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

Annotations already declare read-only, non-destructive, idempotent behavior. The description adds valuable behavioral context beyond annotations: ranks are cohort-relative, each row includes cohort, rank, source scope, calculation method, and source link, and cross-cohort comparisons are invalid. This provides useful detail on data structure and limitations.

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, each adding essential information: what the data is, what each row contains, and a critical usage warning. No redundant phrases or filler; every sentence earns its place and the key purpose is front-loaded.

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 zero-parameter, no-output-schema tool, the description is complete. It specifies the data year, ranking approach, row contents (cohort, rank, source scope, calculation method, source link), and warns against cross-cohort comparison. The agent has enough context to invoke the tool and interpret results without further clarification.

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 tool has zero parameters, so the baseline is 4. The description focuses on the data content and interpretation rather than parameter usage, which is appropriate given there are no parameters to document.

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 provides insurer prior-authorization denial rates for CY2025, ranked within compatible reporting cohorts. It specifies the resource (denial rates), action (ranking), and scope (cohorts), which distinguishes it from sibling tools that focus on other metrics like appeal rights or condition outcomes.

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 includes an explicit usage constraint: 'Never compare ranks across cohorts,' guiding correct interpretation. It does not name alternative tools, but the tool's purpose is clear from the name and description, so the context is sufficient. A minor gap is not explicitly stating when to use this instead of sibling tools, though it is implied.

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