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aadeshrao123

Unreal-MCP

by aadeshrao123

get_niagara_graph_nodes

Introspect Niagara graph nodes via three resolver modes: scratch pad module, emitter stack, or standalone script. Filter by node type or name for targeted inspection.

Instructions

Introspect every node inside a Niagara graph.

Three resolver modes:

  1. system_path + module_name — scratch pad module graph

  2. system_path + emitter_name + script_usage — EMITTER STACK GRAPH (emitter_spawn|emitter_update|particle_spawn|particle_update), where stack modules appear as NiagaraNodeFunctionCall nodes

  3. script_path — standalone UNiagaraScript asset

Args: system_path: Niagara System asset path module_name: Scratch pad module name (mode 1) emitter_name + script_usage: Emitter stack graph (mode 2) script_path: Standalone script asset (mode 3) verbosity: "summary" | "connections" (default) | "full" type_filter: Case-insensitive substring on short class name name_filter: Case-insensitive substring on node title

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
verbosityNoconnections
module_nameNo
name_filterNo
script_pathNo
system_pathNo
type_filterNo
emitter_nameNo
script_usageNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior3/5

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

With no annotations, the description carries full burden. It explains the resolver modes and filter behaviors (verbosity, type_filter, name_filter) but does not explicitly state that the tool is read-only or non-destructive. The output schema is assumed to handle return format, but some gaps remain.

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 lead sentence followed by a clear list of parameters and modes. It is slightly verbose but every sentence adds value; it could be more concise but remains efficient.

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?

Given the tool's complexity (8 parameters, 3 modes) and lack of schema descriptions, the description is quite complete. It covers modes, parameters, filters, and offers examples. It does not mention prerequisites or side effects, but the output schema presumably covers return values.

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 description coverage is 0%, so the description must compensate. It does so excellently by explaining all 8 parameters in a structured manner, including the three modes, verbosity options, and filter substring matching. This adds significant meaning beyond the bare schema.

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?

The description clearly states the tool's purpose: 'Introspect every node inside a Niagara graph.' It distinguishes from sibling tools like get_niagara_node_info by indicating it returns all nodes and specifies three resolver modes for different contexts (scratch pad, emitter stack, standalone script).

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 description defines three modes of use, each with specific parameter combinations, providing clear context. However, it does not explicitly exclude alternatives or state when not to use this tool, though the differentiation from other Niagara introspection tools is implied.

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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