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touchbridge

by GaNotchVFX
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Python
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par_pulse

Pulse a momentary parameter in TouchDesigner by specifying the operator path and parameter name, with options for detail level and response format.

Instructions

Pulse a momentary parameter.

path (<class 'str'>): Operator path.

name (<class 'str'>): Parameter name.

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
nameYes
pathYes
detailNo
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

A3.5/5.0
Behavior2/5

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

There are no annotations, so the description carries the full burden of explaining side effects. 'Pulse a momentary parameter' indicates a transient trigger action but does not disclose whether it mutates state, whether the parameter must already exist, what happens to the current value, or what the response contains.

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 definition is compact and front-loaded with the primary action, followed by a clean parameter-by-parameter list. No filler or repeated schema information is included.

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

Completeness3/5

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

The tool is simple and all parameters are documented, but with no output schema and no annotations, the description does not explain the response shape or error/edge-case behavior. It is adequate for a straightforward call but not fully self-sufficient.

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

Parameters4/5

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

Schema description coverage is 0%, but the description compensates by defining all four parameters, including the accepted values for detail and response_format. The meanings are terse but actionable; the yaml default is noted as token-cheap, which helps an agent choose sensibly.

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 first sentence uses a specific verb ('Pulse') and a specific resource ('momentary parameter'), which clearly distinguishes it from sibling parameter tools like par_get, par_set, and par_set_expression. The action described is not present in any sibling tool name.

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 gives no guidance about when to choose this tool over alternatives, or when it should not be used. Although the purpose implies a momentary-trigger use case, there are no exclusions or comparisons to par_set or other parameter tools.

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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