datasets_google_map_nearby

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

With no annotations provided, the description carries the burden of behavioral disclosure. It goes beyond the schema by explaining the meaning of `rating: null` (no aggregate rating), `review_count: null` (Google didn't return a count) vs. `0` (confirmed zero reviews), and the effect of `min_rating` on unrated businesses. It also cautions about category localization/non-ASCII values. This is valuable behavioral context, though it does not mention pagination behavior or sorting, so a perfect score is not warranted.

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 purpose in the first sentence, followed by targeted guidance on category filtering and null semantics. It uses four sentences with no redundant filler. It is slightly longer than necessary, and the rating/review_count explanation could be tightened, but every sentence contributes useful information.

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?

Given the tool's moderate complexity (8 parameters, no output schema), the description covers key nuances: the target dataset, category exactness, and rating/review_count interpretation. It does not describe the result items' structure, but this is somewhat mitigated by the dataset context. It is reasonably complete but would benefit from a note about pagination or the relationship to `datasets_google_map_item`.

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?

The input schema already provides descriptions for all 8 parameters (100% coverage), so the baseline is 3. The description adds some context about `category` (localized, non-ASCII, punctuation) and `min_rating` behavior, but these largely overlap with schema descriptions. The description also focuses on output fields (rating, review_count) rather than parameter semantics, so it adds limited value beyond the structured schema.

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 a specific verb and resource: 'Search nearby stored Google Maps businesses.' It clearly identifies the dataset (`google-map-businesses`), the coordinate-based search, and implicitly distinguishes from sibling tools like `datasets_google_map_search` (text search) and `datasets_google_map_item` (single item retrieval). This is a precise, differentiating statement.

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 provides clear context on when to use this tool (search businesses near a coordinate) and includes practical usage guidance for the `category` parameter (use the category facet to discover exact labels) and `min_rating` semantics (excludes unrated businesses). However, it does not explicitly name alternative tools or state when not to use this tool, so it falls short of a full 5.

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