list_models

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

With no annotations, the description carries full burden for behavioral disclosure. It fails to state that it is a read-only operation, what 'available' means (e.g., accessible to the user), or whether the result is a list of model identifiers or full metadata. Minimal behavioral 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 a single, concise sentence with no filler. It is front-loaded with the verb and resource, and length is appropriate for a simple list operation.

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 one-parameter list tool, the description is adequate but does not clarify the nature of the returned list (e.g., model names vs full details) or point to get_model_info for specifics. Given the lack of an output schema and the presence of a sibling that provides details, a bit more guidance would improve completeness.

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 input schema already describes the category parameter as 'Filter by category' with an enum, so schema description coverage is 100%. The description's 'by category' adds no semantic value beyond what the schema provides. Baseline 3 is appropriate.

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 states a clear action ('List') on a specific resource ('available AI models') with a scope ('by category'). It is distinguishable from siblings like generate_image or get_model_info, though it does not explicitly name the alternative for detailed info.

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?

No guidance is given on when to use this tool versus siblings. It does not mention that get_model_info provides per-model details, nor when category filtering is appropriate. The description implies usage but offers no explicit decision criteria.

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