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list_niagara_renderer_classes

Read-onlyIdempotent

Enumerate every concrete UNiagaraRendererProperties subclass, skipping abstract classes, to discover valid renderer_class strings for add_niagara_renderer.

Instructions

Enumerate every concrete UNiagaraRendererProperties subclass registered in this process via TObjectIterator. Skips Abstract (those are base classes only). Used to discover what renderer_class strings are valid for add_niagara_renderer.

Returns: { count: int, classes: [{class_name, class_path, display_name, abstract, class_flags}] }

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.1.0

TDQS

A4.5/5.0
Behavior4/5

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

Annotations already declare the safe read-only, idempotent, non-destructive profile, and the description adds real behavior beyond that: enumeration is via TObjectIterator and Abstract base classes are filtered out. It also discloses the return payload shape, though it doesn't mention ordering or runtime-dependency caveats.

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

Conciseness5/5

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

Three tightly packed sentences, front-loaded with the core action and rationale, then a compact return-type sketch. No filler text earns removal.

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

Completeness5/5

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

With no output schema present, the description compensates by spelling out the return object shape ({count, classes[]} with its fields), and combined with the annotations this is everything an agent needs to invoke and interpret the tool.

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?

The tool takes zero parameters, so there is no parameter semantics to explain and the baseline of 4 applies. The description correctly implies a no-argument, whole-process enumeration with no filtering options.

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?

States a precise verb+resource: enumerates concrete UNiagaraRendererProperties subclasses in the current process. It clearly distinguishes itself from siblings like list_niagara_data_interface_classes and list_niagara_modules by the specific class family it targets.

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

Usage Guidelines4/5

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

Explicitly names the downstream consumer ('valid renderer_class strings for add_niagara_renderer'), giving a clear when-to-use signal. It stops short of naming alternative listing tools or stating when this is not the right choice, so it falls just under full marks.

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

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