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set_niagara_emitter_max_gpu_particles

DestructiveIdempotent

Limit the number of GPU particles spawned per frame by a Niagara emitter to manage performance in Unreal Engine.

Instructions

Set the MaxGPUParticlesSpawnPerFrame override on a Niagara emitter (only effective when SimTarget is GPUComputeSim).

Returns: { system_path: string, emitter_name: string, sim_target: string, max_gpu_particles: int, effective_for_current_sim: bool, applied: bool, saved: bool, save_error?: string }

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
system_pathYesAsset path of the Niagara System.
emitter_nameYesName of the emitter handle.
max_gpu_particlesNoNon-negative integer

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changedv1.2.0
    • changedInput schema / required
      Previous value: -[
-  "emitter_name"
-]New value: +[
+  "system_path",
+  "emitter_name"
+]
  2. First observedv1.1.0

TDQS

A4.2/5.0
Behavior4/5

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

Annotations already declare the write/destructive/idempotent profile, so the description isn't obligated to restate safety. It adds non-obvious behavior: the override only takes effect under GPUComputeSim, and the returned applied/saved/save_error fields reveal that the asset may be persisted and persistence can fail.

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

Conciseness4/5

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

Two sentences with the action and its precondition front-loaded, followed by the return shape. The return-field list is somewhat long but earns its place because no output schema exists.

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, the inline return shape plus the sim-target effectiveness condition gives an agent everything needed to call the tool and interpret the result, including the failure signal via save_error.

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

Parameters3/5

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

Schema description coverage is 100% for all three parameters, so the schema already documents them. The description names the underlying property but adds no format, range, or default detail beyond what the schema provides, so baseline 3 applies.

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 specific verb+resource: setting the MaxGPUParticlesSpawnPerFrame override on a named Niagara emitter, with the exact asset/emitter pairing made clear. It also differs cleanly from nearby Niagara siblings like set_niagara_emitter_sim_target or set_niagara_emitter_allocation_mode without needing their schemas.

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?

The parenthetical 'only effective when SimTarget is GPUComputeSim' gives a clear precondition for correct invocation. It stops short of naming an alternative tool or an explicit when-not, but the applicability gate is genuinely useful context.

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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