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

Annotations already declare readOnlyHint=true, idempotentHint=true, openWorldHint=true and destructiveHint=false, so the safety profile is fully covered without the description. The description adds real value by enumerating the returned fields, which matters since no output schema exists. It does not mention pagination, row limits, or coverage/recency of the underlying dataset, so it stays at minimum-viable on behavior.

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, no filler: the first identifies the dataset and covered report categories, the second lists return fields. Everything is front-loaded and each clause carries information an agent would otherwise have to open the schema or a data dictionary to obtain.

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?

With no output schema, the second sentence's field list is exactly the compensating detail needed, and the annotations cover mutability and idempotency. For a simple read-only filterable dataset query with fully documented parameters, this is close to complete; only dataset coverage/recency and pagination behavior are unaddressed.

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%, and the schema documents all four parameters (year, limit with default 50 and 1-1000 bounds, state as full name, etiology with examples). The description's mention of date, state, etiology and exposure adds naming color but no semantics beyond what the schema already states, so the 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 names a specific resource (CDC NORS foodborne/waterborne/enteric outbreak reports) with a dataset identifier, which distinguishes it from the generic cdc_dataset_query and from unrelated cdc_* siblings like cdc_flu_surveillance or cdc_drug_overdose_deaths. It also enumerates the returned columns, so the agent knows exactly what the tool yields. The only weakness is that no sibling is named explicitly as an alternative.

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?

There is no statement of when to use this tool versus alternatives such as cdc_dataset_query or the other cdc_* tools, and no prerequisites or exclusions are given. Usage can only be inferred from the resource name. The agent is left to guess whether this is the canonical path for outbreak data or a fallback to a generic CDC query tool.

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