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

Annotations already declare the tool as read-only, idempotent, and non-destructive. The description adds crucial behavioral context: it is a paid tool costing 0.01 USDC per call, which is not captured in annotations. It also discloses that variants are marked in `extra.variant`, giving the agent insight into data structure. No contradictions.

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 description is concise and well-organized. It leads with the cost (a critical decision factor), then explains the output scope and sources, and finally notes optional inclusions. Two sentences carry all necessary information with no redundancy, earning a top score.

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 the tool's simplicity (two params, read-only, no output schema), the description provides sufficient detail: it lists the sources, the fields included (cache-read price, context length), and how variants are marked. It lacks explicit mention of response format (e.g., array of rows), but that is a minor omission for a read-only quote tool.

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?

Both parameters are fully described in the schema (100% coverage), so the baseline is 3. The description mentions 'one model on one day' but does not add new details about the parameters themselves (e.g., how to format `day` or validate `model`). It merely reiterates the tool's scope, adding no semantic value beyond the schema.

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 clearly states the tool returns price data for one model on one day across multiple sources, with specific fields like USD per million tokens. This differentiates it from sibling tools like tokens_history (which likely covers multiple days) and tokens_models (which lists model slugs). The verb 'retrieves' is implied through 'Every listed price...', and the resource is explicit.

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?

The description explains what the tool does but provides no guidance on when to choose it over alternatives (e.g., tokens_history for trends or tokens_board for a summary). It doesn't mention exclusions or routing conditions, leaving the agent to infer usage from the scope ('one model on one day').

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