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td_python_api

Inspect Python API members and methods for TouchDesigner classes or operator types, including inherited ones, with signatures and return types. Filter the list by query to target specific functionality.

Instructions

Python members and methods available on a class, with inherited ones.

name is an operator type ('noiseTOP') or a class ('TOP', 'OP', 'Par', 'UI'). query filters the member list. Signatures and return types come from the reference shipped with this TouchDesigner build.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "name": "<name>"
    },
    "name": "td_python_api"
  }
}

Input Schema

Name	Required	Description	Default
`name`	Yes
`query`	No

Output Schema

Name	Required	Description	Default
`result`	Yes

Schema Changelog

Changes observed during successful MCP inspections.

First observedv0.1.0Sep 7, 2026

TDQS

A3.7/5.0

Behavior3/5

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

No annotations are provided, so the description carries the behavioral disclosure burden. It discloses that inherited members are included and that signatures/return types come from the shipped TouchDesigner reference. However, it does not clarify query matching behavior, invalid-name handling, or whether the result is a flat list or grouped structure.

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 compact and well-structured: a one-line summary of the tool's purpose followed by parameter semantics. Every sentence adds useful information and there is no redundant filler.

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 query/listing tool, the description covers the main purpose, input semantics, and data source. An output schema exists, so return values need not be described in text. Missing details such as query syntax, case sensitivity, or example usage are minor but would round out the context.

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 this well for `name` by giving concrete examples ('noiseTOP', 'TOP', 'OP', 'Par', 'UI') and explaining `query` as a filter. The exact syntax or matching rule for `query` is not specified, which prevents a perfect score.

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

Purpose4/5

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

The description clearly identifies the resource: Python members and methods available on a class, including inherited ones. It also specifies the input type (`name` is an operator type or class) and the action of filtering with `query`. It does not explicitly distinguish itself from sibling tools like `td_docs` or `td_operator_schema`, but the focus on Python API members/methods is distinct enough.

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

Usage Guidelines3/5

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

The description implies when to use the tool: when you need the Python API surface of a class or operator type, with optional filtering. It explains the roles of `name` and `query` but does not state explicit when-to-use/when-not-to-use guidance or mention alternatives among the many sibling tools.

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