cdc_mortality_rates

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

Annotations already declare readOnlyHint=true, so the safe read-only nature is known. The description adds useful context by noting the data is 'provisional' and specifying the time range (2020–present), but it does not disclose behaviors like pagination, rate limits, or how the limit parameter affects results. No contradiction exists, but the description adds only moderate transparency beyond 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 two sentences with no fluff. The first sentence front-loads the core function and scope; the second provides concrete examples and return fields. Every sentence contributes meaningful information, and the structure is easy to scan.

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 four fully described parameters, a readOnly annotation, and no output schema, the description does a reasonable job of filling gaps by naming the return fields (rate_overall, rate_sex_female, rate_sex_male, per-state rates). It lacks explicit detail about the 'limit' parameter's behavior, but the schema covers that. Overall, the description combined with schema provides sufficient context for correct 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?

The schema already provides 100% coverage of all four parameters with clear descriptions, including valid cause options, quarter format, and rate_type enum. The description's list of causes partially duplicates the schema and adds no new parameter-level syntax. Its mention of output fields (rate_overall, etc.) is useful but pertains to response structure, not parameter semantics. Baseline of 3 is appropriate.

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 uses the specific verb 'Get' and identifies the exact resource: provisional age-adjusted death rates by cause, sex, and state with a quarterly temporal scope. It lists concrete example causes and names return fields, making the tool's purpose unmistakable. Though it doesn't contrast with sibling CDC tools, the specific resource and scope distinguish it effectively.

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 clearly defines the tool's coverage (quarterly, 2020–present, by cause/sex/state), so an agent knows when this data will apply. However, it does not explicitly mention alternatives like cdc_death_rates_historical or cdc_weekly_deaths, nor provide exclusion criteria. The context is clear but lacks direct 'use this instead of X' guidance.

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