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Map Blockout

Community
kevinpbuckley
map-blockout

Procedurally design an AAA-style open-world FPS map blockout (roads, POIs, fields, forests/treelines, railway/bridges) from a landscape, validate it through gated checks, and materialize it into engine geometry. Use when the user asks to block out or lay out an open-world/FPS map, place roads/POIs/forests/railways procedurally, or turn a blockout plan into splines, paint layers, foliage, and actors.

Overview

Publisherkevinpbuckley
RepositoryVibeUE
Skill namemap-blockout
Stars
735
Forks
161
Bundled files
5
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.

  • 5 bundled files

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

  • Open source

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

Installation

Install the Map Blockout 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/kevinpbuckley/VibeUE/tree/master/Content/Skills/map-blockout
  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/kevinpbuckley/VibeUE.git /tmp/VibeUE
mkdir -p .claude/skills
cp -r /tmp/VibeUE/Content/Skills/map-blockout .claude/skills/map-blockout
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Map Blockout 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 Map Blockout 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 Map Blockout 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.

🧠 Brains complement: IF an unreal-engine-skills-manager tool (external MCP) exists in this session, call it with {action: "load", skill: "levels-and-world-partition"} for UE domain knowledge on this topic — correct APIs, architecture, best practices — and treat it as the rubric for any review / "best practices" question. If no such tool is available (e.g. running under Claude Code or Codex without that MCP), skip this line entirely and proceed with this skill alone — do NOT attempt the call.

Procedural FPS Map Blockout Skill

Take a VibeUE-generated landscape (heightmap + paint layers) and turn it into a fully validated, AAA-style open-world FPS map blockout — roads, POIs, fields, forests/treelines, railway, bridges — then materialize the plan as real engine geometry. Quality benchmark is Arma / Squad.

The design pipeline is gated: every stage runs ordered pass/fail checks against the authoritative spec at docs/design/map-designer-spec.md. You may not advance until all checks PASS. On failure, fix the offending element and re-run the stage.

Sub-docs available

Skills load via the engine's AgentSkillToolset (ListSkills / GetSkills). To pull a sub-doc, request map-blockout/<section> through GetSkills. The sibling *.md files also sit next to this SKILL.md on disk and can be read directly.

Sub-docWhen to load
workflows.mdEnd-to-end run: export → stages 1–5 → final pass → materialize. Pick this first.
stage-rules.mdPer-stage CHECK list (what passes, what fails, how to fix). Mirrors the spec.
config-reference.mdFMapBlockoutConfig fields — coverage bands, road grid, POI targets, tuning knobs.
return-types.mdExact USTRUCT property names returned by every service method.
materialization.mdHow the plan becomes splines / paint / actors / foliage in the level.

Critical Rules

The gate is non-negotiable

Each stage's Gate.bAllPassed must be true before advancing. The orchestrator (run_full_pipeline) stops at the first failing gate and surfaces the failing check name + message in the returned struct. Inspect Gate.Checks to know what to repair.

Run Stage 0 first

run_full_pipeline_for_landscape is the one-call convenience. Otherwise:

  1. unreal.MapBlockoutService.export_landcover_grid(landscape_label, grid_n=120)
  2. Pass the result + config to run_full_pipeline

export_landcover_grid reads every paint layer on the source landscape plus the heightmap, returns a normalized grid in one native call — no PNG round-trip and no host-Python pre-processing step.

Map your paint layers to design categories

The spec assumes 4 logical categories: crop, soil, flood (water), forest. You must tell the service which layer names on the source landscape play each role:

python
cfg = unreal.MapBlockoutConfig()
cfg.layers.crop   = "Crop"     # name on the landscape
cfg.layers.flood  = "Water"
cfg.layers.forest = "Forest"
cfg.layers.soil   = "Soil"

Empty flood is allowed — water is derived from a low-elevation percentile of the heightmap.

Output folder is named after level_name

<Project>/Saved/MapBlockout/<level_name>/
  Stage1_Roads.png                                   <- cumulative snapshot
  Stage2_Roads_POIs.png
  Stage3_Roads_POIs_Fields.png
  Stage4_Roads_POIs_Fields_Foliage.png
  Stage5_Roads_POIs_Fields_Foliage_Rail.png
  CombinedFoliageAndMap.png                          <- final, with color key
  FoliageHeatMap.png                                 <- trees + fields + scrub
  MapHeatMap.png                                     <- roads + buildings + rail + bridges

All 8 files are required for delivery. The Final Pass refuses to ship if any upstream gate has unresolved failures.

Color chart is authoritative

Every rendered output uses the MapDesigner color chart (see stage-rules.md). Constants live in MapBlockoutImage::Colors::* (C++). Do not invent new colors — the heatmap + combined map are required deliverables and must match.

ElementColor
Main RoadsWhite
Dirt RoadsBrown
TreelinesLight Purple
ForestDark Purple
BuildingsLight Grey
BridgesOrange
RailwayDark Grey
POI BoundaryBright Green Circle
FieldsYellow
Underbrush / ScrubLight Blue

The Color Key must NOT cover the map

Top-right panel. If the panel rect intersects the map area, the stage fails its "Color Key" check. The renderer enforces this — but if you write a custom renderer, honor the rule.

Two-Phase Workflow

Phase 1 — design the plan (CPU, masks + polylines, no engine geometry):

python
import unreal
S = unreal.MapBlockoutService

cfg = unreal.MapBlockoutConfig()
cfg.level_name = "Verkhova"
cfg.layers.crop, cfg.layers.forest = "Crop", "Forest"
cfg.layers.flood = "Water"

result = S.run_full_pipeline_for_landscape("Landscape1", cfg)
if not result.success:
    # Inspect result.final_state.<stage>.gate.checks for the failing entry
    print(result.error_message)
else:
    print("Wrote:", result.output_files)

Phase 2 — materialize into the level:

python
S.materialize_roads_as_splines(result.final_state.stage1_roads, "Landscape1")
S.materialize_fields_as_paint(result.final_state.stage3_fields, "Landscape1", "Crop")
S.materialize_pois_as_actors(result.final_state.stage2_pois, "/MapBlockout/POIs/")
S.materialize_forest_as_foliage(result.final_state.stage4_foliage,
    "/Game/Foliage/FT_Forest", "/Game/Foliage/FT_Treeline", "/Game/Foliage/FT_Scrub")
S.materialize_railway_and_bridges(result.final_state.stage5_railway, "Landscape1")

Status

Fully implemented — every stage (Roads, POIs, Fields, Foliage, Railway/Bridges), the Final Pass, the renderers, and the materializers are live in C++. The full pipeline has been verified end-to-end: all stage gates plus the Final Pass pass, producing the eight deliverable PNGs.

Related Skills

TaskSkills to Load
Sculpt / paint / create the source landscape firstlandscape
Pull a real-world heightmap before blockoutterrain-data
Materialize foliage scatter (used by MaterializeForestAsFoliage)foliage
Place water (rivers, lakes) preciselyterrain-data (Mapbox) or MapBlockoutService.extract_river_centerlines

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 Map Blockout AI skill do?

Procedurally design an AAA-style open-world FPS map blockout (roads, POIs, fields, forests/treelines, railway/bridges) from a landscape, validate it through gated checks, and materialize it into engine geometry. Use when the user asks to block out or lay out an open-world/FPS map, place roads/POIs/forests/railways procedurally, or turn a blockout plan into splines, paint layers, foliage, and actors.

Why use Map Blockout on TypingMind?

Because you install it once and use it with any model. Map Blockout 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 Map Blockout in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/kevinpbuckley/VibeUE/tree/master/Content/Skills/map-blockout. 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 Map Blockout?

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 Map Blockout?

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

Is the Map Blockout AI skill free?

Yes. It is published on GitHub by kevinpbuckley 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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