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get_memory_usage

Read-onlyIdempotent

Retrieve detailed memory usage for processes, scenes, GPU, and system to monitor performance and diagnose resource bottlenecks in Unreal Engine.

Instructions

Retrieves detailed memory usage including process, scene, GPU, and system information.

Returns: { process_memory: {used_physical_memory_mb, peak_used_physical_memory_mb, available_physical_memory_mb, total_physical_memory_mb, used_virtual_memory_mb, peak_used_virtual_memory_mb}, scene_memory: {actor_count, component_count, static_mesh_count, material_count (distinct), material_slot_count, texture_count (distinct textures the scene's materials use), resident_texture_count (every UTexture2D in memory)}, gpu_memory: {gpu_memory_available, gpu_memory_status, rhi_name, dedicated_video_memory_mb?, shared_system_memory_mb?, total_graphics_memory_mb?, streaming_texture_memory_mb, non_streaming_texture_memory_mb}, system_info: {platform, cpu_brand, cpu_cores, cpu_threads} }

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.1.0

TDQS

A3.6/5.0
Behavior4/5

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

Annotations already declare readOnlyHint, idempotentHint, and openWorldHint=false, so safety and side-effect questions are covered. The description goes further by disclosing the exact payload anatomy (which counters are 'distinct' counts, what resident_texture_count means, which GPU fields are optional), which is substantive behavioral context beyond the annotations.

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?

The purpose sentence is front-loaded and short; the remaining bulk is the inline return-shape dump. That dump is dense but earns its place because no output schema is declared, and the parenthetical clarifications on ambiguous counters add real value rather than padding.

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

Completeness4/5

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

With no output schema, the description fully compensates by spelling out the four return sections and their fields, so an agent knows exactly what it will get. It does not state scope conditions (editor vs PIE context, whether values are snapshot-in-time), which would be the only remaining useful addition.

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 the schema has nothing to document and the baseline is 4. Nothing in the description contradicts or needs to compensate for the empty input schema.

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

Purpose4/5

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

The description states a specific verb and resource ('Retrieves detailed memory usage') and enumerates the four scopes covered: process, scene, GPU, and system. It is clear what the tool does, but it never distinguishes itself from the overlapping sibling get_asset_memory_usage (nor from broader stats tools like get_engine_stats), which leaves sibling disambiguation to the agent.

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?

There is no explicit when-to-use or when-not-to-use guidance, and no alternative tool is named. Given that get_asset_memory_usage sits right next to it in the catalog, the absence of any routing hint (engine/process memory vs per-asset memory) is a real gap, though the read-only nature makes intent implicitly safe.

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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