List selectable AI person models

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

With no annotations, the description carries the disclosure burden. It conveys a read-only browsing behavior and that models are 'selectable' for a specific field, which is useful. However, it does not mention pagination behavior, ordering, or what kind of identifiers/fields are returned beyond the schema-provided limit and gender filter.

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 a single, tightly constructed sentence. It front-loads the catalog action and immediately adds the cross-tool usage context, with no redundant or filler words.

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 low complexity, optional parameters, and full schema coverage, the description is nearly complete. It ties the tool to a downstream field in create_generation, though it could be slightly more explicit about the shape or identity of the returned model values.

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 description coverage is 100%, so the baseline applies and the schema already documents limit and gender. The description adds no parameter-level meaning beyond stating the broader purpose of the returned models.

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 names a specific verb ('Browse') and resource ('catalog of AI person models'), and explicitly ties the output to a concrete use case: 'use as images.fashion_model in create_generation.' This clearly distinguishes it from sibling list tools like list_models or list_poses.

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 clear context for when to use the tool: when choosing an AI person model to pass as images.fashion_model in create_generation. It does not explicitly name alternatives or state when not to use it, but the purpose is specific enough to route an agent correctly.

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