seedream_text_to_image

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

With no annotations provided, the description carries the full burden. It discloses that multiple images are supported only for certain model versions, and mentions output formats (URL or base64) and watermarks. However, it does not address potential issues like rate limits, content moderation, or timeout, leaving gaps in behavioral knowledge.

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 well-structured: purpose statement, model capabilities, examples, and a note. The three example prompts, while useful, add some verbosity. Overall, it is largely concise and front-loaded, with minimal waste.

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 8 parameters and no output schema, the description covers critical aspects: model versions, image count, size options, output formats, and watermark. It does not detail the return structure (e.g., how URLs are presented), but for an image generation tool, the provided information is sufficient for basic invocation.

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?

Schema coverage is 100% (baseline 3). The description adds value by explaining model version constraints for the 'n' parameter, suggesting prompt length limits, and noting that size can be custom (e.g., 1920x1080). This enriches the schema beyond defaults and enums.

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 explicitly states it generates images from text descriptions ('文生图：根据文本描述生成图片'), providing clear purpose. It uses a specific verb ('生成') and resource ('图片'). However, it does not differentiate from sibling tools like seedream_image_to_image or seedream_merge_images, lacking explicit contrast.

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 gives a useful note on model version limitations for multiple images ('注意：5.0 和 4.0 版本支持 n>1，4.5 仅支持 n=1'), guiding parameter selection. It also provides example prompts to illustrate usage context. No explicit when-not-to-use or alternative tools mentioned, but the context is clear.

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