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aadeshrao123

Unreal-MCP

by aadeshrao123

list_niagara_available_parameters

List Niagara parameters for map pin binding, including engine, particles, user, and module variables, with optional filtering by namespace or system path.

Instructions

List parameters that can be bound to a Map Get / Map Set pin.

Returns well-known Engine.* parameters and Particles.* attributes unconditionally. When system_path + module_name are supplied, also adds:

  • User.* parameters from the system's exposed parameter collection

  • Rapid-iteration parameters from every emitter script

  • The target scratch pad module's own script graph variables (Module.* / Input.* / Transient.*)

Args: filter: Optional case-insensitive substring filter on parameter name namespace: "all" (default), "engine", "particles", "user", "module", "input", "transient", "rapid_iteration" max_results: Cap on returned entries (default 500) system_path: Optional system path to pull per-emitter + user params module_name: Optional scratch pad module to pull script-local params

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
filterNo
namespaceNoall
max_resultsNo
module_nameNo
system_pathNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior4/5

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

No annotations provided, so description carries full burden. It details unconditional vs conditional results, namespace filter, and parameter effects. Could mention pagination or error handling, but overall transparent.

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?

Well-structured with paragraphs and a list. Every sentence adds value, front-loads the primary purpose, and avoids unnecessary details. Efficient and clear.

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?

Given 5 optional parameters and an output schema, the description covers all relevant behavior, including conditional additions. No gaps in what needs to be explained for an agent to use it correctly.

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

Parameters5/5

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

Schema coverage is 0%, but the description includes an 'Args' section explaining each parameter's purpose, default, and effect (e.g., filter for substring, namespace for category). Fully compensates for missing schema descriptions.

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?

Clearly states the tool lists parameters that can be bound to Map Get/Map Set pins. Distinguishes from sibling tools like get_niagara_module_inputs by focusing on binding and including all relevant parameter namespaces.

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?

Explains when to use (for parameter binding) and how the list changes based on optional parameters (system_path, module_name). Does not explicitly list alternatives or state when not to use, but context is clear.

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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