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Threejs World Generation

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calesthio
threejs-world-generation

Build deterministic, editable, free-viewpoint Three.js worlds from text or structured briefs. Use for cinematic 3D terrain, semantic regions, procedural biomes, explicit landmarks, environmental scattering, camera fly-throughs, world diagnostics, or requests for a real 3D environment rather than generated 2D footage. Integrates OpenMontage's threejs_world tool with HyperFrames; do not use for a single isolated 3D object or a flat parallax scene.

Overview

Publishercalesthio
RepositoryOpenMontage
Skill namethreejs-world-generation
Stars
67K
Forks
8.5K
Bundled files
3
LicenseAGPL-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.

  • 3 bundled files

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

  • Open source

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

Installation

Install the Threejs World Generation 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/calesthio/OpenMontage/tree/main/.agents/skills/threejs-world-generation
  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/calesthio/OpenMontage.git /tmp/OpenMontage
mkdir -p .claude/skills
cp -r /tmp/OpenMontage/.agents/skills/threejs-world-generation .claude/skills/threejs-world-generation
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Threejs World Generation 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 Threejs World Generation 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 Threejs World Generation 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.

Three.js World Generation

For production meshes and Blender assembly, also read 3d-asset-generation. Three.js remains the semantic interactive/blockout renderer; Blender is the production renderer when the brief calls for dense reference-grade scenery.

The production handoff must include target dimensions for imported assets, semantic scatter exclusion zones, terrain-following water/path geometry, landmark visibility policy, camera clearance, and global/regional/walk review frames. These are world-spec contracts, not manual Blender cleanup notes.

Create a persistent scene graph, not a sequence of unrelated 2D shots. Preserve the user's explicit constraints, infer missing construction details separately, establish the global terrain first, and refine selected regions without disturbing the world-wide spatial contract.

Choose the fidelity tier explicitly

  • blockout: procedural primitives, vertex colors, semantic/layout validation, fast iteration. Never call this production-quality, reference-grade, or visually equivalent to WorldClaw.
  • production: licensed local GLTF/GLB catalogs, a minimum eight-model palette across four semantic categories, three PBR terrain layers, asset provenance, walk-level repetition review, and no primitive landmark fallback.

For a hero video or any reference showing populated textured environments, use production. If its catalog/material/provider requirements cannot be met, stop at preflight or the asset gate. Do not render a blockout as the final deliverable.

Read first

  • Read references/worldclaw-principles.md when planning or explaining the coarse-to-fine method.
  • Read references/world-spec.md before authoring a world_spec or calling threejs_world.
  • Read hyperframes-core, hyperframes-animation, and hyperframes-animation/adapters/three.md before editing the emitted workspace.
  • Read threejs-loaders, threejs-materials, threejs-textures, threejs-lighting, and threejs-postprocessing for production-tier work.

Route the request

  • Use the animation pipeline for design-led, explanatory, abstract, or music-led world films.
  • Use the cinematic pipeline for trailer-like mood, dramatic reveals, or source-plus-world edits.
  • Choose HyperFrames when the deliverable is the code-native Three.js world. Choose Blender for reference-grade hero rendering and FFmpeg only to package Blender's numbered frames and approved audio. Record that choice at proposal; do not silently switch after approval.
  • Keep this as a capability inside existing pipelines. Do not create a new pipeline merely because a scene is 3D.

Workflow

1. Separate intent from completion

Record two lists before planning:

  • explicit_constraints: only facts the user supplied.
  • inferred_details: scale, region coverage, terrain operators, densities, palette refinements, and camera details added to make the world executable.

Never smuggle an inferred landmark, biome, or story beat into the explicit list.

2. Plan globally

Author one shared world_spec containing:

  • world scale, terrain resolution, elevation range, and seed;
  • semantic regions with normalized centers, radii, landform operators, palette, and scatter recipes;
  • atmosphere and lighting shared across all regions;
  • explicit landmarks with stable IDs and world-space placement;
  • a complete camera path with time, position, target, and field of view.

Prefer 3-7 regions. Each region must contribute a distinct silhouette, surface read, or functional role.

3. Build the terrain foundation

For production, first call threejs_asset_catalog to install rights-safe catalogs under projects/<id>/assets/3d/catalogs/<catalog-id>/. Record source, license, archive hash, model inventory, and every selected model in the asset manifest. Then call threejs_world with quality_tier: "production" and the installed catalog paths.

python
from tools.graphics.threejs_world import ThreeJSWorld

result = ThreeJSWorld().execute({
    "operation": "build",
    "world_spec": world_spec,
    "output_path": "projects/<id>/hyperframes",
    "duration_seconds": 60,
    "render_mode": "cinematic",
    "quality_tier": "production",
    "asset_catalog_paths": ["projects/<id>/assets/3d/catalogs/kenney-nature-kit"],
})

Treat world.json, world-spec.js, world-runtime.js, and world-report.json as editable assets. Do not flatten them into a video until the assets gate is approved.

4. Inspect regionally

Build a second pass with render_mode: "semantic" or "wireframe" when spatial problems are hard to see in the cinematic material pass. Inspect snapshots from global, regional, and walk-level viewpoints.

Maintain an issue queue with stable subjects:

  • terrain transition or silhouette;
  • landmark scale, pose, or contact;
  • scatter density, slope rejection, or repetition;
  • material contrast and atmosphere;
  • camera clearance, clipping, or weak framing.

Fix only the affected region or object when possible. Preserve the seed, region IDs, camera times, and unrelated parameters.

5. Refine with bounded loops

Run at most three render-guided refinement rounds:

  1. build the workspace;
  2. run the unified HyperFrames check gate and snapshot representative times;
  3. inspect frames and update the issue queue;
  4. change the narrowest relevant spec fields;
  5. rebuild with the same seed and compare.

Stop when no substantial issue remains or the iteration budget is reached. Report residual limitations rather than disguising them with overlays.

6. Compose without overwriting

For browser-native delivery, set render_runtime: "hyperframes" and composition_mode: "atelier"; video_compose must preserve the authored workspace. For reference-grade video, render a Blender PNG sequence with resume: true, then set render_runtime: "ffmpeg" for packaging. Preserve the world spec and .blend as the editable source of truth.

Quality gates

  • Terrain is continuous and region boundaries blend without obvious seams.
  • Every landmark touches its support surface and remains inside world bounds.
  • Scatter respects region affinity, slope limits, and deterministic seed behavior.
  • Global, regional, and walk-level frames all read as the same continuous world.
  • Camera paths remain above terrain, avoid clipping, and provide at least one scale-establishing reveal.
  • World source remains editable after render: regions, landmarks, camera keys, and palette have stable IDs or fields.
  • HyperFrames check and post-render review pass before delivery. Use the legacy validate or inspect operations only when supporting an older runtime.
  • Production beauty frames contain textured assets at foreground, midground, and background depths; no dominant object may read as an untextured box, cone, octahedron, or dodecahedron.
  • Production requires at least four semantic asset categories, eight distinct models, three PBR terrain layers, one regional composition review per camera-critical region, and explicit repetition/contact findings.

Boundaries

  • The production catalog path materially improves geometry and surface richness, but it still does not reproduce WorldClaw's GPT-Image-2, SAM3, SAM3D, Hunyuan3D, BlenderMCP, or four-H20 implementation.
  • Do not claim articulated assets, game physics, navigation meshes, or interaction logic unless another tool explicitly adds them.
  • Do not use unseeded randomness, wall-clock animation, remote models, or render-time asset fetches.
  • Do not delete the lower-level threejs-* skills. They are the subsystem references used when extending this runtime.

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 Threejs World Generation AI skill do?

Build deterministic, editable, free-viewpoint Three.js worlds from text or structured briefs. Use for cinematic 3D terrain, semantic regions, procedural biomes, explicit landmarks, environmental scattering, camera fly-throughs, world diagnostics, or requests for a real 3D environment rather than generated 2D footage. Integrates OpenMontage's threejs_world tool with HyperFrames; do not use for a single isolated 3D object or a flat parallax scene.

Why use Threejs World Generation on TypingMind?

Because you install it once and use it with any model. Threejs World Generation 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 Threejs World Generation in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/calesthio/OpenMontage/tree/main/.agents/skills/threejs-world-generation. 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 Threejs World Generation?

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 Threejs World Generation?

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

Is the Threejs World Generation AI skill free?

Yes. It is published on GitHub by calesthio under the AGPL-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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