Skip to main content
Glama
GaNotchVFX

touchbridge

by GaNotchVFX
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Local

data_dat_write

Write text, append rows, or clear TouchDesigner DAT operators at a specified path. Choose detailed or summary responses in YAML or JSON.

Instructions

Write text / append a row / clear a DAT.

path (<class 'str'>): DAT operator path.

text (str | None): Replace full text content.

appendRow (list[typing.Any]): Append a row to a table DAT.

clear (bool | None): Clear before writing.

detail (str | None): full (default) | summary (long lists cut to 25 + count) | minimal (top-level scalars only).

response_format (str | None): yaml (default, token-cheap) | json.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
pathYes
textNo
clearNo
detailNo
appendRowNo
response_formatNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed2 schema fields changedv0.4.0
    • addedInput schema / properties / detail
      Added value: +{
+  "anyOf": [
+    {
+      "type": "string"
+    },
+    {
+      "type": "null"
+    }
+  ],
+  "default": null,
+  "title": "Detail"
+}
    • addedInput schema / properties / response_format
      Added value: +{
+  "anyOf": [
+    {
+      "type": "string"
+    },
+    {
+      "type": "null"
+    }
+  ],
+  "default": null,
+  "title": "Response Format"
+}
  2. First observedv0.2.0

TDQS

A4.1/5.0
Behavior4/5

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

With no annotations provided, the description carries the full behavioral burden. It explicitly discloses the mutating effects: replacing full text, appending a row, and clearing before writing. It also explains response shaping through detail and response_format, giving an agent a clear picture of side effects and output style.

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 summary line is compact and front-loaded, and each parameter gets a single focused line. There is no filler or repeated schema information; every sentence adds meaning.

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 six-parameter tool with no output schema or annotations, the description covers the core operations, parameter semantics, and output format. It lacks only minor context such as error behavior or permissions, but an agent has enough to call the tool and interpret its response.

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?

Although the schema has no descriptions for its properties, the tool description documents every parameter with types and allowed values. It explains path, text replacement, appendRow, clear, detail levels, and response_format defaults, fully compensating for the 0% 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 begins with a clear verb and resource: 'Write text / append a row / clear a DAT.' It names the specific operations and target, making the tool's function obvious. The coarse-grained name is reinforced by concrete actions rather than restating the title.

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

Usage Guidelines2/5

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

The description says what the tool does but gives no guidance about when to prefer it over sibling tools such as data_dat, data_chop, data_top, or data_sop. There are no exclusions, prerequisites, or alternative-routing hints.

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

Deploy Server

Other Tools