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

Annotations already declare readOnlyHint=true and destructiveHint=false, so the bar is lower. The description adds valuable context by listing return components (peer_group, benchmark_percentiles, metadata, source attribution, optional database_row detail) and the data source (CMS HCRIS cost reports). No contradiction or missing safety disclosure is apparent.

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 four sentences with no fluff. It front-loads the use case, lists outputs, provides a concrete example, and cites the source—all in a compact structure. Every sentence earns its place.

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?

Given there is no output schema, the description must explain return values and does so by naming the key output components and source. It also provides an example for concrete understanding. It lacks detailed shape or format of the returned objects, but for a benchmark tool with good annotations and clear purpose, it is sufficiently complete for agent invocation.

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 0%, so the description bears the burden of explaining parameters. It does mention 'by bed size, state, and hospital type' and gives an example ('300-bed acute care hospital in Illinois'), which partially compensates. However, it does not specify formats (e.g., state as abbreviation vs full name, bed_size as number) or clarify which parameter controls the optional database_row detail, leaving meaningful gaps.

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 benchmarks hospital operating costs against CMS peer cohorts and returns specific outputs like peer_group context, benchmark_percentiles, metadata, and source attribution. The verb 'benchmarking' plus resource 'hospital operating costs against CMS peer cohort' distinguishes it from sibling tools focused on other benchmarks (ASC, supply chain, etc.).

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 when to use it: 'when benchmarking hospital operating costs against CMS peer cohort or preparing a healthcare CFO board presentation.' It does not mention alternatives or exclusions, but the use case is clear and distinct from sibling tools, which earns it a 4.

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