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Generate Image(s)

generate_image

Generate image(s) from a text prompt.

Instructions

Generate image(s) from a text prompt. Prefer explicit provider+model; respect model capabilities.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
nNoCount of images to generate; provider limits apply.
sizeNoUnified size class: 'S' | 'M' | 'L'.
modelYesModel id (e.g., 'gpt-image-1', 'dall-e-3', 'imagen-4.0-generate-001').
promptYesText description of the desired image.
qualityNoQuality preference: 'draft' | 'standard' | 'high'.
providerYesProvider: 'openai' | 'openrouter' | 'azure' | 'vertex' | 'gemini'.
directoryNoOptional directory path to save generated images. If not provided, images will be saved to a temporary directory.
backgroundNoOptional background alpha for AR engines supporting transparency.
orientationNoOrientation preference: 'square' | 'portrait' | 'landscape'.
negative_promptNoOptional negative prompt honored by supporting providers.
Behavior2/5

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

Annotations already indicate non-readOnly (write operation) and non-idempotent, but description adds no behavioral context beyond what annotations provide. It does not disclose potential side effects, no mention of auth requirements, rate limits, or what happens with different model choices. Descriptions should add value beyond structured fields.

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?

Extremely concise—one sentence and a short instruction. No wasted words, but could be restructured to include essential guidance. Concision is high, but at the cost of completeness.

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?

Tool has 10 parameters, complex schema with enums, and no output schema. Description fails to explain return values, supported image formats, error handling, or model-specific constraints. Incomplete for a complex generative tool.

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 coverage is 100%, so baseline is 3. Description provides minor added guidance regarding explicit provider+model but does not add significant meaning beyond what parameter descriptions already cover. Minimal extra value.

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?

Clear verb+resource: 'generate image(s) from a text prompt'. Description states action and input. However, it does not explicitly distinguish from sibling tools like 'edit_image' or 'get_model_capabilities', though the tool name itself is unambiguous.

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?

Provides implicit usage guidance ('Prefer explicit provider+model; respect model capabilities') but lacks explicit when-to-use, when-not-to-use, or alternatives. No mention of why one would choose this tool over 'edit_image' or when to use 'get_model_capabilities' instead.

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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