cdc_mortality_rates

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

Annotations already declare the tool read-only, idempotent, and non-destructive. The description adds useful behavioral context by stating the return fields (rate_overall, rate_sex_female, etc.) and the 'provisional' nature of the data, but does not mention pagination behavior or rate limits. It adds value 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: the first states the core function with a front-loaded verb and resource, the second lists causes and return fields. No wasted words, well structured.

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?

The description covers the main return structure and data scope, which is sufficient given the absence of an output schema. It doesn't explain pagination or default behavior when parameters are omitted, but these are minor gaps. The read-only, idempotent nature is already annotated, so the description is fairly complete for an agent to call correctly.

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 input schema already provides full descriptions for all 4 parameters (cause, limit, quarter, rate_type) with examples and defaults. The description adds no additional parameter-specific information, so it relies on the schema. With 100% schema coverage, the baseline score of 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?

The description clearly states the tool retrieves provisional age-adjusted death rates filtered by cause, sex, and state, with a specific time range (quarterly, 2020–present). This distinguishes it from siblings like cdc_death_rates_historical (historical) and cdc_weekly_deaths (weekly).

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 provides context (quarterly, provisional, 2020–present) but does not explicitly state when to use this tool over alternatives like cdc_death_rates_historical or cdc_query. No exclusions or alternative routing is given, so the agent must infer based on the data granularity.

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