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, yet it discloses nothing about read-only safety, ordering, pagination, or completeness of results. The presence of an output schema covers return values, but nothing about how the call behaves is stated.

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?

It is a single short sentence with no padding, so it is concise and front-loaded. However, the brevity comes at the cost of substance, so the sentence does not fully earn its place as a usable definition.

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?

The tool is simple (zero params, output schema present), which lowers the bar, and the description plus schema is arguably enough to call it. Still, an agent gets no statement of scope (all models vs. filtered) or relationship to describe_model, leaving a clear gap.

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 takes zero parameters, so there is no parameter semantics for the description to explain. Baseline 4 applies; no compensating detail is needed.

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 phrase 'The models that already exist' restates the tool name rather than stating a verb and resource. It is interpretable as a listing operation, but it never says 'list' or clarifies the scope of what 'exist' means, leaving an agent to infer the action.

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 when-to-use or when-not-to-use guidance is offered, despite siblings like describe_model and create_model that an agent must choose between. The only implied signal is that this returns existing models, which an agent could already infer from the name.

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