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Get operator workflow guide

get_operator_workflow_guide
Read-only

Look up TouchDesigner operators for workflow guides with inputs, outputs, examples, and next-operator suggestions. When an operator is missing from the snapshot, returns candidate IDs and a caveat.

Instructions

Read-only: return an embedded TouchDesigner operator workflow guide with common inputs, outputs, examples, next-operator suggestions, and snapshot provenance. When an operator is absent from the imported snapshot, returns candidate guide ids and an explicit snapshot caveat instead of claiming that the operator does not exist.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
operatorYesOperator name, display name, or slug to look up.
next_limitNoMaximum number of next-operator suggestions to return.
include_examplesNoInclude Python examples, expressions, and generated usage patterns.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
foundYesTrue when the embedded knowledge base has a workflow guide.
guideNoOperator connection guide, when found.
examplesNoOperator examples, when requested and available.
operatorYesThe operator string from the request.
suggestionsYesCandidate operator ids when no exact guide is found.
data_versionNoImport source, source version, timestamp, and covered TouchDesigner version.
lookup_statusYesWhether the operator is present in the imported knowledge snapshot.
nextOperatorsYesSuggested downstream operators.
snapshot_noticeNoCaveat attached when an operator is absent from the imported snapshot.
Behavior5/5

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

The description adds valuable behavior beyond the annotations: when an operator is absent from the imported snapshot, it returns candidate guide IDs and an explicit snapshot caveat instead of falsely claiming the operator does not exist. This is a nuanced fallback an agent would not infer from the readOnlyHint/destructiveHint annotations. It also clarifies the data source ('embedded', 'snapshot provenance'), which is not in the annotations.

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 two sentences, front-loaded with the core purpose ('Read-only: return...') and then addresses an important edge case. Every sentence adds distinct value, and there is no redundant wording.

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?

Given the output schema and annotations, the description is largely complete: it names the output contents, notes the snapshot provenance, and discloses the missing-operator fallback. It could be more explicit about the relationship to the snapshot and what 'embedded' means, but overall it gives an agent enough context to invoke the tool correctly.

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

Parameters3/5

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

The input schema already provides full descriptions for all three parameters (operator, next_limit, include_examples) with 100% coverage. The description does not add parameter-specific details beyond what the schema captures, so the baseline of 3 is appropriate.

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 the action ('return') and the resource ('an embedded TouchDesigner operator workflow guide'), and specifies its contents (common inputs, outputs, examples, next-operator suggestions, snapshot provenance). This distinguishes it from sibling tools like get_td_docs or search_operators, which focus on documentation or search rather than a curated workflow guide.

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 a workflow guide for an operator) and notes the read-only nature, but it does not explicitly state when to prefer it over alternatives like get_td_docs or search_operators, nor does it mention exclusions. The missing-operator caveat gives some behavioral context but not usage boundaries.

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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