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Edit image

edit_image

Edit images by providing a prompt and source images via multipart upload, URL, or JSON array, with optional mask editing.

Instructions

Edit image Edits an image using multipart image uploads, JSON image URLs, or the official JSON images array for supported GPT Image models.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
nNo
maskNoOptional JSON mask reference for image edits. Provide exactly one of image_url or file_id. Multipart requests can also send mask as a file part.
sizeNo
userNo
asyncNoReturn a task before the edited image is ready for models that support public async execution.
modelYesModel to use for image edits. Send this explicitly.
imagesNoOfficial JSON image references for image edits. Provide exactly one of image_url or file_id for each item. GPT Image edits accept up to 16 source images; xAI Grok Imagine edit models accept at most 3 source images.
promptYes
streamNoImage streaming is not exposed through MCP tool calls; omit stream or set it to false.
qualityNo
image_urlNoSingle source image URL. Kept for TokenLab compatibility; use images for the official JSON shape.
backgroundNo
image_urlsNoMultiple source image URLs. GPT Image edits accept up to 16 source images; xAI Grok Imagine edit models accept at most 3 source images.
moderationNo
resolutionNo
compressionNo
aspect_ratioNo
output_formatNo
response_formatNo
output_compressionNo
Behavior2/5

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

Annotations indicate openWorldHint, but the description does not elaborate on unspecified side effects. No mention of auth, rate limits, or behavioral traits beyond stating input methods.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness3/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single sentence with some redundancy ('Edit image Edits an image'). It is short but wastes words on repetition rather than adding value.

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?

With 20 parameters, no output schema, and minimal description, the definition is incomplete for an AI agent to use effectively.

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

Parameters2/5

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

Schema coverage is only 35%, and the description adds no meaning to parameters. Many parameters (e.g., background, resolution, compression) remain unexplained.

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 the tool edits an image and mentions input methods, but lacks specificity on what kind of editing (e.g., inpainting, style transfer) and overlaps slightly with siblings like create_image and edit_image_file.

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?

No guidance on when to use this tool instead of alternatives like edit_image_file or create_image. No prerequisites or context provided.

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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