SeedreamMCP

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 return format (JSON with task_id, image URLs), default watermarking behavior, asynchronous callback capability, and model-specific constraints (e.g., seed only works with v3). Could improve by explicitly noting the async task nature (implied by task_id and sibling get_task tools) and any rate limits.

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?

Well-structured with clear visual hierarchy: one-line summary, capability elaboration, usage conditions, model selection guide, and return specification. No redundant text; every sentence provides decision-making value. Appropriate length for a 12-parameter tool with complex model variants.

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 high complexity (12 parameters, 4 model versions with different capabilities, conditional features) and 100% schema coverage, the description provides sufficient context. It addresses model selection strategy and usage boundaries without needing to replicate detailed parameter specs already covered in the schema. Output schema exists, so brief return summary is adequate.

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% so baseline is 3. The description adds value through the 'Model selection guide' section which organizes model options by capability (flagship vs. cost-effective) and the usage guidelines which help agents understand when to set certain parameters (e.g., not using edit models for generation).

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 immediately states 'Generate an AI image from a text prompt using ByteDance's Seedream model' with specific verb (generate), resource (AI image), and provider context (ByteDance/Seedream). It distinguishes from sibling seedream_edit_image by explicitly naming it as the alternative for editing existing images.

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?

Contains explicit 'Use this when:' and 'Do NOT use this when:' sections with clear scenarios (generate from scratch vs. edit/combine images). Specifically names seedream_edit_image as the alternative tool, providing unambiguous guidance on tool selection.

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