datasets_bbb_businesses_facets

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

With no annotations provided, the description carries the behavioral disclosure burden. It explains that the tool returns distribution counts over a specific index (`bbb-businesses` dataset id), and that it honors the same filters as search. This is useful beyond the schema, though it does not detail response shape or pagination.

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 with zero waste. It front-loads the primary action, then immediately lists the enum values and the key behavioral note about sharing search filters. Every sentence earns its place.

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?

For a facets tool with no output schema, the description explains what the tool returns (distribution counts), which filter parameters it accepts, and which facets are valid. It is reasonably complete for its complexity, though the 'honoring the same filters as search' reference assumes the agent already understands datasets_bbb_businesses_search.

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 explicitly naming the facet enum values and confirming that all filter parameters behave the same as in search. This goes beyond simply restating the schema and helps the agent use the `facet` parameter correctly.

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: 'Facet the BBB businesses dataset' with a specific verb and resource. It also enumerates the valid facet enum values (category, state, city, rating, accredited, entity_type, run_id), leaving no ambiguity about what this tool operates on or what it returns.

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 states it 'honoring the same filters as search,' which provides context for when to use this tool versus the sibling datasets_bbb_businesses_search. However, it does not explicitly say when NOT to use it or name alternatives like datasets_bbb_businesses_item, so the usage guidance is implied rather than fully explicit.

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