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Game Level Design

Community
witnesstodark
game-level-design

Turn a game-level brief or existing scene snapshot into a reviewable spatial plan, then apply approved changes with coordinate, navigation and scene checks. Use for layouts, encounter placement and terrain plans.

Overview

Publisherwitnesstodark
Repositorymr-mak-workspace
Skill namegame-level-design
Stars
545
Forks
183
Bundled files
Instructions only
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.

  • Self-contained

    Everything the model needs lives in the instructions — no extra files to sync.

  • Open source

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

Installation

Install the Game Level Design 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.
    https://github.com/witnesstodark/mr-mak-workspace/tree/main/.agents/skills/game-level-design
  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/witnesstodark/mr-mak-workspace.git /tmp/mr-mak-workspace
mkdir -p .claude/skills
cp -r /tmp/mr-mak-workspace/.agents/skills/game-level-design .claude/skills/game-level-design
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Game Level Design 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 Game Level Design 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 Game Level Design 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.

Game level design

Establish the play goal, scale, camera, movement/navigation limits and existing visual setup. Inspect the scene and documented mechanics before proposing placements. Reuse approved lighting/material settings when making another level; a new layout does not imply permission to redesign the game's presentation.

Keep source and proposal separate

For an existing level, capture a read-only source snapshot with scene identity, units, origin, axis convention, terrain/navigation data and object IDs. Record source hashes or revisions. For a new level, label the baseline as a proposal; do not describe a generated map as an engine export.

Store edits separately: layer overrides, marker additions/moves/removals and design notes. Keep alternate layouts independent. Regeneration must not silently replace a user's edited draft. On a changed source, preserve a recovery copy and resolve conflicts rather than treating the draft as disposable.

Make the plan useful for decisions

Show terrain, passage, obstacles, cover and objectives as distinct layers. Define brush/cell sizes in world units. Visual ground colour is not necessarily a navigation blocker; tree cover, water and a road may have different rules. Preserve stable marker IDs and distinguish counts, capacity and starting occupants. Unchosen prefabs or mechanics remain explicit design intent.

Check main/alternate routes, chokepoint width, clearances, encounter order and travel distances against actual character sizes and speeds. A 2D simulation can compare strategies only within its documented assumptions. Its result does not prove native navigation, combat behaviour or final balance.

Apply only the approved plan

Export a manifest mapping coordinates, source revision and markers to engine assets. Reject stale/conflicting revisions before applying. Confirm the target scene and which objects are generated; do not overwrite an unrelated authored scene or manual edits as a side effect of a rebuild.

Verify saved terrain dimensions, height/axis conversion, prefab references, colliders, navigable paths, spawn locations and camera bounds in the engine. Traverse representative routes and test the changed encounter flow. Preserve unrelated gameplay values and assets. Deliver the editable plan, applied scene, export manifest, native captures and unresolved choices.

Example request: "Plan a small valley with two routes to the objective, then apply the chosen version." Success includes a reviewable layout, measured route clearance and a verified native path through the saved scene. Dependencies: project design rules; an editor bridge/CLI or engine access for scene work.

Frequently asked questions

What does the Game Level Design AI skill do?

Turn a game-level brief or existing scene snapshot into a reviewable spatial plan, then apply approved changes with coordinate, navigation and scene checks. Use for layouts, encounter placement and terrain plans.

Why use Game Level Design on TypingMind?

Because you install it once and use it with any model. Game Level Design 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 Game Level Design in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/witnesstodark/mr-mak-workspace/tree/main/.agents/skills/game-level-design. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Game Level Design?

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 Game Level Design?

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

Is the Game Level Design AI skill free?

Yes. It is published on GitHub by witnesstodark 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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