Skip to main content
Glama

Create Azure Kinect body bus

create_azure_kinect_body_bus

Create an Azure Kinect body/depth scaffold with TOP/CHOP placeholders, stream maps, and calibration notes for TouchDesigner.

Instructions

Create an Azure Kinect body/depth scaffold with Kinect Azure TOP/CHOP placeholders, stream maps, and calibration notes.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
nameNoGenerated baseCOMP name.azure_kinect_body_bus
activeNo
body_countNo
parent_pathNoParent COMP for the Azure Kinect scaffold./project1
device_indexNo
include_color_topNo
include_depth_topNo
Behavior3/5

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

Annotations indicate readOnlyHint=false and destructiveHint=false. The description adds that the scaffold includes placeholders, stream maps, and calibration notes, providing some context about what is created. However, it does not disclose prerequisites like device connection or potential side effects, so transparency is moderate.

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 a single, front-loaded sentence that communicates the tool's purpose and key output components without unnecessary words.

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

Completeness2/5

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

For a creation tool with 7 parameters and no output schema, the description is too brief. It mentions scaffold components but does not explain the impact of parameters, integration requirements, or how the scaffold is structured in the network. This leaves significant gaps for an agent deciding whether to use the tool.

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

Parameters1/5

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

Schema description coverage is only 29% (2/7 params described). The tool description does not explain any of the parameters such as body_count, device_index, include_color_top, or include_depth_top, nor does it relate them to the scaffold contents. Thus the description fails to compensate for the low schema coverage.

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 clearly states it creates an Azure Kinect body/depth scaffold with specific contents (TOP/CHOP placeholders, stream maps, calibration notes). This is a specific verb+resource and distinguishes it from other depth-sensor tools like create_realsense_depth_bus.

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

Usage Guidelines4/5

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

The description provides clear context that this tool is for creating an Azure Kinect body/depth scaffold, which implies when to use it. It does not mention alternatives or exclusions, but the purpose is specific enough to avoid ambiguity for an agent selecting this tool.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Install Server

Other Tools

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/Pantani/tdmcp'

If you have feedback or need assistance with the MCP directory API, please join our Discord server