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

The description goes beyond the annotations by explaining data source behavior: counts include only certified publishable dependencies, uncertified families report zero instead of falling back to legacy rows, and the distinct nature of countries and shipping_lines counts. It also discloses that the tool is free and provides a return object with a timestamp. This adds valuable context without contradicting the readOnly, idempotent, and non-destructive 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?

The description is concise and well-structured. It front-loads the main purpose, then provides usage context, a specific behavior caveat, the return object, and related tools. Every sentence adds value, with no redundant or filler content. The format is easy to scan.

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 there are no parameters and no output schema, the description is highly complete. It specifies the return object structure, the semantic meaning of counts, the timing of usage, and relevant alternatives. It also covers edge cases like uncertified families. This is more than sufficient for an agent to select and invoke the tool correctly.

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 are zero parameters, so the schema provides no semantics. The baseline for 0 params is 4. The description does not need to explain parameters, but it does describe the return fields, which is helpful. Since there are no parameters, the description's value in this dimension is inherently limited; however, it fully compensates by not requiring any parameters and clarifying output.

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: 'Get current counts from ShippingRates customer-published datasets.' It specifies the resource and the type of output (counts) and lists the exact fields returned. This distinguishes it from sibling tools, which focus on specific data like rates, lines, or searches.

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?

Explicit guidance is provided: 'Use this before calling data tools' indicates the optimal timing. Additionally, it names alternatives: 'Use shippingrates_lines for per-carrier breakdowns, shippingrates_search for keyword discovery.' This clearly tells the agent when to use this tool versus related ones.

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