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generate_image

Create an image from a text prompt. Costs money; checked against the budget first.

Instructions

Create an image from a text prompt. Costs money; checked against the budget first.

Input Schema

NameRequiredDescriptionDefault
modelNoModel ID from list_models. Default: configured default.
promptYesWhat to create, in natural language.
resolutionNoImage size: 512, 1K, 2K or 4K1K
output_nameNoShort name used in the file name (a slug is derived from it).
aspect_ratioNoe.g. 1:1, 16:9, 9:16, 4:51:1

Output Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A3.6/5.0
Behavior4/5

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

Annotations already declare readOnlyHint=false, openWorldHint=true and destructiveHint=false, so the mutating, open-world nature is known. The description adds genuinely new behavioral context that annotations cannot express: the call incurs monetary cost and is budget-checked before execution. It does not say what happens when the budget check fails or whether generation is synchronous.

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?

Two short sentences with no waste, and the cost caveat is placed early enough that an agent sees it before committing to the call. Every clause carries information.

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?

With an output schema present, return values need no explanation, and all five parameters are fully described in the schema. The cost-and-budget note covers the main non-obvious risk; only edge behavior (budget rejection, failure modes) is left unstated, which is a minor gap for this complexity.

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?

Schema description coverage is 100%, so every parameter including model, resolution, aspect_ratio and output_name is already documented in the schema. The description adds no syntax, defaults, or constraint detail beyond that, which is the expected baseline when the schema does the work.

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 uses a specific verb and resource ("Create an image") plus the input modality ("from a text prompt"), which implicitly separates it from edit_image and start_video. It stops short of naming a sibling explicitly, so an agent must infer the boundary rather than being told.

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 explicit when-to-use or when-not-to-use guidance and no mention of alternatives such as edit_image for modifying an existing image. The only steer is the implied contrast in "from a text prompt", and nothing tells the agent to call list_models first for a model ID, even though a sibling exists for that.

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