Skip to main content
Glama

create_basic_castle

Create a basic castle in Unreal Engine from primitive shapes, with customizable layout, size, palette, and rotation.

Instructions

Create a sample castle workflow from primitive shapes.

Parameters:

  • kwargs: Optional key=value pairs or JSON object Supported parameters:

    • prefix: Actor label prefix, default Castle

    • origin: x,y,z base location

    • stone_color: r,g,b or r,g,b,a color for stone elements

    • roof_color: r,g,b or r,g,b,a color for roof elements

  • layout: classic, courtyard, bastion, or longhall

  • size: compact, standard, or grand

  • palette: granite, sandstone, moss, or obsidian

  • yaw: rotate the layout around the origin in degrees

  • replace_existing: true/false, default true

    • dry_run: true/false, default false

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
kwargsNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior2/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are provided, so the description must disclose behavioral traits. It mentions parameters like 'replace_existing' and 'dry_run' but does not explain their implications (e.g., whether the tool overwrites existing actors or requires specific permissions). The behavioral impact is unclear.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness3/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single block listing parameters. It efficiently states the purpose but lacks clear structuring (e.g., bullet points or sections). It is adequate but not optimally concise.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness2/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Despite having an output schema (not shown), the description is incomplete. It doesn't mention prerequisites, level context, or how the tool fits with siblings like 'reset_basic_castle'. The parameter details are helpful but insufficient for full context.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 0% (only 'kwargs' with no description), so the description compensates by listing supported sub-parameters (prefix, origin, stone_color, etc.). However, it does not specify the exact format for 'kwargs' (e.g., JSON object or key=value pairs), which limits clarity.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool's action: 'Create a sample castle workflow from primitive shapes.' This is a specific verb and resource, distinguishing it from siblings like 'reset_basic_castle' or 'verify_basic_castle'.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides no guidance on when to use this tool versus alternatives like 'spawn_actor_from_blueprint' or 'modify_actor'. No explicit usage context or exclusions are given.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Install Server

Other Tools

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/runeape-sats/unreal-mcp'

If you have feedback or need assistance with the MCP directory API, please join our Discord server