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

Annotations already mark it read-only and idempotent, and the description adds crucial behavioral context: deprecation with a removal date, no data refresh, sorting order, price units, and the handling of unpriced models as undetermined rather than excluded. This goes well beyond the structured annotations and does not contradict them.

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 deprecation warning and redirect are front-loaded, followed by compact, meaningful behavior details. Every sentence earns its place, and there is no repetition of schema names 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 no output schema, the description reasonably explains what is returned: candidate models, corroboration, sorting, and the undetermined category. It clearly routes to current alternatives. The main gap is not explaining how limit and provider interact with the results, though their property names give some hint.

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?

With 0% schema description coverage, the description must compensate for missing parameter documentation. It clarifies constraints for minContextWindow, capabilities, and input price limits, and notes prices are per million tokens. However, it does not explain provider or limit, leaving some parameters dependent on their self-explanatory names.

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 states a specific verb and resource: return models satisfying user constraints from evidence, sorted by cheapest input price. It distinguishes itself from siblings by explicitly flagging deprecation and naming the replacement tools. The scope and output are clear.

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?

It explicitly tells users not to use this for building and directs them to discover_daystruct_capabilities and compat_check instead. It also clarifies that this tool returns candidates with evidence, not a recommendation, which helps an agent decide when the tool is or isn't appropriate.

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