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seedream_edit_image

Edit images by providing text instructions to change styles, backgrounds, or attributes. Use cases include style transfer, background replacement, 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
seedNoRandom seed for reproducible edits. Range: [-1, 2147483647]. Default is -1 (random). Only works with v3 models.
sizeNoOutput image resolution. '1K' (default), '2K', '3K', '4K', or 'adaptive'.
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. 'doubao-seededit-3-0-i2i-250628' (dedicated editing model, best for image modification). Other models can also be used for editing when images are provided.doubao-seededit-3-0-i2i-250628
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'.
guidance_scaleNoPrompt weight — higher values make edits follow the prompt more closely. Range: [1, 10]. Default is 5.5 for doubao-seededit-3-0-i2i. Only works with v3 models.
response_formatNoResponse format. 'url' (default) or 'b64_json'.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior3/5

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

No annotations are provided, so the description carries full burden. It discloses that the tool modifies images, uses a model, and returns JSON with task_id and image URLs. It does not mention potential side effects, authentication needs, rate limits, or async behavior (though callback_url parameter hints at it).

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 bullet points for use cases and clear sections. It is slightly lengthy but each part adds value. Front-loaded with the core purpose.

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 10 parameters, no annotations, and an output schema, the description covers main functionality, use cases, and return format. It lacks details on error handling, limits, or edge cases, but is generally sufficient.

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% – all 10 parameters have descriptions in the schema. The description adds context like 'supports single or multiple image inputs' and lists common use cases, but does not significantly enhance understanding beyond what the schema already provides.

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 starts with a clear verb and resource ('Edit or modify existing images using ByteDance's Seedream/SeedEdit model'), and distinguishes from sibling tools like seedream_generate_image by focusing on editing existing images. Use cases are listed to reinforce the purpose.

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?

A 'Use this when:' section explicitly lists scenarios (e.g., modify existing image, change style, virtual try-on), providing clear context. However, it does not explicitly state when NOT to use or mention alternatives (like seedream_generate_image for generation).

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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