seedream_list_models

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

No annotations provided, so description carries full burden. It states it returns a formatted table with descriptions, implying no side effects. Does not mention authentication requirements or data freshness, but for a read-only listing tool it is adequately transparent.

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?

Concise: one line for purpose, bulleted use cases, and output format. No fluff. Well-structured and easy to scan.

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 zero parameters and an output schema exists, description is complete. Explains what models are listed and for what purpose. Does not need to explain return values since output schema covers that.

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?

No parameters in input schema. Description compensates by detailing what the output includes (capabilities, pricing, descriptions). Baseline 4 for zero-param tools where description adds meaningful output context.

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?

Description clearly states it lists all available Seedream models with capabilities and pricing. Specific verb 'list' and resource 'models'. Distinguishes from sibling tools which focus on editing, generating, or retrieving tasks.

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?

Explicitly lists three use cases: user asks about models, need to choose a model, want to compare capabilities. Does not mention when not to use, but that is not critical for a simple listing tool. No alternative tools suggested, but sibling tools are distinct in purpose.

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