Now liveThe Skillselion MCP - thousands of ranked skills, loaded into your agent mid-task. No install.Get it →
alphaonedev avatar

Procedural Generation

  • 50 installs
  • 6 repo stars
  • Updated March 13, 2026
  • alphaonedev/openclaw-graph

procedural-generation is a skill that algorithmically generates game content like terrains and levels using noise functions and rule-based systems.

About

procedural-generation is a skill that programmatically generates game content such as terrains and levels using noise functions and rule-based algorithms. A developer uses it to create dynamic, replayable worlds for roguelikes or infinite runners without manual design. It supports seed values for reproducibility and integrates with engines like Unity and Godot via CLI and API.

  • Generates 2D/3D terrains via Perlin/Simplex noise
  • Rule-based level generation (cellular automata, BSP dungeons)
  • Seedable, reproducible output with Unity and Godot integration

Procedural Generation by the numbers

  • 50 all-time installs (skills.sh)
  • Ranked #168 of 247 Game Development skills by installs in the Skillselion catalog
  • Data as of Jul 28, 2026 (Skillselion catalog sync)
At a glance

procedural-generation capabilities & compatibility

Requires OPENCLAW_API_KEY environment variable for CLI/API calls.

Capabilities
terrain generation · level generation · noise functions · engine integration
Works with
unity
Pricing
Bring your own API key
From the docs

What procedural-generation says it does

Algorithmic technique for generating game content like terrains and levels using noise functions and rules.
SKILL.md
Generate 2D/3D terrains via noise functions (e.g., Perlin, Simplex) with parameters for scale, octaves, and persistence.
SKILL.md
npx skills add https://github.com/alphaonedev/openclaw-graph --skill procedural-generation

Add your badge

Show developers this skill is listed on Skillselion. Paste this into your README.

Listed on Skillselion
Installs50
repo stars6
Last updatedMarch 13, 2026
Repositoryalphaonedev/openclaw-graph

What it does

Generate game terrains and levels algorithmically with noise functions and rule-based systems for engines like Unity and Godot.

Who is it for?

Generating dynamic, replayable game worlds and levels without manual design.

Skip if: Hand-authored fixed level design or non-game content.

When should I use this skill?

You need procedurally generated terrains or levels for a game.

What you get

Seedable, reproducible terrains and levels exported as JSON meshes or PNG heightmaps.

By the numbers

  • 2 noise functions named (Perlin, Simplex)
  • supports 2D and 3D terrain generation

Files

SKILL.mdMarkdownGitHub ↗

Purpose

This skill allows OpenClaw to programmatically generate game content, such as terrains and levels, using algorithms like Perlin noise and rule-based systems, reducing manual design effort.

When to Use

Apply this skill for dynamic content in games where variability is key, like procedural worlds in roguelikes or infinite runners, or when optimizing for replayability and asset efficiency in resource-constrained projects.

Key Capabilities

  • Generate 2D/3D terrains via noise functions (e.g., Perlin, Simplex) with parameters for scale, octaves, and persistence.
  • Create levels using rule-based algorithms, such as cellular automata for cave generation or binary space partitioning for dungeons.
  • Support custom seed values for reproducible outputs, integrating with game engines like Unity or Godot.
  • Handle multi-threaded generation for performance in real-time applications.
  • Export results in formats like JSON for meshes or PNG for heightmaps.

Usage Patterns

Always initialize with a seed for consistency; use CLI for quick prototyping and API for integration. Provide exact parameters to avoid defaults.

Example 1: Generating a Perlin terrain for a game world:

  • CLI command: openclaw generate terrain --noise perlin --seed 42 --width 256 --height 256 --output terrain.json
  • In code (Python): import openclaw; terrain_data = openclaw.api.generate_terrain({'noise': 'perlin', 'seed': 42, 'width': 256})

Example 2: Creating a procedural level with rules:

  • CLI command: openclaw generate level --rules '{"min_rooms": 5, "max_rooms": 10}' --seed 123 --output level.yaml
  • In code (JavaScript): const openclaw = require('openclaw'); const level = openclaw.api.generate_level({rules: {min_rooms: 5}, seed: 123});

Follow patterns by chaining commands, e.g., generate then validate: openclaw generate terrain ... && openclaw validate output.json.

Common Commands/API

Use the OpenClaw CLI or REST API; authenticate via $OPENCLAW_API_KEY environment variable.

  • CLI Commands:
  • openclaw generate terrain [flags]: Flags include --noise [type] (e.g., perlin), --seed [int], --scale [float]; e.g., openclaw generate terrain --noise perlin --seed 42.
  • openclaw generate level [flags]: Flags include --rules [JSON string]; e.g., openclaw generate level --rules '{"type": "dungeon"}'.
  • openclaw validate [file]: Checks generated output; e.g., openclaw validate terrain.json --check integrity.
  • API Endpoints:
  • POST /api/procedural/generate: Body as JSON, e.g., {"type": "terrain", "params": {"noise": "perlin", "seed": 42}}; requires header Authorization: Bearer $OPENCLAW_API_KEY.
  • GET /api/procedural/status: Query job status; e.g., GET /api/procedural/status?job_id=123 with auth header.

Config formats: Use JSON for API bodies, e.g., {"noise": "perlin", "octaves": 4}; for CLI, pass as flags or files, e.g., --config config.json where config.json is {"seed": 42}.

Integration Notes

Set $OPENCLAW_API_KEY in your environment before calls; integrate into game loops by importing the OpenClaw SDK and calling async functions. For Unity, use a C# wrapper: OpenClawAPI.GenerateTerrain(new Dictionary<string, object> { {"noise", "perlin"} });. In Godot, hook into scripts: var result = OpenClaw.generate_level({"rules": {"min_rooms": 5}}). Ensure error logging is enabled via SDK config, e.g., set openclaw.config.log_level = 'debug'.

Error Handling

Always wrap API/CLI calls in try-catch blocks; check for common errors like invalid parameters or network issues.

  • For CLI: Parse errors from stdout, e.g., if --noise is invalid, it returns "Error: Unknown noise type"; handle with scripts: if [ $? -ne 0 ]; then echo "Generation failed"; fi.
  • For API: Catch HTTP errors, e.g., in Python: try: response = openclaw.api.generate_terrain({...}) except openclaw.APIError as e: print(e.code) # e.g., 400 for bad request.
  • Specific cases: If seed is non-integer, API returns 422; validate inputs first, e.g., if not isinstance(seed, int): raise ValueError("Seed must be an integer").
  • Use retries for transient errors: In code, for attempt in range(3): try: openclaw.api.generate(...) except: time.sleep(1).

Graph Relationships

  • Related to: level-design (shares game-dev cluster for combined level building), asset-creation (uses generated content as inputs).
  • Depends on: noise-libraries (for underlying noise functions), game-engines (for integration hooks).

Related skills

FAQ

What can procedural-generation create?

It generates 2D/3D terrains via noise functions like Perlin and Simplex and creates levels using rule-based algorithms such as cellular automata or binary space partitioning.

Is output reproducible?

Yes, it supports custom seed values for reproducible outputs and integrates with engines like Unity or Godot.

Game Developmentbackendintegrations

This week in AI coding

Five minutes, every Monday - the tools, releases and tactics for developers.

unsubscribe anytime.