datasets_bbb_businesses_search

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

No annotations are provided, so the description carries the full burden. It discloses that records come from bbb.org's search/category-browse pages, that the dataset stores a computed A+-F letter-grade rating, and that several detail types are deliberately not embedded. It thus sets correct expectations about data completeness and points to the live detail endpoints for anything absent. It does not disclose pagination beyond the schema's constraint, or authorization/rate-limit behavior, but the data-coverage transparency is unusually good.

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 a single dense paragraph, slightly long, but every sentence earns its place: dataset source, contents, exclusions, routing to detail endpoints, and enums. It front-loads the core action and dataset identity before the caveats and enum lists. The trailing repetition of the enum values that already appear in the input schema is mildly redundant, but as a compact reference it is efficient.

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 search tool with 12 optional parameters, no required params, no output schema, and no annotations, the description is remarkably complete. It explains what data is present, what is missing, where to get the missing data, and how the rating/rank values behave. The main gap is not mentioning the facade/facet sibling (datasets_bbb_businesses_facets) for exploring valid filter values, since the category parameter even says to use facet values.

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 100%, so the baseline is 3; the description adds value above the schema by naming the dataset id enum (`bbb-businesses`) and by explaining the computed rating, the sort enum variants, and the relationship between the rating filter and the rating rank (A+=12 to F=0). The min_rating_rank example ('A- and above' = 10) likewise adds meaning the raw schema lacks. It doesn't walk through every parameter, but it supplements the schema meaningfully where ambiguity was highest.

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 states a specific action ('Search the BBB businesses dataset'), identifies the exact dataset id enum value (`bbb-businesses`), names the source (bbb.org crawl), and lists precisely what fields are present (rating, accreditation, category, contact info, hours, products/services). It also clearly distinguishes itself from the related bbb endpoints by describing what is NOT embedded and where to find that data on demand. This is a strong, specific purpose statement that differentiates it from sibling tools.

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 explains what this search endpoint returns and explicitly states what it does NOT contain (complaints, full reviews, full reasons-for-rating/service-area details), then points to sibling endpoints (bbb-business-complaints, bbb-business-reviews, bbb-business-more-info) as on-demand lookups for those. This is a clear 'use this for record-level search, use those for detail enrichment' routing. It does not, however, contrast this tool with its closest sibling datasets_bbb_businesses_facets, which is a notable omission.

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