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Flux-Point-Studios

Unreal Engine MCP Server

workflow

Run composite Unreal Engine operations: audit level performance, analyze blueprint health, populate scenes with actors, and smoke-test levels.

Instructions

Composite workflow tool that chains multiple operations into high-level workflows. Actions: level_performance_audit (comprehensive level analysis with scene stats, actor summary, perf capture, lighting status, and recommendations), blueprint_health_check (analyze a blueprint for compilation issues, graph complexity, and general health), scene_populate (fill a bounding box with randomized static mesh actors), quick_test (smoke test the current level: info, actors, PIE, viewport capture).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
countNo[scene_populate] Number of actors to place (default: 10, max: 500).
actionYesThe workflow to execute. level_performance_audit: comprehensive level audit. blueprint_health_check: inspect and compile a blueprint. scene_populate: fill an area with actors. quick_test: smoke test the current level.
extentNo[scene_populate] Half-extents [x, y, z] of the bounding box.
originNo[scene_populate] Center point [x, y, z] of the area to populate.
asset_pathsNo[scene_populate] Array of static mesh asset paths to use (cycled through).
blueprint_nameNo[blueprint_health_check] Name of the blueprint to analyze.
random_rotationNo[scene_populate] Apply random Y-axis rotation to placed actors (default: true).
random_scale_rangeNo[scene_populate] Uniform scale range [min, max] for random scaling (default: [0.8, 1.2]).
Behavior3/5

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

Annotations are all false, leaving the description to carry the burden. It partially discloses behavior by naming actions (e.g., scene_populate creates actors, quick_test runs a smoke test) and listing outputs. However, it omits side effects, reversibility, permissions, or transactional behavior for a tool that can chain multiple operations, leaving destructive implications unclear.

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 description is well-structured with a clear lead-in and enumerated actions, each earning its place. It is somewhat redundant with the schema's action descriptions but remains compact and scannable.

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

Completeness3/5

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

With 8 parameters, no output schema, and no annotations, the description gives the core action catalog but lacks guidance on prerequisites, how to construct composite workflows, and expected return formats. It's sufficient for understanding individual actions but incomplete for fully driving the tool.

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 coverage is 100%, so the baseline is 3. The description adds little parameter-level meaning beyond what the schema already provides; its action summaries align with the enum but don't explain parameter syntax or constraints beyond the 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 clearly states the tool is a composite workflow tool that chains operations, and enumerates four distinct actions with concise summaries. It differentiates from sibling tools by emphasizing high-level composition, though it doesn't explicitly contrast with specific siblings.

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

Usage Guidelines3/5

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

The description implies usage for high-level chained workflows but provides no explicit when-to-use guidance, exclusions, or preferred alternatives. The phrase 'chains multiple operations' hints at composition, but the agent isn't told when to choose this over sibling tools like manage_level_structure or validate.

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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