list_models

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

No annotations are provided, so the description carries the full behavioral burden. 'List' reasonably implies a read-only operation with no side effects and a returned collection of models, which is useful. However, it doesn't state ordering, pagination, or what exactly qualifies as 'saved'.

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?

A single sentence with no filler, and the action and object are front-loaded. This is appropriately sized for a parameterless list command.

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 zero-parameter list operation with no output schema, the description covers the core action and implied return value. It would benefit from a brief note on what 'saved models' includes or whether results are sorted/filtered, but the low complexity makes this nearly complete.

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 tool has zero parameters, so the input schema fully documents the call. The description adds no parameter-level information, but none is needed; the baseline for zero-parameter tools applies.

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 uses a specific verb and resource ('List saved models'), making the operation unambiguous. It is naturally distinct from sibling get_model (singular retrieval) and mutating tools like edit_model or put_model, though it does not explicitly name them.

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 phrase 'List saved models' implies a use case: when you need an inventory of saved models. However, it gives no explicit guidance about when to prefer it over get_model or how it relates to the other siblings, so the usage context is only implied.

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