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

Annotations already declare readOnlyHint, idempotentHint and openWorldHint=false, so safety is covered. The description earns credit by disclosing what the payload contains — percentiles, US median, prior-year medians and report count — which is useful behavioral context the annotations cannot convey.

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?

Front-loaded with the purpose and scope before the metric list, and no filler sentences. The long enumeration of metrics is dense but each item is informative, not padding.

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 no output schema, the description takes on the job of describing the return payload and does so thoroughly, plus it covers defaults and grouping behavior. The only shortfall is the absence of any cross-reference to the sibling 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 both parameters are fully documented in the schema, including the constraint that national_group applies only when state is US. The description reiterates the state/US/group concept but adds no syntax or edge-case detail beyond the schema. Baseline 3 applies.

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?

States a specific resource (Medicare cost-report benchmarks for skilled nursing facilities) and enumerates the metrics returned (occupancy, revenue, margin, payer mix, PPS payment, contract labor). Clear what it produces, but never contrasts with the sibling snf_valuation, so sibling differentiation is left to inference.

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 parenthetical scope '(or the US, or a national ownership or size group)' implies the calling contexts, and the default of US is stated in the schema. There is no explicit when-to-use/when-not guidance or reference to snf_valuation, which is the main alternative an agent would weigh.

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