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

Annotations already declare readOnly, non-destructive, and closed-world, so the safety profile is covered. The description adds genuinely new context: the list is filtered by Builder switch-on, the workspace chosen at connect time, and the caller's role, and it enumerates returned attributes (kind, status, latest accuracy).

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?

Two sentences, front-loaded with the resource and its authority claim, with no filler. Slightly clause-heavy in the first sentence, but every clause carries scope information.

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?

With no output schema, the description carries the return-value burden and does so at a summary level (kind, status, latest accuracy), plus the scoping rules that determine membership. Adequate for a zero-param read tool; finer field detail would be the only improvement.

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 nothing for the description to disambiguate; baseline 4 applies. The description correctly implies no filtering arguments exist by framing the list as fully determined by connection context.

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 names the specific resource being listed and its scope ('the models AI assistants may use'), and adds a strong boundary statement ('This list is authoritative; no other model can be reached'). It does not explicitly distinguish itself from the sibling model_report, so it stops short of a 5.

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?

Usage is implied rather than stated: the 'authoritative' claim tells the agent this is the source of truth for reachable models, but there is no explicit when-to-use, when-not-to-use, or named alternative (e.g. model_report for per-model detail).

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