National CMS benchmarks

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

With only readOnlyHint=true in annotations, the description adds meaningful behavioral context: it is computed from the current CMS Provider Information file and includes method and sample size with each value. This reassures the agent about data provenance and the nature of the output. No contradiction with annotations.

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 a single dense sentence that front-loads the key value (national reference values) and packs specific metrics without fluff. It could be broken into two sentences for readability, but it is efficient and every clause conveys needed information.

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 no-parameter tool with an output schema, the description sufficiently covers what the agent needs to know: what data is computed, from what source, and how to use it. It doesn't need to detail return formats because the output schema exists. This is complete for the tool's simplicity.

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 per the rubric the baseline is 4. The description need not explain parameters, and it doesn't. It does explain what the result contains, which is sufficient for a parameter-less read-only query tool.

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 identifies what the tool does: it returns national reference values for specific staffing and occupancy metrics computed from a named data source. It enumerates the exact outputs (mean HPRD, star-rating mean/distribution, bed-weighted occupancy) and notes method/sample size, making it unambiguous and distinct from sibling tools that cover operator-level data.

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 states the intended use: 'Use these to contextualize operator metrics.' This gives the agent clear when-to-use guidance. It doesn't name alternatives or exclusion conditions, but the purpose is specific enough that confusion with siblings like portfolio_overview or operator_metrics is unlikely.

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