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Create YOLO ONNX tracker scaffold

create_yolo_onnx_tracker

Builds a TouchDesigner YOLO tracking scaffold with input source, detection DAT, stable tracks CHOP, annotated TOP, and configurable backend (WebSocket, ONNX, NDI, file watch).

Instructions

Build a deterministic TouchDesigner scaffold for YOLO-style object tracking. Creates source input, backend receiver placeholder, detections DAT, stable tracks_out CHOP channels, annotated_out TOP, and setup notes. Live detection requires an external detector or validated TouchDesigner Python ONNX runtime.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
nameNoContainer name for the tracker scaffold under parent_path.yolo_onnx_tracker
activeNoStart live receiver operators active. Default is off until validation.
backendNoDetection transport or runtime scaffold to build.external_websocket
model_pathNoONNX model path documented by onnx_script mode.
server_urlNoExternal WebSocket detector URL used by external_websocket mode.ws://127.0.0.1:8766
max_objectsNoMaximum tracked object slots exposed as stable CHOP channels.
parent_pathNoParent COMP that will receive the YOLO/ONNX tracker container./project1
class_filterNoOptional class names the external detector or ONNX postprocess should keep.
input_top_pathNoOptional source TOP path pulled into the container through a Select TOP.
confidence_thresholdNoMinimum detection confidence expected from the detector or postprocess.
Behavior4/5

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

While annotations indicate readOnlyHint=false and destructiveHint=false, the description adds significant behavioral context beyond those flags. It states the scaffold is 'deterministic', lists the exact network nodes it creates, and discloses the limitation that live detection depends on external components. This provides transparency about what the tool actually does and its operational requirements.

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 compact and efficient: a direct opening sentence, a concise list of created components, and a final sentence covering the live detection requirement. No filler or redundancy. Every sentence contributes useful information.

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?

For a tool with 10 parameters, all fully documented in the schema, and with annotations covering read/destructive hints, the description provides a solid overview of the build output and the key operational prerequisite. It doesn't explain what 'deterministic' means in practice or detail the scaffold's default state, but the essentials are covered. It is complete enough for an agent to understand the tool's role and limitations.

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 the baseline is 3. The description mentions outputs like 'source input' and 'backend receiver placeholder' that map to parameters (input_top_path, backend), but it doesn't explain parameter values, defaults, or usage beyond what the schema already documents. All parameter semantics are adequately handled by the schema; the description adds no additional parameter-level meaning.

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 a specific verb ('Build'/'Creates') and a specific resource ('deterministic TouchDesigner scaffold for YOLO-style object tracking'). It enumerates the key created components (source input, backend receiver placeholder, detections DAT, stable tracks_out CHOP channels, annotated_out TOP, setup notes), which distinguishes it from generic create_* siblings. The purpose is unambiguous and differentiated.

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 gives clear context that this tool is for building a YOLO/ONNX tracker scaffold and includes an important when-not condition: 'Live detection requires an external detector or validated TouchDesigner Python ONNX runtime.' This implies the scaffold alone isn't sufficient for live detection, providing a practical boundary. It does not explicitly name alternative tools, but the context is sufficient for selection.

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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