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

Annotations already declare readOnly/idempotent/non-destructive, and the description adds real behavioral context: the heat score is shrunk toward the platform average to prevent one lucky job from ranking high, and it instructs reading heat alongside confidence. It stops short of describing pagination or window semantics, but that is minor given the annotation coverage.

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?

Purpose is front-loaded in the first clause and each subsequent clause adds a distinct measure or caveat rather than restating. The single long sentence is dense and readable, though slightly packed relative to the minimal information an agent strictly needs.

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 carries the full burden of explaining returns and does so: jobs, applicants, reply share, median first-response hours, heat, and confidence. Combined with 100% schema coverage on the four filters, an agent has everything needed to call and interpret this tool.

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%, so the baseline is 3, but the description adds interpretive meaning beyond the schema — how heat/confidence relate and why the shrinkage matters — which informs the sort and confidence parameters. It does not add syntax or format detail beyond the schema, so it stays below a 5.

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?

Opens with a specific verb and resource ('Find which US cities are actually converting') and enumerates the concrete measures returned (jobs posted, locals applied, reply share, median hours to first applicant). It explicitly names and differentiates itself from the sibling check_service_availability, so an agent can choose between them without opening schemas.

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?

States the decision this tool informs ('decide where supply is dense (spend more) versus where jobs go unanswered (a supply hole)') and names the alternative tool plus the axis on which they differ (counting locals vs measuring whether they respond). Both when-to-use and the sibling comparison are present.

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