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add_get_right_vector_node

Adds a Blueprint node that retrieves the right vector of an actor.

Instructions

Add a 'Get Actor Right Vector' node.

Ch.14: Returns normalized right direction vector of the actor. Multiply by -1 to get the left vector.

Args: blueprint_name: Blueprint name node_position: Optional [X, Y] graph position

KB: see knowledge_base/26_CHAOS_PHYSICS_AND_DESTRUCTION.md#overview Example: add_get_right_vector_node(blueprint_name="/Game/MCP_Test/BP_Example")

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
node_positionNo
blueprint_nameYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.0.0

TDQS

A3.7/5.0
Behavior3/5

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

No annotations are present, so the description carries the behavioral disclosure burden. It clearly communicates the operation and the node's output behavior, including the normalization and left-vector transformation. However, it does not address graph-mutation consequences, duplicate-node behavior, or failure modes for invalid blueprint_name inputs, which leaves some behavioral ambiguity.

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 compact and front-loaded with the core purpose, followed by a concise example and knowledge-base reference. The Args block partly duplicates schema field names, but given the lack of schema descriptions, it is justified and not wasteful.

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?

For a simple two-parameter node-adding tool, this is largely sufficient: it explains what the node does, describes parameters, provides a concrete invocation example, and points to relevant documentation. Since an output schema exists, return-value detail is not a major gap; the main missing piece is explicit sibling routing and side-effect caveats.

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 0%, so the inline Args block provides the only parameter guidance. It usefully marks node_position as an optional [X, Y] graph position and the example demonstrates a valid blueprint path. Still, blueprint_name is essentially restated as 'Blueprint name', and coordinate units or default placement behavior for node_position are not explained.

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 and resource: it adds a 'Get Actor Right Vector' node and explains what that node returns (normalized right direction vector). The mention of negating to get the left vector makes the resource unambiguous and clearly differentiates it from sibling vector-node tools like add_get_forward_vector_node.

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 when to use it—when a right-vector node is needed—and even provides a left-vector usage tip. However, it does not explicitly state when not to use it or name sibling alternatives such as add_get_forward_vector_node or add_get_up_vector_node, so the agent must infer selection from the name and semantics.

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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