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generate_image

Create images from text prompts with configurable size, quality, and format. Save output to a file or receive a URL.

Instructions

Generate image(s) with the OpenAI Images API. SSE/HTTP transports auto-save files and return image URLs; stdio requires filepath.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
nNoNumber of images to generate.
sizeNoImage size. Supported values: auto, 256x256, 512x512, 1024x1024, 1536x1024, 1024x1536, 1792x1024, 1024x1792. Some models only support a subset.
promptYesImage generation prompt.
qualityNoImage generation quality.
filepathYesAbsolute path where the generated image should be saved.
overwriteNoAllow replacing existing output files.
backgroundNoGenerated image background behavior.
moderationNoImage moderation strictness.
output_formatNoOutput image format. jpg is normalized to jpeg for the API request.
output_compressionNoCompression level for jpeg or webp outputs, from 0 to 100.
Behavior3/5

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

With no annotations provided, the description carries the burden of disclosing behavior. It usefully reveals that SSE/HTTP transports auto-save files and return URLs, which is behavioral context beyond the schema. Still, it does not mention other notable behaviors such as default overwrite behavior, moderation handling, or exactly what happens in stdio mode after generation.

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 short sentences with no filler. The primary purpose is front-loaded, and the transport nuance is stated efficiently. Every sentence earns its place.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

The description covers the tool's purpose and a key transport difference, and the schema fully documents the parameters. However, with 10 parameters, no annotations, and no output schema, an agent might still be unsure what to expect as a result in stdio mode or how this tool relates to edit_image. The description is adequate but not fully complete.

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 the baseline is 3. The description adds almost no parameter-level detail beyond the schema; the only minor addition is the contextual note that stdio requires filepath, but that is already captured by the required field.

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 clearly states a specific action ('Generate image(s)') and resource ('with the OpenAI Images API'). It is easy to understand that this tool creates new images, and the sibling 'edit_image' suggests the complementary operation, though the description does not explicitly compare itself to that sibling.

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 transport-specific guidance: SSE/HTTP auto-save files and return image URLs, while stdio requires filepath. However, it does not explicitly explain when to choose this tool over edit_image; the use case is only implied by the tool name and the generate-vs-edit distinction.

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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