open_payments_top_doctors

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

Annotations already indicate readOnlyHint=true. The description adds behavioral details: it aggregates all payments per doctor, groups and sorts by total descending. This provides transparency about the data processing beyond the read-only annotation.

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 three sentences with no redundancy. The first sentence states the purpose, the second explains the mechanism, and the third provides a use case. It is front-loaded and every sentence adds value.

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?

The tool has no output schema, but the description conceptually explains the output (list of doctors with total payments). Input parameters are well-documented in the schema. It could mention the default limit or that filters are optional, but overall it is sufficient for a simple aggregation 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?

Schema coverage is 100%, so baseline is 3. The description does not add new parameter-specific meaning beyond what the schema already provides. It explains the aggregation behavior but not parameter details.

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 finds 'HIGHEST-PAID doctors by TOTAL payments received', specifying the verb (Find), resource (highest-paid doctors), and aggregation. It distinguishes from siblings like 'open_payments_by_physician' by emphasizing total aggregation.

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 explicitly marks itself as 'the key tool for finding doctors with the biggest pharma relationships', providing strong usage guidance. It implicitly suggests using this over other open_payments tools for top-level aggregation, though it doesn't explicitly list when not to use alternatives.

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