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generate_variants

Generate 2–4 variants of one Roblox prop prompt. Returns one generation_id immediately; poll get_generation until every requested variant is complete. Each variant runs the full pipeline and counts individually against quota.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
styleNoStyle preset. Default low-poly.
promptYesWhat to generate.
variantsYesNumber of variants (2–4).
tri_budgetNoTriangle target per variant (500–10000). Default 10000.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.4/5.0
Behavior4/5

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

With no annotations, the description carries the full disclosure burden. It reveals three material behaviors: the call returns before generation finishes, completion must be tracked via get_generation, and each variant runs the full pipeline and consumes quota separately. This goes well beyond the schema, though it does not cover failure or auth edge cases.

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?

Three short sentences, each earning its place: purpose, async return/polling behavior, and per-variant quota impact. The most important information is front-loaded in the first sentence, and there is no 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?

The description is sufficient for an agent to invoke the tool and understand the next step (poll get_generation), despite lacking an output schema. It does not specify the shape of the immediate response beyond generation_id or what failure statuses look like, but the explicit polling instruction covers the key workflow gap.

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 coverage is 100%, so the baseline is 3; the description adds meaningful semantics beyond the schema by clarifying that 'prompt' is a single Roblox prop prompt and that 'variants' each trigger a full pipeline and quota charge. It does not explain style or tri_budget, but those are already well described in the schema.

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 names a specific verb ('Generate'), the resource ('Roblox prop prompt'), and the distinguishing scale ('2–4 variants'), clearly separating it from single-asset siblings like generate_asset. The first sentence alone tells an agent exactly what the tool produces.

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 description clearly sets the async workflow: call this tool, get a generation_id immediately, then poll get_generation until all variants are done. It does not explicitly name generate_asset as the single-variant alternative or state when not to use this tool, so it stops short of a full when/when-not explanation.

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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