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

Annotations already declare read-only, idempotent, non-destructive behavior, so safety is covered. The description adds genuinely useful context beyond that: the data is modeled (not raw counts) and comes from a specific CDC dataset id, which matters when interpreting the numbers.

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?

Three tight sentences, front-loaded with the resource and its scope, with no filler or repetition.

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 read-only query tool with full schema coverage and no output schema, the description covers source, granularity (state and week), and interpretation caveat (modeled estimates). Only the return shape/columns are left unstated, which is a minor gap.

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 description coverage is 100%, with limit, state, and outcome all documented in-schema including examples. The description adds nothing about parameter semantics, so the baseline 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?

Names a specific dataset (CDC excess deaths, dataset id xkkf-xrst) and its scope: modeled expected vs observed deaths by state and week. That is enough to separate it from cdc_weekly_deaths_by_state and cdc_leading_causes_of_death, though it never names those siblings explicitly.

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 closing sentence ('Used to estimate true pandemic impact beyond reported COVID deaths') implies an analytical use case, but there is no explicit when-to-use guidance, no prerequisites, and no named alternative for raw death counts versus excess-death estimates.

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