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add_anim_graph_parameter

Add a typed value parameter to an O3DE anim graph, setting its default, optional range, description, and group for animation logic.

Instructions

Add a value parameter to an anim graph.

Returns the parameter object as get_anim_graph emits it. The gem checks each value against the type; min and max are only valid for ranged types (Float, Int, Vector2/3/4, Color, Rotation).

Args: anim_graph_id: Graph id (number or digit string). name: Parameter name. parameter_type: Float (a FloatSlider), FloatSpinner, Int (an IntSlider), IntSpinner, Bool, String, Tag, Vector2, Vector3, Vector3Gizmo, Vector4, Color, Rotation, or the full class name. default: Default value: a number, bool, string, or a list of numbers for vector, color and rotation types. min: Range minimum (ranged types only). max: Range maximum (ranged types only). description: Optional description. group: Group to put the parameter in; created when missing.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
maxNo
minNo
nameYes
groupNo
defaultNo
descriptionNo
anim_graph_idYes
parameter_typeYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. Addedv0.6.0

TDQS

A3.7/5.0
Behavior4/5

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

With no annotations, the description carries the full burden and does well: it discloses that the gem type-checks each value, that min/max are only valid for ranged types, that group is auto-created when missing, and what the return value resembles. It omits failure behavior when validation fails and any permission/session requirements.

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?

Well front-loaded: purpose first, then return/validation notes, then a structured Args block. Every line carries information, though the prose is slightly more verbose than strictly needed.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a mutation tool with zero annotation coverage, the description documents inputs thoroughly and can lean on the existing output schema for return shape. However it says nothing about permissions/session state, whether the operation is destructive or reversible, or what happens when type validation fails.

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, and it does: every one of the 8 parameters is documented, including the full list of accepted parameter_type values (effectively an enum absent from the schema), value formats for default per type, and the ranged-type constraint on min/max.

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?

The opening sentence states a specific verb and resource ('Add a value parameter to an anim graph'), which cleanly separates it from the sibling remove_anim_graph_parameter and the various set_anim_graph_* tools. It doesn't explicitly name a sibling, but the add/remove polarity is unambiguous.

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?

There is no when-to-use or when-not-to-use guidance, no prerequisites (does the graph need to be loaded/created first?), and no routing to alternatives. The Args section explains fields, not usage context.

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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