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yberudev
by yberudev

generate_variations

Creates up to four prompt or image variations using a model's n parameter when supported, or sends exact count requests after explicit paid-use authorization.

Instructions

Gera um conjunto limitado de variações de um prompt ou imagem. Usa n quando publicado pelo modelo; caso contrário envia exatamente count pedidos, após autorização explícita.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
sizeNo
countNo
modelNo
promptYes
dry_runNo
filenameNo
allow_paidNo
output_dirNo
resolutionNo
aspect_ratioNo
max_cost_usdNo
input_image_pathNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

C2.7/5.0
Behavior2/5

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

With no annotations, the description must carry the full behavioral burden. It discloses that the tool uses n when the model publishes it, otherwise sends exactly count requests after explicit authorization, but it omits cost implications, output/file side effects, and permissions for a 12-parameter generation tool.

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

Conciseness4/5

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

The description is two sentences with no wasted words and front-loads the core purpose. The second sentence is dense but still concise; clarity could be improved by defining 'n' in context.

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?

This is a complex tool with 12 parameters, no annotations, no output schema, and 0% schema description coverage. The description covers only the generation purpose and a narrow request-count rule, leaving most operational and parameter details missing.

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

Parameters2/5

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 for all 12 parameters. It only explains the count parameter and the model-specific 'n' behavior, leaving prompt, size, model, dry_run, filename, allow_paid, output_dir, resolution, aspect_ratio, max_cost_usd, and input_image_path undocumented.

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 states a specific verb and resource: 'Gera um conjunto limitado de variações de um prompt ou imagem.' This is clear enough to distinguish it from generating a single image, though it does not explicitly reference sibling tools like generate_image or edit_image.

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 on when to use this tool versus alternatives such as generate_image, edit_image, or animate_image. The mention of 'autorização explícita' is a behavioral constraint, not a usage condition.

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