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

Annotations already establish read-only/idempotent, and the description adds real behavioral context on top: result shape, inclusion of total count and default model, truncation at default 25 / max 100, and the truncation hint. That is exactly the kind of operational detail annotations cannot carry.

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 dense sentences, front-loaded with the purpose and the return shape, then actionable routing. The long parenthetical field list is efficient but makes the first sentence heavy; nothing is wasted, though it is close to overpacked.

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?

No output schema exists, and the description compensates by describing the returned fields, the count, and the default model, plus truncation behavior. An agent can call this correctly and interpret the response without further context.

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 coverage is 100%, so the baseline is 3; the description still adds value by explaining the limit/truncation interaction, giving concrete query examples ("claude", "gpt"), and clarifying that model returns full details for one item. It does not mention zero_data_retention, the one filter whose effect is least obvious from its name alone.

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?

"Find models" is a thin opener but the following sentence nails the resource and scope: a compact model catalog with id, name, context_length, pricing and zero_data_retention, plus total count and default model. No sibling tool lists models, so differentiation is clear by default, though the verb could be tighter ("list/search models").

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?

Explicit when-to-use guidance: filter with query when narrow, read the hint when truncated, pass model (or id) for a single model's full details, and feed the returned id into create_run. It also names the alternative path (detail vs list) and the reason (hundreds of models).

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