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AbhishekMore-1

LiteLLM MCP Server Bridge

create_image

Generate images from text prompts using LiteLLM. Specify count, size, and model to tailor outputs.

Instructions

Generate images using LiteLLM (/images/generations)

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
nNoThe number of images to generate.
sizeNoThe size of the generated images. (e.g. 1024x1024)1024x1024
modelNoThe model to use for image generation.
promptYesA text description of the desired image(s).
Behavior2/5

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It only states 'Generate images' without mentioning side effects, authentication needs, cost implications, or what happens with the generated output.

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 a single sentence that front-loads the core action and resource, containing no wasted words.

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?

Despite the fully described input schema, the description lacks usage context, behavioral notes, and return value expectations, making it insufficient for confidently using the tool in complex scenarios.

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 has 100% coverage with descriptions for all four parameters, so the description does not need to add parameter details. It offers no additional meaning beyond 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 clearly states the tool's function ('Generate images') and identifies the endpoint ('LiteLLM (/images/generations)'), which distinguishes it from sibling tools like chat_completion or create_speech.

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?

The description provides no guidance on when to use this tool versus alternatives, nor does it mention any prerequisites or exclusions for usage.

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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