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

Annotations already declare readOnlyHint, idempotentHint, and openWorldHint, yet the description adds substantial context beyond them: API key/OAuth requirement, per-minute and slow-lookup rate limits by tier, 1-lookup-per-call cost accounting, 120s cold-start latency, partial-failure semantics (status failed with retryable, unavailable_types), and a full error taxonomy. It stops short of describing pagination or ordering guarantees beyond 'nearest first', but the behavioral disclosure is well above the annotation baseline.

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?

Front-loaded with purpose, then organized into Selection/Output/Cost/Behavior/Errors blocks, all of which earn their place for a tool with this much behavior. It is dense and a few clauses (e.g. radius flagging) restate schema text, keeping it from a 5, but there is little true 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 carries the return-shape burden and does so: nearest-first ordering, per-feature fields (type, label, category, status, distance in m/km/mi, source, name, attributes, within_radius), plus partial-failure and error handling. Given 7 params and a rich behavioral surface, nothing an agent needs to call it correctly is missing.

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%, so the baseline is 3, but the description adds real semantics the schema does not: how features and categories combine, that neither yields 14 defaults, and that synonyms are resolved. It also reinforces that radius_m flags rather than filters. These additions justify moving above baseline.

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+resource: 'Find the nearest mapped feature of each requested type to one US point or address', and enumerates the 7 categories so an agent knows the scope immediately. It also distinguishes itself from the sibling fetch_location by stating that fetch_location returns non-distance facts at the point.

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?

Explicitly routes between siblings ('fetch_location returns non-distance facts...; ask may call this tool') and gives selection rules for its own inputs: features and categories combine, synonyms are accepted, and 14 default types apply when neither is given. The conditions that select this tool versus alternatives are stated, not implied.

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