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Create visual system

create_visual_system

Turn natural-language descriptions into TouchDesigner visual systems, classifying intent and building self-contained node networks with automatic verification and preview.

Instructions

Create a complete visual system from a natural-language description. Classifies intent (audio-reactive, particle, feedback, reaction-diffusion, landscape, generative) and delegates to the matching Layer-1 builder (or a tag-matched recipe), creating a self-contained COMP under parent_path, then verifies and previews it. Use plan_visual instead for a dry run that reports which tool/recipe would be chosen without building anything. Returns a note on how the description was interpreted plus the underlying builder's result (created nodes, exposed controls, and a preview image).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
resolutionNoAdvisory target resolution. Recorded in the build note; the sub-builders use their own internal sizes and do not enforce this per-node.1080p
target_fpsNoAdvisory target frame rate (informational only — TD's real cook rate is a project-level setting, not set here).
descriptionYesNatural-language description of the visual system.
parent_pathNoParent COMP path the generated visual-system container is created inside./project1
Behavior5/5

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

Beyond the annotations, the description discloses the full behavioral pipeline: classifies intent, delegates to a builder/tag-matched recipe, creates a self-contained COMP under parent_path, verifies, previews, and returns a note plus the builder's result. This is rich context well beyond the basic readOnly/destructive hints and does not contradict annotations.

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 well-structured and front-loaded with the core action, followed by process details and a clear alternative reference. Every sentence earns its place, and the classification list adds useful specificity without redundancy.

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 complex orchestration tool with a rich schema and no output schema, the description adequately covers input interpretation, side effects, verification, preview, return values, and the main alternative. It could mention failure behavior or more details on the preview, but overall it is sufficiently complete for selection and invocation.

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 coverage is 100%, so the baseline is 3. The description adds only minimal parameter context beyond the schema, such as mentioning parent_path in the creation flow; it does not add new semantic details for resolution, frame rate, or description beyond what the schema already explains.

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 the tool creates a complete visual system from a natural-language description, with specific verbs and a defined resource. It distinguishes itself from siblings by naming classifier categories (audio-reactive, particle, etc.) and by delegating to Layer-1 builders or recipes, and from plan_visual by explicitly marking the difference.

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?

Explicit guidance is given: use this tool to actually build a visual system, and 'Use plan_visual instead for a dry run that reports which tool/recipe would be chosen without building anything.' This clearly communicates when to use this tool versus a key alternative.

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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