cdc_places_health

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

Annotations already declare readOnly, idempotent, open-world, and non-destructive behaviorikuha. The description adds beyond annotations by stating 'Returns crude prevalence (%) by county' and identifying the data as BRFSS-based estimates. This gives the agent concrete output-format and source-quality context without contradicting the 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 front-loaded with the core action and scope, followed by a compact, exhaustive measure list and a single closing sentence about return format. The measure enumeration earns its length because it compensates for the incomplete schema enum; there is no filler.

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 description appropriately states the return type and unit ('crude prevalence (%) by county'). It fully enumerates available measures and implies filtering through the schema's state/measure parameters. Minor gaps like county identifier format and pagination behavior do not prevent correct selection and invocation.

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?

Although schema description coverage is 100%, the description adds value by listing all 27 measure IDs, far more than the schema's truncated measure list. It also clarifies the output unit ('crude prevalence (%)') and the county-level domain. This materially enriches the sparse schema parameter descriptions.

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 opens with 'Get county-level health indicators from CDC PLACES', combining a specific verb, resource, and geographic scope. The county-level qualifier distinguishes it from sibling tools like cdc_places_city, and the long measure list makes the data domain unmistakable.

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 clearly frames this as a county-level CDC PLACES indicator tool, which implicitly tells an agent when to reach for it versus cdc_places_city or general CDC query tools. It does not name alternative tools or explicitly state exclusions, but the county-level scope is a strong contextual signal.

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