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Author Game Levels

CommunityPopular
MengTo
author-game-levels

Author or revise readable, flat-world Three.js game levels. Use for movement and camera routes, collision and navigation, encounter zones, landmarks, objectives, pickups, motivated lighting, visibility, deterministic level data, or desktop and mobile playthrough verification.

Overview

PublisherMengTo
RepositorySkills
Skill nameauthor-game-levels
Stars
6.1K
Forks
717
Bundled files
1
LicenseMIT
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.

  • 1 bundled files

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

  • Open source

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

Installation

Install the Author Game Levels 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/MengTo/Skills.git /tmp/Skills
mkdir -p .claude/skills
cp -r /tmp/Skills/agent-skills/game-development/author-game-levels .claude/skills/author-game-levels
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Author Game Levels 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 Author Game Levels 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 Author Game Levels 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.

Author Game Levels

Treat architecture as gameplay communication. Every route, arena, gate, prop, and light must help the player read movement, threats, objectives, or state.

Enforce one gameplay plane

Keep all collision, navigation, encounter routes, objectives, pickups, and player movement on one accessible plane.

  • Do not add stairs, ramps, raised platforms, drop-offs, cliffs, bridges, ledges, pits, or vertical traversal.
  • Do not change gameplay elevation for shortcuts, arenas, hazards, rewards, or visual variety.
  • If visual height is requested later, keep it non-walkable background dressing. It must not alter navigation, camera occlusion, threat visibility, targetability, or player movement.

Separate level systems

Maintain explicit, independently testable layers for:

  • authored level data and stable zone/anchor IDs;
  • visual geometry and non-walkable background dressing;
  • simplified collision geometry;
  • flat navigation data and movement clearance;
  • encounter, enemy, gate, reset, pickup, objective, and exit zones.

Share stable IDs and transforms between layers, but never infer collision, navigation, or encounter boundaries from decoration alone.

Lay out readable play

  1. Define the architectural purpose of each space: traversal, orientation, combat, recovery, reward, transition, or objective.
  2. Preserve clear movement, camera, and dodge corridors at the intended play distance.
  3. Keep threats, pickups, exits, gates, and interaction targets visible before commitment.
  4. Telegraph encounters through visible arena shape, approach, state change, and stable zone anchors.
  5. Deliberately place arenas, gates, checkpoints, retry spawns, and reset paths. Prevent soft locks, duplicate rewards, hidden re-entry, and enemies pursuing through unrelated zones.
  6. Use landmarks, lighting, contrast, and composition to guide without hiding hazards or making the route ambiguous.

Motivate every local light

Attach every local torch, lantern, brazier, or similar light spatially to a visible emitter. Its position, range, color, intensity, shadowing, and occlusion behavior must match what that emitter appears able to produce.

  • Forbid unexplained floating local lights.
  • Keep a source-to-light inventory with emitter ID, light ID, attachment transform, type, range, color/intensity, occlusion intent, enabled state, and fallback behavior.
  • Move the light with a moving emitter. Disable or remove its local contribution when the emitter is disabled, hidden, destroyed, or unloaded.
  • Document ambient or world lighting separately. Use it for deliberate global visibility or mood, never to fake a torch or other local source.

Validate data and geometry

  • Assert that all walkable collision, navigation vertices/links, encounter anchors, gates, objectives, pickups, exits, and reset points remain on the configured gameplay plane within a small tolerance.
  • Reject walkable slopes, out-of-plane links, vertical shortcuts, elevated spawn points, and level data that implies height-changing traversal.
  • Check collision/nav agreement, route clearance, zone containment, deterministic gate/reset behavior, stable anchor references, and persistence of level progress.
  • Validate source-to-light inventory completeness, emitter/light attachment, range/color intent, and moving or disabled emitter state transitions.

Prove traversal in the browser

Run deterministic route, collision, navigation, encounter, reset, and lighting fixtures, then traverse every critical and optional route in the repository-approved browser.

  • On desktop and mobile, verify uninterrupted flat movement, dodge clearance, camera framing, threat/pickup/exit visibility, encounter telegraphs, gates, retry paths, and touch controls.
  • Exercise moving and disabled emitter cases and confirm no light remains detached or unexplained.
  • Inspect dense views for occlusion, console health, frame time, draw calls, memory stability, and long-session lighting cost.
  • Report new failures separately from existing baseline issues.

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 Author Game Levels AI skill do?

Author or revise readable, flat-world Three.js game levels. Use for movement and camera routes, collision and navigation, encounter zones, landmarks, objectives, pickups, motivated lighting, visibility, deterministic level data, or desktop and mobile playthrough verification.

Why use Author Game Levels on TypingMind?

Because you install it once and use it with any model. Author Game Levels 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 Author Game Levels in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/MengTo/Skills/tree/main/agent-skills/game-development/author-game-levels. 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 Author Game Levels?

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 Author Game Levels?

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

Is the Author Game Levels AI skill free?

Yes. It is published on GitHub by MengTo under the MIT 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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