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seedream_edit_image

Modify existing images via text instructions to change style, background, attributes, or clothing. Handles single or multiple images for style transfer, scene changes, and virtual try-on.

Instructions

Edit or modify existing images using ByteDance's Seedream/SeedEdit model.

This tool modifies existing images based on text instructions. It can change
styles, backgrounds, attributes, clothing, and more. Supports single or
multiple image inputs.

Use this when:
- You want to modify or transform an existing image
- You need to change style, background, colors, or attributes
- You want to apply artistic transformations (watercolor, oil painting, etc.)
- You need virtual try-on (clothing on person)
- You want to place objects in different scenes

Common use cases:
- Style transfer: "Convert to anime style", "Make it look like a pencil sketch"
- Background change: "Replace background with a sunset beach"
- Attribute edit: "Change hair color to blonde", "Add sunglasses"
- Virtual try-on: Provide person image + clothing image
- Scene composition: Place products in realistic environments

Returns:
    JSON with task_id, trace_id, success status, and edited image data
    including image URLs.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
sizeNoOutput image resolution. '1K' (default), '2K', '3K', or '4K'.
imageYesList of image URLs or base64-encoded images to edit. Supports HTTP/HTTPS URLs (publicly accessible) or base64 format (data:image/png;base64,...). Each image must be under 10MB.
modelNoModel to use for editing. Seedream 5.0 Pro, 5.0 Lite, 4.5, and 4.0 all support image editing when images are provided.doubao-seedream-5-0-260128
promptYesDescription of the edit to perform on the image(s). Describe what changes you want. Example: 'Change the background to a beach scene', 'Make the person wear a red dress', 'Convert to watercolor painting style'
watermarkNoWhether to add an AI-generated watermark. Default is true.
callback_urlNoOptional webhook URL for async result notification.
output_formatNoOutput image format. 'jpeg' (default) or 'png'.
response_formatNoResponse format. 'url' (default) or 'b64_json'.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior4/5

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

With no annotations provided, the description carries the full transparency burden. It explains the tool modifies existing images, supports single/multiple inputs, and describes the return JSON structure (task_id, trace_id, success, image URLs). It does not cover operational details like async behavior, failure modes, or permissions, but it is reasonably transparent for an edit tool.

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?

The description is well-structured with a clear first sentence, bulleted usage criteria, and a returns section. It is somewhat long but every section provides useful guidance. It is front-loaded with the core purpose and avoids redundancy.

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 the tool has 8 parameters, no annotations, but a rich schema and output schema, the description is quite complete. It explains when to use, common applications, return format, and even some parameter constraints. It could mention async callback behavior more explicitly, but overall it provides sufficient context for correct invocation.

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

Parameters4/5

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

Schema coverage is 100%, so baseline is 3. The description adds value beyond the schema by giving prompt examples, explaining multi-image support for virtual try-on, and clarifying that image inputs can be URLs or base64. This enhances an agent's understanding of how to set parameters.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states "Edit or modify existing images using ByteDance's Seedream/SeedEdit model," with a specific verb and resource. It distinguishes itself from sibling tools like seedream_generate_image by focusing on modification rather than creation, and the first sentence establishes the scope.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides a clear "Use this when" section with specific bullets (modify, change style, virtual try-on, etc.) and common use cases. However, it does not explicitly name alternatives or provide when-not-to-use guidance, so it falls short of a perfect 5.

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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