interest_by_region

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

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, so safety is covered. The description adds real behavioral value beyond that: the 0-100 normalization relative to the strongest place, the percentage split for multi-term queries, and what include_low_volume does. It does not mention rate limits or pagination, which limits it from a 5.

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 compact and front-loaded, leading with the core purpose before the term-count behavior and parameter semantics. The shorthand 'geo: ... resolution: ...' structure is efficient, though slightly terse for readers unfamiliar with the domain.

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 an output schema present, return values need not be explained, and the description still usefully clarifies the 0-100 scale and percentage semantics. The main remaining gap is the four undocumented parameters, but the core call-correctly information is present for an 8-param read-only 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 0% across 8 parameters, so the description must compensate, and it only covers geo, resolution, include_low_volume, and implicitly keywords. limit, category, property, and timeframe are left entirely undocumented in both places, so the description only partially closes the gap.

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 gives a specific verb+resource ('where a term is most popular') and immediately defines the output unit as places ranked by interest, distinguishing it from siblings like interest_over_time or compare_locations. The one-term vs 2-5-term explanation makes the ranking semantics unambiguous.

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?

It conveys clear usage context: blank geo ranks countries, a country ranks its regions, a region ranks its cities, and how results differ for one term versus 2-5 terms. It does not explicitly name an alternative tool to use instead, so the routing guidance is implicit rather than spelled out.

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