kev_list_models

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It does convey that the tool lists models and metadata, implying a read-only operation, but it does not explicitly state side-effect safety, authentication requirements, or list behavior (e.g., pagination, ordering). This is adequate but not rich.

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 that front-loads the core action ('List Kev models') and then adds valuable metadata examples. Every word earns its place, with no redundancy or filler.

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 zero parameters, an existing output schema, and a simple list operation, the description is nearly complete. It covers what is returned at a high level and would allow an agent to invoke the tool correctly, though it could mention output shape or pagination if applicable.

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 and the schema is empty, so the baseline for 0 parameters is 4. The description does not need to explain parameter behavior since none exist; it appropriately focuses on the tool's action.

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 a specific verb ('List') and resource ('Kev models'), and adds concrete metadata examples (device, temperature, prefix-cache statistics). This distinctly differentiates it from the sibling tools (kev_evaluate, kev_permute, kev_separate), which suggest different operations.

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 provides no guidance on when to use this tool versus alternatives like kev_evaluate, kev_permute, or kev_separate. There is no explicit 'when to use' or 'when not to use' context, leaving the agent to infer from the tool name alone.

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