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

Annotations already declare readOnlyHint=true, idempotentHint=true and openWorldHint=false, so the safe-read profile is covered by structured data. The description adds the scoping constraint (single model, one usage volume) but says nothing about unknown/misspelled model handling, catalog size or data freshness. With annotations carrying the safety burden, a 3 is appropriate.

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?

A single dense sentence with no filler, and the most decision-relevant facts (price, context window, cost) are front-loaded. It reads as a run-on inventory rather than structured prose, but nothing is wasted.

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 three parameters, no output schema, and only one-third of parameters documented, the description leaves concrete gaps: units/defaults for the token inputs and behaviour for an unresolvable model id. Annotations cover the safety profile, so the omission is not severe, but the definition is only minimally sufficient for correct invocation.

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 only 33%: only 'model' is documented in the schema, while input_tokens and output_tokens carry defaults but no descriptions. The phrase 'cost for a usage volume' hints that token volumes drive the cost figure, but the description never states that these are token counts, that defaults are 1M/250k, or what happens if they are omitted.

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 enumerates exactly what facts are returned (price, context window, indices with rank, licence, privacy, computed cost, alternatives) and scopes it to 'one language model', which implicitly contrasts with the plural search tools (find_models, recommend_models). It is clear, but it is framed as a return-value list rather than a verb+resource statement and never names a sibling to differentiate itself.

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 explicit when-to-use or when-not-to-use guidance, no prerequisites, and no routing to alternatives such as estimate_cost or cheaper_alternative. The mention of 'cheaper or open alternatives' inside the return list arguably overlaps with the sibling cheaper_alternative without clarifying the boundary.

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