Procedural Modeling

Community

arjun988

procedural-modeling

Procedural asset creation for rocks, buildings, vegetation, roads, terrain, pipes, cables, and sci-fi panels using Geometry Nodes and modifier-based workflows in Blender via MCP.

Overview

Publisher	arjun988
Repository	`blender-skills`
Skill name	`procedural-modeling`
Stars	384
Forks	22
Bundled files	Instructions only
License	MIT
Links	Skill source Repository Homepage

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 arjun988 on GitHub. Read the source before you install it.

Installation

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

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.

Open the app and go to Plugins → Skills.
Choose "Install from GitHub".
Paste the skill folder URL below and confirm.
https://github.com/arjun988/blender-skills/tree/main/.claude/skills/procedural-modeling
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.

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/arjun988/blender-skills.git /tmp/blender-skills
mkdir -p .claude/skills
cp -r /tmp/blender-skills/.claude/skills/procedural-modeling .claude/skills/procedural-modeling

Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Procedural Modeling 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 Procedural Modeling 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 Procedural Modeling 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.

Procedural Modeling

Parametric assets with art-directable variation. Geometry Nodes priority. Bake for game export.

When to Use

Rocks, cliffs, terrain features
Modular building generation
Road and path systems
Pipe/cable networks
Sci-fi panel arrays
Vegetation placement systems

Workflow


Define Parameters → Build Procedural System → Validate Variations
    → Realize/Bake → Optimize → Export

System Categories

System	Primary Tool	Output
Rocks	Geo Nodes + noise	Static mesh
Buildings	Geo Nodes stack	Modular pieces
Roads	Curve + Geo Nodes	Mesh strip
Pipes	Curve to mesh	Network
Vegetation	Scatter GN	Instanced/baked
Sci-fi panels	Array + random	Trim sheet geo

Rock Generation


Base shape (ico sphere) → Displace (multi-scale noise)
    → Decimate → Subdivide (selective) → Weighted Normal
    → Variation: seed input controls all noise

Expose: seed, scale, roughness, density

Building Generation


Footprint curve → Extrude floors → Window boolean pattern
    → Balcony probability → Roof type switch → Material ID

Output separate meshes per floor module for game kits.

Road Systems


Centerline curve → Resample → Cross-section profile
    → Bridge blend at intersections → UV follow curve

Pipe/Cable Networks


Node graph points → Connect minimum spanning → Curve segments
    → Profile sweep → Collision offset → Clamp size range

Sci-Fi Panels


Grid subdivide → Random inset/extrude → Bevel
    → Panel index → Material variation
    → Bake to trim sheet layout

Variation Testing

Test at parameter extremes:

Minimum scale/density
Maximum scale/density
Seed 0, 42, 9999 (reproducibility check)

Game Export Decision

Approach	When
Keep procedural in Blender only	Iteration phase
Realize single variant	Standard game prop
Bake multiple seeds as LOD variants	Background variety
Export node group to engine	Only if engine supports

MCP Integration

Build procedural systems via MCP
Set seed/density parameters via MCP
Realize geometry via MCP
Query output polycount per variation
Export realized meshes

Constraints

MUST DO

Expose seed for reproducibility
Test min/max parameter bounds
Realize before game engine export
Optimize after realize (asset-optimization)
Document parameter ranges in production brief

MUST NOT DO

Export unrealsized geometry nodes to game without validation
Infinite variation without performance testing
Procedural where manual hero quality required
Skip UV planning on procedural output
Hardcode random without seed control

Reference Guide

Topic	Reference	Load When
Geo nodes patterns	`../geometry-nodes/SKILL.md`	Node setup
Environment integration	`../environment-artist/SKILL.md`	Scene placement

Frequently asked questions

What does the Procedural Modeling AI skill do?

Procedural asset creation for rocks, buildings, vegetation, roads, terrain, pipes, cables, and sci-fi panels using Geometry Nodes and modifier-based workflows in Blender via MCP.

Why use Procedural Modeling on TypingMind?

Because you install it once and use it with any model. Procedural Modeling 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 Procedural Modeling in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/arjun988/blender-skills/tree/main/.claude/skills/procedural-modeling. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Procedural Modeling?

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 Procedural Modeling?

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

Is the Procedural Modeling AI skill free?

Yes. It is published on GitHub by arjun988 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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Overview

Installation

Install in TypingMind

Install in another agent

Use it in TypingMind

Works with any AI model

Skill instructions

Procedural Modeling

When to Use

Workflow

System Categories

Rock Generation

Building Generation

Road Systems

Pipe/Cable Networks

Sci-Fi Panels

Variation Testing

Game Export Decision

MCP Integration

Constraints

MUST DO

MUST NOT DO

Reference Guide

Frequently asked questions

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