  • NEVER move rooms individually by pixel values during procedural generation; strictly use Marker2D Connection Points in pre-authored scenes to calculate exact offsets for seamless room stitching.
  • NEVER allow Run State to leak into Meta State; strictly use separate singletons or Resources for RunManager and MetaManager.
  • NEVER scale meta-progression to be overpowered (+100% damage); strictly keep upgrades subtle (+5-15%) to maintain skill-based play.
  • NEVER forget to call duplicate(true) on base stat Resources; failing to deep-duplicate causes all entities to share a single health instance.
  • NEVER save run states to .tscn files; strictly serialize to JSON or binary in user:// to prevent bloat.
  • NEVER rely on the SceneTree as the source of truth for grid logic; strictly maintain grid data in a separate Dictionary or Array.

Grid & Performance

  • NEVER forget to handle Navigation re-baking; strictly rebake NavigationRegion2D AFTER procedural tiles are placed.
  • NEVER use AStar2D for tile grids; strictly use AStarGrid2D with jumping_enabled = true (Jump Point Search) for O(1) queries and high-performance pathing across open areas.
  • NEVER forget to call update() on AStarGrid2D after modifying states; strictly ensures pathfinding queries aren't stale.
  • NEVER use floats (Vector2) for discrete grid coordinates; strictly use Vector2i to prevent precision drift.
  • NEVER use Manhattan heuristics for 8-way movement; strictly use HEURISTIC_CHEBYSHEV or HEURISTIC_OCTILE.
  • NEVER iterate over every cell coordinate (0 to W,H) in GDScript; strictly use get_used_cells() for optimized tile access.
  • NEVER clear procedural levels using free(); strictly use queue_free() to avoid mid-frame segmentation faults.
  • NEVER broadcast mass state changes to a grid immediately; strictly use call_deferred() or call_group_flags to avoid frame spikes during turn transitions.
  • NEVER use heavy TileMapLayer nodes for high-resolution Fog of War; strictly use a GPU Shader Mask via ColorRect and an ImageTexture updated via RenderingServer.texture_2d_update().

🛠 Expert Components (scripts/)

MANDATORY before implementing generation, seed sharing, or meta unlocks — read these first (do not reinvent from inline samples):

Do NOT Load the full scripts/ folder for a single task. Open only the script that matches the phase below.

Original Expert Patterns

Modular Components

Core Loop

  1. Preparation: Select character, equip meta-upgrades (see meta_progression_resource.gd).
  2. The Run: complete procedural levels (dungeon_generator_walker.gd), acquire temporary power-ups.
  3. The Challenge: Survive increasingly difficult encounters using A* pathfinding (astar_grid_handler.gd).
  4. Death/Victory: Run ends, resources calculated.
  5. Meta-Progression: Spend resources on permanent unlocks (meta_progression_resource.gd).
  6. Repeat: Start a new run with new capabilities.

Skill Chain

PhaseSkillsPurpose
1. Architecturegodot-autoload-architecture, godot-state-machine-advancedRun State vs Meta State boundaries
2. World Gengodot-procedural-generation, godot-tilemap-masteryUnique levels every run (walker/BSP/noise)
3. Combatgodot-combat-system, godot-ai-navigationHigh-stakes encounters + FOV/pathing
4. Progressiongodot-inventory-system, godot-resource-data-patternsRun items/relics + typed Resources
5. Persistencegodot-save-load-systemsMeta unlocks + anti-scum mid-run deletes
6. Balancegodot-monte-carlo-balancerWin% vs meta level; dead-item detection

Architecture Overview

Roguelikes require a strict separation between Run State (temporary) and Meta State (persistent).

Key Mechanics (route to scripts/)

Procedural Dungeon Generation

Relics, turns, fog, pacing

Common Pitfalls

  1. RNG Dependency: Don't make runs entirely dependent on luck. Good roguelikes allow skill to mitigate bad RNG.
  2. Meta-progression Imbalance: If meta-upgrades are too strong, the game becomes a "grind to win" rather than "learn to win".
  3. Lack of Variety: Procedural generation is only as good as the content it arranges. You need a lot of content (rooms, enemies, items) to keep it fresh.
  4. Save Scumming: Players will try to quit to avoid death. Save the state only on floor transition or quit, and delete the save on load (optional, but standard for strict roguelikes).

Godot-Specific Tips

  • Seeded Runs: Always initialize RandomNumberGenerator with a seed. This allows players to share specific run layouts.
  • ResourceSaver: Use ResourceSaver for meta-progression, but be careful with cyclical references in deeply nested resources.
  • Scenes as Rooms: Build your "rooms" as separate scenes (Room1.tscn, Room2.tscn) and instance them into the generated layout for handcrafted quality within procedural layouts.
  • Navigation: Rebake NavigationRegion2D at runtime after generating the dungeon layout if using 2D navigation.

Advanced Techniques

  • Synergy System: Tag items (fire, projectile, companion) and check for tag combinations to create emergent power-ups.
  • Director AI: An invisible "Director" system that tracks player health/stress and adjusts spawn rates dynamically (like Left 4 Dead).

MANDATORY for depth beyond decision trees and script catalog: roguelike-meta-systems-deep.md. Do NOT Load on first-pass wiring — use bundled scripts/ first.

Reference

Progressive disclosure: open Official Documentation links only when researching a specific API; load Related Skills when routing to a peer domain — do not preload the whole lattice.

Official Documentation

  • Using TileMaps — TileMapLayer cells, sources, and runtime placement for procedural floors/walls.
  • TileMapLayerset_cell / get_used_cells APIs used after walker/BSP generation and fog clears.
  • AStarGrid2D — grid pathfinding with heuristics, diagonal modes, and update() after solid-cell edits.
  • RandomNumberGenerator — seeded PCG32 for shareable runs; prefer local instances over global randi().
  • WorkerThreadPool — offload heavy dungeon generation without freezing the main thread.
  • Using multiple threads — when WorkerThreadPool/tasks are safe versus SceneTree ownership rules.
  • Thread-safe APIs — generate data off-thread, then apply tiles/nodes on the main thread only.
  • Saving gamesuser:// persistence patterns for meta unlocks and anti-scum mid-run deletes.
  • Resources — Resource-backed meta/run data, duplicate(true), and save/load of .tres/custom resources.
  • Singletons (AutoLoad) — isolate RunManager vs MetaManager so run death cannot wipe permanent progress.
  • Ray-casting — PhysicsDirectSpaceState queries for FOV / line-of-sight without Area2D spam.
  • FastNoiseLite — noise fields for cave-style maps before connectivity validation with AStarGrid2D.

Related Skills

Prerequisites
Complements
Downstream / consumers
Master
  • godot-master — library router and mirrored module entry for cross-skill discovery.

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Godot Genre Roguelike AI skill do?

Expert blueprint for roguelikes including procedural generation (Walker method, BSP rooms), permadeath with meta-progression (unlock persistence), run state vs meta state separation, seeded RNG (shareable runs), loot/relic systems (hook-based modifiers), and difficulty scaling (floor-based progression). Use for dungeon crawlers, action roguelikes, or roguelites. Trigger keywords: roguelike, procedural_generation, permadeath, meta_progression, seeded_RNG, relic_system, run_state.

Why use Godot Genre Roguelike on TypingMind?

Because you install it once and use it with any model. Godot Genre Roguelike is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Godot Genre Roguelike in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/thedivergentai/GD-Agentic-Skills/tree/main/skills/godot-genre-roguelike. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Godot Genre Roguelike?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Godot Genre Roguelike?

As many as you like. As long as a model supports skills, you can use Godot Genre Roguelike with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Godot Genre Roguelike AI skill free?

Yes. It is published on GitHub by thedivergentai under the LGPL-3.0 license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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