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generate_image

Creates images from text prompts and optional base or reference images, then saves the result to a specified local PNG path.

Instructions

Generates an image and saves it to a local file.

operation: "generate" (the only operation in this version). prompt: full instructions (composition, style, what is forbidden). output_path: output .png file (relative to IMAGEGEN_ROOT or absolute). base_image: image whose composition must be preserved; attached first. reference_images: style images, attached after the base, in the given order. size: desired "WIDTHxHEIGHT" (e.g. "1536x864"). With the codex backend it is only requested in text and not guaranteed; check width/height in the result. overwrite: allows replacing an existing file.

Returns path, format, width, height, operation, backend, model, warnings and log.

Input Schema

NameRequiredDescriptionDefault
sizeNo
promptYes
operationYes
overwriteNo
base_imageNo
output_pathYes
reference_imagesNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A4.1/5.0
Behavior4/5

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

With no annotations, the description does substantial work: it discloses local file writing, relative or absolute output_path handling, overwrite replacement behavior, and the caveat that size may not be guaranteed on the codex backend. It still omits what happens when a file already exists without overwrite, directory creation behavior, and any permission or cost constraints.

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 purpose is front-loaded in one sentence, followed by a compact per-parameter list. Every line adds useful information, including format examples and backend caveats, with no filler.

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 no output schema, the description usefully lists return fields: path, format, width, height, operation, backend, model, warnings and log. Given no annotations and seven parameters, it covers the key behavior and caveats well, though it leaves some edge-case behavior around existing files and filesystem setup unstated.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters5/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%, so the description must carry parameter meaning, and it does: it explains operation, prompt intent, output_path resolution, base_image composition role and attachment order, reference_images ordering, size format and backend caveat, and overwrite behavior. All seven parameters are meaningfully documented.

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 first sentence gives a specific verb and resource: generates an image and saves it to a local file. It is clear for an image-generation tool, though there are no sibling tools to distinguish from and no broader task framing.

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 implies usage through parameter roles: base_image for preserving composition, reference_images for style, and overwrite for replacing existing files. It does not explicitly say when to use this tool versus alternatives or when not to use it.

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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