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add_anim_transform_curve

Add a transform curve to a UAnimSequence to store location, rotation, and scale keys, with save success and error reporting via the data controller.

Instructions

Add a transform curve (RCT_Transform) to a UAnimSequence via the data controller. A failed save makes success false, with saved=false and save_error.

Returns: { anim_sequence_path, curve_name, num_transform_curves, num_keys, keys_set, success, saved, save_error }

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
keysNoJSON array of {time, location:[x,y,z], rotation:[pitch,yaw,roll], scale:[x,y,z]} objects
curve_nameYesName of the transform curve to add.
anim_sequence_pathYesObject path of the UAnimSequence.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.1.0

TDQS

A3.7/5.0
Behavior4/5

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

Annotations already cover the safety profile (readOnly=false, destructive=false, idempotent=false). The description adds non-obvious behavioral context: that the operation can partially succeed, and a failed save surfaces as success=false with saved=false and save_error. That partial-success/failure semantics is genuinely useful beyond what the annotations provide.

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?

Purpose is front-loaded in the first clause, followed by failure semantics and a return-field list. Dense but every sentence earns its place given the absence of an output schema; the Returns enumeration is the only mildly verbose element.

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 appropriately enumerates the return fields and explains the save-failure outcome, and all parameters are covered by the schema. It is complete enough to invoke and interpret correctly, though it omits any hint about when this tool is the right choice versus sibling curve tools.

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 100%, so all three parameters (keys, curve_name, anim_sequence_path) are already documented in the schema, including the key object shape. The description adds no syntax or format detail beyond the schema, so the baseline 3 applies.

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 ('Add'), the exact resource ('transform curve (RCT_Transform)'), and the target container ('UAnimSequence'), distinguishing it from siblings like add_anim_float_curve and add_anim_curve_name. An agent can identify the operation without opening the schema.

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?

The description says how it executes ('via the data controller') but never states when to choose this over add_anim_float_curve or add_anim_curve_name, nor any prerequisites or exclusions. No when-to-use guidance is present.

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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