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Budka MCP

Budka MCP

by curlysasha
OverviewSchemaSourceRelated ServersDiscussionsAdmin
JavaScript
Remote

Get Aspect Ratios

get_aspect_ratios

Find supported aspect ratios for image generation. Pass a model mode to see ratios for that model, or omit it to view all ratios grouped by model.

Instructions

Returns the list of available aspect ratios for image generation. Pass a mode to get ratios for a specific model, or omit to see all ratios grouped by model.

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

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

Input Schema

NameRequiredDescriptionDefault
modeNoModel mode. If provided, returns only ratios supported by this model.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.0.0

TDQS

A4/5.0
Behavior4/5

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It states that the tool returns a list and describes the grouping behavior when mode is omitted. This gives a clear picture of the read-only nature. It does not mention potential quirks like sorting, errors, or authentication, but for a simple listing tool the description is reasonably transparent.

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 long, front-loaded with the primary purpose, and contains no unnecessary wording. Every piece of information earns its place.

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 tool's low complexity (one optional enum parameter, no output schema, no annotations), the description is largely complete. It explains the main behavior and the two modes of operation. However, without an output schema, it could be more explicit about the exact return structure beyond just 'list grouped by model.'

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 schema covers 100% of parameters, with the 'mode' parameter fully described as 'Model mode.' The description adds the behavior when omitted (grouped by model) but this is more about tool behavior than parameter semantics. It does not add significant new meaning beyond the schema, 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 tool returns a list of available aspect ratios for image generation. It uses a specific verb ('Returns') with a clear resource ('aspect ratios') and provides context ('for image generation'). This distinguishes it from siblings like get_models and generate_image.

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 gives clear parameter usage instructions: 'Pass a mode to get ratios for a specific model, or omit to see all ratios grouped by model.' However, it does not explicitly discuss when to use this tool versus alternatives such as get_models or when not to use it. The usage guidance is implied rather than explicitly contrasted with siblings.

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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