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

Annotations already establish this is a read-only, idempotent, non-destructive operation. The description adds the provisional nature, the dataset identifier, and the weekly/state/cause aggregation, but doesn't disclose caveats such as reporting lags or revisions.

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?

Two sentences: the first states what the tool returns, the second gives concrete analytical use cases. No filler or redundancy.

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 simple query tool with fully documented optional parameters and strong safety annotations, the description gives enough context to select and invoke it. It stops short of listing valid cause categories or output columns, but the schema supplies the parameter detail and there is no output schema to elaborate.

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?

Input schema covers all four parameters with descriptions and examples, so the description doesn't need to repeat them. It adds only a generic reference to state and cause, which isn't new semantic value beyond the schema.

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 names the exact resource (CDC weekly provisional deaths NCHS dataset muzy-jte6) and a specific verb ('Returns'). It specifies state-and-cause granularity and ISO week, which clearly distinguishes it from CDC sibling tools about flu surveillance, overdose deaths, or vaccinations.

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?

It provides clear use-case context ('excess-mortality and respiratory-disease seasonality analysis') that helps an agent decide when to call it. It doesn't name alternative tools or state when not to use it, so it misses explicit exclusions.

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