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

Annotations already declare readOnlyHint and idempotentHint, but the description adds vital behavioral details: numeric values are replaced with '<number: paid>', provenance fields are included, and the paid REST endpoint URL is returned. This gives the agent a precise expectation of the output without contradicting annotations.

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?

Three sentences, each earning its place: the first states the free sample purpose, the second explains the value replacement and the output structure, the third ties it to paid usage and lists included fields. No wasted words.

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 simple tool with one parameter, annotations, and an output schema, the description is complete. It covers the tool's purpose, what to expect in the response, how it relates to the paid endpoint, and cost implications. No missing critical context.

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?

The single parameter `commodity` is fully documented in the schema with an enum and description (100% coverage). The description adds no additional semantic detail beyond referring to 'any supported commodity,' so baseline 3 is appropriate.

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's function: providing a free sample of benchmark data shape. It distinguishes itself from the paid sibling benchmark.commodity by detailing the key difference (numeric values replaced with '<number: paid>') and naming the endpoint.

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?

Explicitly tells when to use this tool: 'Use this to understand exactly what fields you will receive from the paid benchmark.commodity endpoint before spending $0.10 USDC.' This direct guidance also names the alternative and the cost, making the usage context unambiguous.

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