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

Annotations already provide readOnlyHint=true, destructiveHint=false, idempotentHint=true. The description adds context about the scope (1,400+ datasets) and return fields, which is useful. No contradiction with annotations, and it enhances understanding without repeating structured data.

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, extremely concise, front-loaded with the main action and examples. No wasted words, every sentence adds value.

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?

Completeness is high given the schema and annotations. The description covers purpose, scope, return values, and cross-tool usage. For a search tool with full schema description and annotations, no missing critical information.

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 coverage is 100% and schema descriptions already explain query, category, and limit. The description does not add new meaning beyond the schema; it only implies the search action. Baseline 3 is appropriate as per guidelines.

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 it searches CDC health datasets, specifies the count (1,400+), gives example topics (COVID-19, chronic disease, etc.), and explicitly lists return fields (dataset ID, name, description, category). It differentiates from the sibling 'cdc.health.query' by saying 'Use dataset IDs with cdc.query to fetch data'.

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 explicitly instructs when to use this tool (searching for datasets) and then to use 'cdc.query' for fetching data, providing a clear alternative. It also indicates the domain (US Gov).

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