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get_anim_curve_data

Read-onlyIdempotent

Read one UAnimSequence curve without altering it: retrieve float curve keys as time/value pairs or transform curve flags and summed key counts; returns found=false if the curve is missing.

Instructions

Read one curve of a UAnimSequence without changing it: for a float curve its flags, num_keys and keys as time/value pairs; for a transform curve only flags and a summed num_keys. found=false (still a success) when the curve does not exist.

Returns: { anim_sequence_path, curve_name, curve_type, found, num_keys, flags, time, value, keys }

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
curve_nameYesName of the curve to read
curve_typeNoCurve type to target: float (default) or transform
anim_sequence_pathYesFull asset path to the UAnimSequence

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.1.0

TDQS

A3.9/5.0
Behavior4/5

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

Annotations already declare readOnly/idempotent/non-destructive, so the bar is lower, but the description adds real behavioral detail: distinct return shapes for float vs transform curves and the important found=false-is-still-success case. This is context structured fields do not carry.

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?

Front-loaded with the verb and resource, then the curve-type behavior, then the error case, with a compact return object listing. Every sentence earns its place; the Returns line slightly overlaps the prose but aids the no-output-schema case.

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?

With no output schema, the description carries the return-value burden and does so fully by enumerating the returned fields and explaining the found=false success case. Nothing essential for correct invocation is missing.

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

Parameters4/5

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

Schema coverage is 100% so baseline is 3, and the description adds meaning above that by explaining the consequence of curve_type: float yields flags/num_keys/keys as time-value pairs while transform yields only flags and a summed num_keys.

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?

States a specific verb (read) plus a precise resource (one curve of a UAnimSequence) and further qualifies the behavior by curve type. An agent can distinguish it from curve-listing or mutation siblings, though no sibling is named explicitly.

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 'without changing it' phrasing and the found=false note imply this is a safe read and how a missing curve is reported, which guides usage. However, it never says when to prefer this over get_anim_curve_names or evaluate_curve_at_time, so no explicit alternative routing is provided.

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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