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

Annotations already establish the tool as read-only, idempotent, and non-destructive. The description adds meaningful behavioral context beyond those annotations: ordering by payment amount, filter compatibility with open_payments_search, and a focus on individual records rather than totals.

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 carry the key distinctions (sorting, filter compatibility, use case) with no filler. The most important information is front-loaded before the use-case sentence.

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 read-only, optional-parameter query with complete schema coverage, the description is sufficient: it explains what the tool returns (top individual payments), how results are ordered, and how filters relate to a known sibling. It omits only minor details like the default limit, which is already in the schema.

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 description coverage is 100%, so the schema already documents all six optional parameters with examples. The description does not add new parameter-level detail; it only points to shared filters, which is fine given the baseline of 3.

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 names a clear resource (Open Payments individual payment records) and a specific behavior: same filters as open_payments_search but sorted by payment amount descending. It also states the intended use case (finding the largest payments), which distinguishes it from the aggregate sibling tools.

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?

It explicitly points to open_payments_search as the filter baseline and gives a use-case trigger: 'Use this to find the LARGEST individual pharma payments.' It does not enumerate when to prefer the aggregate siblings, but the 'individual' phrasing and sort focus provide enough direction.

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