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measure_fps

Retrieve current FPS, realtime flag, cook rate, and throttle queue in TouchDesigner to diagnose performance bottlenecks during live rendering.

Instructions

FPS, realtime flag, cook rate, throttle queue.

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
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

C2.7/5.0
Behavior2/5

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

No annotations are present, so the description carries the full burden of disclosing behavior. It does explain output-shaping details such as summary truncation, minimal mode, and YAML/JSON options, but it never states whether the tool is read-only, what the listed fields actually mean, or what side effects or limitations exist.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness3/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is very compact and front-loads the relevant metric names, and the parameter lines are efficient. However, the opening line is an ambiguous fragment rather than a clear sentence, which harms readability even though it is short.

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

Completeness2/5

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

With no output schema and no annotations, the description should explicitly say what the tool does and what it returns. It lists metric names and formatting options but omits an explicit operation description, usage context, and any relationship to the sibling measure_* tools, leaving the tool under-specified for an agent.

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%, so the description must compensate. It does so well: 'detail' is explained with its three modes and their output effects, and 'response_format' is explained with defaults and a token-efficiency note. The only minor gap is that 'full' is not elaborated, but the overall parameter semantics are clear and useful.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose3/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description names the subject area (FPS, realtime flag, cook rate, throttle queue) but never states an action verb like 'measure' or 'return'. It is not a full tautology because it lists specific metrics, but it is vague and does not clearly distinguish itself from sibling measurement tools such as measure_gpu, measure_chain, or measure_cooktimes.

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?

There is no guidance about when to use this tool versus the many sibling tools. The description only explains output formatting options, not selection criteria, prerequisites, or context. An agent is left to infer when measure_fps is appropriate.

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