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Create data visualization

create_data_visualization

Build a data-driven visualization in TouchDesigner by generating a container with data source, conversion operators, scale, and chart. Wire your data into the created 'data' node.

Instructions

Build a data-driven visualization: a data source feeds a CHOP that drives a chart TOP. Creates a new baseCOMP under parent_path holding a 'data' source operator (seeded with placeholder values), a DAT-to-CHOP / CHOP-to-TOP conversion, a Scale level, the chart visual, and a Null output. Wire your real data into the created 'data' node. Returns a summary plus a JSON block with the container path, created node paths, the output path, exposed controls, any node errors, warnings (including a reminder to wire real data), and an inline preview image.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
data_sourceNoKind of source operator to create: 'table' (Table DAT, pre-seeded with sample values), 'file' (File In DAT), or 'chop' (Constant CHOP). Wire your real data into the created 'data' node afterward.table
chart_styleNoVisual style. 'bars' renders a GLSL bar chart; 'graph' and 'points' currently render the data as a texture strip and add a warning that richer plotting needs customization.bars
expose_controlsNoWhen true (default), expose a live 'Scale' knob that amplifies the data values feeding the chart.
parent_pathNoParent network where the visualization container is created (default '/project1')./project1
Behavior5/5

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

Annotations are minimal (readOnlyHint=false, destructiveHint=false, openWorldHint=true). The description adds rich behavioral detail: it creates nodes under parent_path, seeds placeholder data, returns a summary with paths, errors, warnings, and preview. It warns about needing to wire real data and notes that graph/points styles render as texture strips with customization warnings.

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?

The description is front-loaded with a concise summary, then details the created nodes, usage tip, and return info. It is efficient with no wasted words, though slightly longer than strictly necessary.

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?

No output schema exists, but the description explicitly lists return values. It covers what the tool creates, the pipeline, a usage reminder, and return structure. Minor gaps: doesn't specify behavior if parent_path is invalid or naming conflicts, but overall complete for a creation tool.

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 baseline is 3. The description adds architectural context (pipeline flow) but does not significantly expand on parameter-specific semantics beyond what the schema already provides (e.g., chart_style options are only mentioned in schema). Value added is marginal.

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 builds a data-driven visualization with a specific node pipeline (data source, CHOP, chart TOP). It distinguishes from sibling create_* tools by specifying the data-visualization use case and the exact components created.

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

Usage Guidelines3/5

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

The description implies when to use the tool (when building a data-driven chart) but does not provide explicit when-not-to-use guidance or mention alternatives among the many sibling creation tools. The context is clear but lacks exclusionary advice.

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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