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. The description adds the default currency (USD) and the per-1M-token pricing basis, but says nothing about what happens for an unknown id or how scores are scaled/measured.

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 front-loaded sentence that leads with identity and scope before enumerating returns. No filler or redundancy.

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 usefully enumerates the returned payload (scores per category, price per 1M tokens, regions, context, capabilities), which is exactly what the agent needs. It stops short of describing error behavior for a bad id or score semantics.

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 only 50% (id has no schema description), so the description must compensate: 'by id' clarifies that id is the model identifier, and '(default USD)' restates the currency default. This covers both parameters, though it adds no format or example for id.

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 identifies the resource ('one model ... by id') and anchors it to the sibling list_models, so an agent knows this is the single-item counterpart to the list tool. It lacks an explicit verb and does not differentiate from recommend_model or estimate_cost, which also deal with single 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?

Usage is implied: fetch details for one model when you already have its id. There is no explicit when-to-use, no when-not-to-use, and no routing advice for cases where the caller lacks an id or wants a recommendation (recommend_model exists as a sibling).

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