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

Annotations already indicate read-only, idempotent, non-destructive behavior. The description adds critical context about what the gross spending numbers do NOT represent (manufacturer revenue, net price, profit, etc.), which is valuable beyond structured metadata.

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?

Two sentences with no redundancy. First sentence front-loads the core function and outputs; second sentence provides an essential clarification. Every word serves a purpose.

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 an output schema present, the description sufficiently covers the query scope (time range, metrics). Minor omission on pagination behavior, but not critical given the schema and annotations.

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 low (33%) but the description adds meaning for the 'drug' parameter (brand or generic name). 'limit' is already described in schema. 'offset' receives no additional explanation, so overall partial compensation.

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 uses a specific verb 'Search' and resource 'CMS Medicare Part D spending', and clearly lists the returned fields (spending, claims, beneficiaries, dosage units, unit-cost trends) and time range (2020–2024). It distinguishes from sibling tools like medicare_part_d_generic_competition by focusing on spending and claims.

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 implies usage for Part D spending queries but lacks explicit guidance on when to use this tool over alternatives. The clarification 'Gross Part D spending is not manufacturer revenue...' provides some boundary but does not replace explicit usage context.

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