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add_bt_node

Add a single node to an existing Behavior Tree graph for incremental edits, supporting custom node types and properties.

Instructions

Add a single node to an existing Behavior Tree graph.

Use this for incremental edits — add one node at a time after the initial tree is built with build_behavior_tree.

Node type strings (case-insensitive): "Selector", "Sequence", "Wait", "MoveTo" or a full Blueprint class name/path for custom tasks.

Args: behavior_tree_name: Name of the existing BT asset node_type: Node type string (see above) parent_node_index: 0-based index in the graph Nodes array (skip root). -1 = attach directly to root. x: Graph X position (0 = auto) y: Graph Y position (0 = auto) properties: Dict of property name → string value for the node instance e.g. {"WaitTime": "3.0", "AcceptableRadius": "100.0"} decorators: List of {"type": "..."} objects for decorator sub-nodes services: List of {"type": "..."} objects for service sub-nodes

Returns: Dict with 'success', 'node_type', 'node_index'

KB: see knowledge_base/04_AI_SYSTEMS.md#overview Example: add_bt_node(behavior_tree_name="ExampleName", node_type="Example")

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
xNo
yNo
servicesNo
node_typeYes
decoratorsNo
propertiesNo
parent_node_indexNo
behavior_tree_nameYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.0.0

TDQS

A4.8/5.0
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 it does well by explaining parent_node_index semantics, -1 as root attachment, auto-placement when x/y are 0, and the return dict. It implies mutating behavior by saying 'add' but does not fully disclose edge cases such as invalid node types or failure behavior.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is structured into succinct sections: usage intent, valid node types, Args, Returns, KB pointer, and example. It is moderately long but every section adds actionable information, and the most important guidance is front-loaded.

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?

Given the complexity of 8 parameters, nested objects, and a behavior-tree-specific operation, the description covers the required parameters, optional parameters, return format, and points to knowledge_base/04_AI_SYSTEMS.md#overview for further context. Nothing critical is missing for selecting and invoking the tool.

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 is the only source of parameter meaning. It explains all 8 parameters beyond their schema types: accepted node_type strings, parent_node_index indexing, x/y auto values, properties as string-valued dict, and decorators/services as list objects. This fully compensates for the missing schema descriptions.

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 starts with a specific verb and resource: 'Add a single node to an existing Behavior Tree graph.' It clearly distinguishes itself from build_behavior_tree by framing it as the incremental follow-up tool, and the node_type list ('Selector', 'Sequence', 'Wait', 'MoveTo', or Blueprint class path) narrows the operation precisely.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

'Use this for incremental edits — add one node at a time after the initial tree is built with build_behavior_tree' explicitly names the alternative tool and the condition for using this one. This gives the agent a clear routing rule without needing to compare schemas.

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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