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

Annotations already declare readOnlyHint=true and openWorldHint=false, so the safety profile is covered elsewhere. The description adds genuine value by disclosing the shape of the return (three price components at a per-1M-token basis plus illustrative monthly agent costs), but it omits currency, data freshness, and what happens when the model id is unknown — all relevant for a pricing lookup whose numbers may drive decisions.

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?

One sentence, front-loaded with the core purpose and followed by the return contents. No filler, no repetition of the title or annotations — every clause carries 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?

For a one-parameter read-only lookup with no output schema, the description is nearly sufficient: it tells the agent which price dimensions come back and in what unit. The remaining gap is currency and whether 'example monthly agent costs' are assumptions the caller should interpret cautiously, which matters given the illustrative framing.

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?

There is a single parameter with 100% schema description coverage, and the schema already explains it accepts a model id like 'anthropic/claude-sonnet-5.5' or a name. The description adds nothing beyond that, so the baseline of 3 applies; no ambiguity is introduced, but no extra matching or fallback behavior is clarified.

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?

States a specific verb and resource ('Current API list price of one model') and enumerates what is returned: input, output, and cached input pricing per 1M tokens plus example monthly agent costs. It scopes to 'one model', which implicitly separates it from multi-model siblings, but it never names compare_models, cheapest_models_for, or estimate_cost, so sibling differentiation is left to inference.

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 only implied by the phrase 'one model' — an agent can guess this is the single-model lookup versus list_models or cheapest_models_for, but no when-to-use or when-not-to-use rule is stated. There is no guidance on choosing this over estimate_cost when the goal is cost projection rather than raw price lookup.

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