datasets_google_map_facets

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

With no annotations provided, the description carries the burden of disclosure. It explains that the tool returns terms aggregation counts and warns that category facet values are exact locale-specific labels that may contain non-ASCII characters or punctuation, telling agents to pass them unchanged. This is useful behavioral context, though output structure and edge cases are not detailed.

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 two sentences, front-loaded with the primary purpose, and includes the facet enum and the critical category-value caveat. No wasted words.

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?

The tool has 17 parameters and no output schema, so the description must compensate. It explains the core facet behavior but does not discuss how facets interact with q, filters, sorting, or output details. The rich schema covers parameters, but the description leaves some contextual gaps.

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. The description adds value by enumerating the facet options and specifying that category values must be passed unchanged to the category filter, including non-ASCII and punctuation handling, which goes beyond the schema's 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 clearly identifies the tool's function: faceting stored Google Maps businesses and returning terms aggregation counts. It distinguishes itself from sibling tools like datasets_google_map_search and datasets_google_map_item by focusing specifically on facet counts.

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 implies usage through 'pass a returned value unchanged to the category filter,' but it does not explicitly state when to use this tool versus alternatives or provide exclusionary criteria. No direct comparison with other Google Maps dataset tools is given.

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