list_image_models

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

With no annotations provided, the description carries the burden of describing behavior. It details what data the tool returns (strengths, price, aspect ratios, reference image count, valid aspect ratios/resolution tiers) and the query filter behavior. It does not mention output format or potential errors, but for a read-only listing tool this is adequate context.

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 tightly written with essential information only: purpose, contents, usage conditions, and parameter example. Despite being dense, every clause adds value, and the structure front-loads the action.

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?

For a simple listing tool with one optional parameter and no output schema, the description is comprehensive: it lists the return contents, the query semantics, and the relationship to image_generate. No further information is needed for an agent to decide when to invoke it.

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 parameter 'query' is fully described in the schema (coverage 100%), and the description adds concrete examples ('text', 'photorealistic', 'fast') and clarifies the filtering matches use-case keywords. This adds value beyond the schema's description.

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 lists available image-generation models with details (strengths, price, aspect ratios, reference image count) and additionally the valid aspect ratios and resolution tiers for image_generate. It uses the specific verb 'List' and resource 'image-generation models', distinguishing it from sibling list tools for video/audio models.

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 explicitly says when to use it: when you need to choose a model and don't already have one in mind, or to check valid aspect_ratio/resolution values before calling image_generate. It also states when not needed ('most of the time the model is the default or already specified'), providing clear exclusions.

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