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touchbridge

by GaNotchVFX
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Python
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script_class_list

List TouchDesigner td module classes with optional case-insensitive substring filter and detail levels, returned as YAML or JSON.

Instructions

List names in the td module (optional substring filter).

pattern (str | None): Case-insensitive substring.

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
detailNo
patternNo
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

A3.9/5.0
Behavior3/5

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

No annotations are provided, so the description must carry the full burden. It discloses behavior for the detail parameter (full/summary/minimal with cutoff behavior) and response_format (yaml is token-cheap). However, it does not state side effects (though listing is likely read-only) or describe the exact return structure. It also doesn't mention what happens if pattern matches nothing. These gaps lower the score.

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 three lines, each parameter explained inline. It is front-loaded with the core purpose and uses minimal words. Every sentence adds value, with no fluff.

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 simple listing tool with no output schema, the description covers the essential purpose and parameter behaviors. It could benefit from specifying the return format (e.g., a list of names or objects) and handling of empty results, but these are minor gaps given the tool's simplicity. The detail levels already convey what the output will contain.

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?

Schema description coverage is 0%, so the description must compensate. It fully explains all three parameters: pattern (case-insensitive substring), detail (allowed values with meanings), and response_format (yaml/json with note about token cost). This adds significant meaning beyond the schema, which only shows types and defaults.

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 states 'List names in the td module' which is a specific verb and resource. It clearly distinguishes from siblings like script_class_detail (which likely shows details) and script_module_help (help). The optional substring filter is mentioned, making the purpose unambiguous.

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 parameter details but does not explain when to use this tool versus alternatives like script_class_detail or script_module_help. There is no explicit when-to-use or when-not-to-use guidance, nor any mention of prerequisites or exclusions. Only the optional filter and detail levels are described, which is context but not usage differentiation.

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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