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touchbridge

by GaNotchVFX
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Python
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measure_cooktimes

Measure per-operator cook times in TouchDesigner, sorted most-expensive first, to pinpoint which devices slow down frame rendering.

Instructions

Per-operator cook cost (ms) sorted most-expensive first: which device is eating the frame.

paths (list[str]): Operator paths to measure.

path (str | None): Parent whose children are measured.

top (int | None): Return only the N most expensive.

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
topNo
pathNo
pathsNo
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

A4.2/5.0
Behavior3/5

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

With no annotations, the description carries the full burden and does disclose useful behavior: results are sorted most-expensive first, 'summary' truncates long lists to 25 + count, and 'response_format' offers yaml (default, token-cheap) or json. It does not state whether the operation is read-only, what happens when both 'path' and 'paths' are provided, or any prerequisites like an active bridge connection, leaving some gaps.

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 front-loaded with a concise purpose statement and then lists each parameter with a short, scannable explanation. There is no filler; every sentence adds value, and the structure is easy for an agent to parse quickly.

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?

All five parameters are documented and core output behavior is described, but there is no output schema and some interactions remain ambiguous, such as whether 'path' and 'paths' are mutually exclusive, what happens if neither is given, and how 'top' interacts with detail modes. This creates moderate risk for an agent using the tool without additional context.

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%, and the description fully compensates by explaining every parameter: paths, path, top, detail, and response_format. It adds semantics beyond types—clarifying parent/child relationships, allowed detail levels, and the token-cheap yaml default—making the invocation intent clear.

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 a specific verb-resource pair: it measures per-operator cook cost in milliseconds, sorted most-expensive first, and frames it as 'which device is eating the frame.' This unambiguously differentiates it from siblings like measure_gpu, measure_chain, or measure_fps by focusing on operator-level cook times.

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

Usage Guidelines4/5

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

The opening line gives a clear usage context (diagnosing which device consumes frame time) and the parameter descriptions add operational guidance. However, it does not explicitly name sibling tools or state when not to use it, so alternative routing is implied rather than explicit.

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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