seedream_image_to_image

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

No annotations are provided, so the description carries the full burden. It states that the tool generates a new image based on a reference and prompt, but it does not disclose behavioral traits such as destructive nature (e.g., whether the original image is modified), authentication requirements, rate limits, or error handling (e.g., invalid URL). The examples are illustrative but not transparent about behavior.

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

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

The description is very concise, with just one sentence and two example prompts. It is front-loaded with the purpose. While efficient, it could be slightly more structured (e.g., bullet points for models or parameters). No redundant information, but the conciseness leaves out useful details.

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

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

Given the complexity (9 parameters, no output schema), the description is minimal. It covers the core functionality but does not explain output behavior, response formats, or parameter interaction. The schema covers parameter descriptions, so the description's job is to provide higher-level context, which it does only partially. The examples help but are not sufficient for full contextual completeness.

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

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

The input schema has 100% description coverage, meaning each parameter is already explained in the schema. The tool description adds minimal additional semantic value beyond the schema: it provides example prompts but does not elaborate on parameter meaning, constraints, or interactions. Thus, a baseline score of 3 is appropriate.

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

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

The description clearly states the tool's purpose: '图生图：基于参考图片生成新图片' (image-to-image: generate a new image based on a reference image). It provides specific examples of prompts, making the intent unmistakable. It is well-distinguished from sibling tools like seedream_text_to_image by explicitly requiring a reference image URL.

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

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

The description explains when to use the tool: provide a reference image URL and a text description. However, it does not provide any guidance on when not to use it or how it compares to alternatives like seedream_text_to_image or seedream_merge_images. The mention of model versions (4.5 and 5.0) is helpful but not sufficient for clear usage boundaries.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.