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

Annotations already declare the operation read-only and non-destructive, so the description does not contradict them. However, it adds no behavioral detail beyond that, such as pagination behavior, result scope, or whether all rows are returned; the parenthetical only clarifies domain meaning.

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. The parenthetical adds relevant clarification without bloating the text, and the key action is front-loaded.

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 presence of an output schema and read-only annotations reduces the burden on the description, but the ambiguity with `theoretical_models.list` and the lack of pagination semantics leave important selection and invocation gaps. An agent may not be able to reliably choose this over the sibling list tool.

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 0%, and the description provides no explanation of the `limit` and `offset` parameters. Since the schema itself also lacks descriptions, these parameters are effectively undocumented, and the description does nothing to compensate.

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 clear verb-resource pair, 'List Model rows', and adds a useful parenthetical defining models as 'theoretical / structural frameworks.' However, it does not explicitly distinguish this list from the sibling `theoretical_models.list`, leaving some ambiguity about the exact entity boundary.

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?

There is no guidance about when to use this tool versus alternatives like `models.lookup`, `models.search`, or `theoretical_models.list`. The list semantics are implied by the name and verb, but no explicit when/when-not or alternative routing is provided.

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