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datasets_bbb_businesses_facets

Facet BBB businesses data by field such as state or city, honoring search filters, to count records and split searches over 10,000 results.

Instructions

Facet the BBB businesses dataset. Returns the values of one field of the BBB businesses index (dataset id enum value bbb-businesses) with the number of records for each, honoring the same filters as search. Facet enum: country, address_country, category, state, city, rating, accredited, entity_type, run_id, alert_title, has_alerts. The country facet is parsed from profile URLs; address_country is derived from business addresses. Both enums are us, ca. Values come most frequent first, 50 per page by default; page through all of them with limit (up to 1000) and offset while has_more is true. The response also returns total (records matching the filters), total_values (distinct values) and missing (records with no value for the facet), so the counts can be checked against the total. Values of the accredited and has_alerts facets are 1 (true) and 0 (false). Use it to split a search that would exceed 10,000 records: facet=state lists every state and province, and facet=city with a state filter lists every city in it.

Input Schema

NameRequiredDescriptionDefault
qNoFull-text match on the business name/category, max 256 characters
cityNoExact city slug as in the profile URL, e.g. san-diego (case-insensitive). Use the values returned by facet=city with a state filter
facetYesFacet enum: country, address_country, category, state, city, rating, accredited, entity_type, run_id, alert_title, has_alerts
limitNoValues per page, 1 to 1000, defaults to 50
stateNoExact 2-letter state or province code as in the profile URL, e.g. tx (case-insensitive). Use the values returned by facet=state
offsetNoValues to skip, 0 or greater, defaults to 0; offset + limit must be <= 10000. Request offset + limit next while has_more is true
ratingNoExact letter-grade rating filter. Enum: A+, A, A-, B+, B, B-, C+, C, C-, D+, D, D-, F
run_idNoExact crawl run id filter, e.g. bbb-20260906. Use the values returned by facet=run_id
countryNoCountry filter, parsed from the profile URL (case-insensitive). Enum: us, ca
categoryNoExact category filter, e.g. Plumber (case-sensitive). Use the values returned by facet=category
accreditedNoAccreditation filter; true keeps only accredited businesses, false only the others
has_alertsNoBBB-alert filter; true keeps businesses whose profile carries at least one BBB alert, false keeps refreshed records with none
alert_titleNoExact BBB alert title filter, e.g. Pattern of Complaint (case-sensitive). Use the values returned by facet=alert_title
entity_typeNoExact entity-type filter, e.g. Limited Liability Company (LLC) (case-sensitive). Use the values returned by facet=entity_type
min_complaintsNoFloor against total_complaints (BBB's three-year complaint count), 0 or greater
address_countryNoCountry filter derived from the business address, separate from the profile-URL country (case-insensitive). Enum: us, ca
min_rating_rankNoNumeric floor against the denormalized rating rank (A+=12 down to F=0), e.g. 10 for 'A- and above'

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed3 schema fields changedv1.17.13
    • addedInput schema / properties / address_country
      Added value: +{
      +  "description": "Country filter derived from the business address, separate from the profile-URL country (case-insensitive). Enum: us, ca",
      +  "enum": [
      +    "us",
      +    "ca"
      +  ],
      +  "type": "string"
      +}
    • changedInput schema / properties / facet / description
      Previous value: -"Facet enum: country, category, state, city, rating, accredited, entity_type, run_id, alert_title, has_alerts"New value: +"Facet enum: country, address_country, category, state, city, rating, accredited, entity_type, run_id, alert_title, has_alerts"
    • changedInput schema / properties / facet / enum
      Previous value: -[
      -  "country",
      -  "category",
      -  "state",
      -  "city",
      -  "rating",
      -  "accredited",
      -  "entity_type",
      -  "run_id",
      -  "alert_title",
      -  "has_alerts"
      -]New value: +[
      +  "country",
      +  "address_country",
      +  "category",
      +  "state",
      +  "city",
      +  "rating",
      +  "accredited",
      +  "entity_type",
      +  "run_id",
      +  "alert_title",
      +  "has_alerts"
      +]
  2. Changed15 schema fields changedv1.17.12
    • changedInput schema / properties / accredited / description
      Previous value: -"Accreditation filter"New value: +"Accreditation filter; true keeps only accredited businesses, false only the others"
    • addedInput schema / properties / alert_title
      Added value: +{
      +  "description": "Exact BBB alert title filter, e.g. Pattern of Complaint (case-sensitive). Use the values returned by facet=alert_title",
      +  "type": "string"
      +}
    • changedInput schema / properties / category / description
      Previous value: -"Exact category filter"New value: +"Exact category filter, e.g. Plumber (case-sensitive). Use the values returned by facet=category"
    • changedInput schema / properties / city / description
      Previous value: -"Exact city filter"New value: +"Exact city slug as in the profile URL, e.g. san-diego (case-insensitive). Use the values returned by facet=city with a state filter"
    • addedInput schema / properties / country
      Added value: +{
      +  "description": "Country filter, parsed from the profile URL (case-insensitive). Enum: us, ca",
      +  "enum": [
      +    "us",
      +    "ca"
      +  ],
      +  "type": "string"
      +}
    • changedInput schema / properties / entity_type / description
      Previous value: -"Exact entity-type filter"New value: +"Exact entity-type filter, e.g. Limited Liability Company (LLC) (case-sensitive). Use the values returned by facet=entity_type"
    • changedInput schema / properties / facet / description
      Previous value: -"Facet enum: category, state, city, rating, accredited, entity_type, run_id"New value: +"Facet enum: country, category, state, city, rating, accredited, entity_type, run_id, alert_title, has_alerts"
    • changedInput schema / properties / facet / enum
      Previous value: -[
      -  "category",
      -  "state",
      -  "city",
      -  "rating",
      -  "accredited",
      -  "entity_type",
      -  "run_id"
      -]New value: +[
      +  "country",
      +  "category",
      +  "state",
      +  "city",
      +  "rating",
      +  "accredited",
      +  "entity_type",
      +  "run_id",
      +  "alert_title",
      +  "has_alerts"
      +]
    • addedInput schema / properties / has_alerts
      Added value: +{
      +  "description": "BBB-alert filter; true keeps businesses whose profile carries at least one BBB alert, false keeps refreshed records with none",
      +  "type": "boolean"
      +}
    • addedInput schema / properties / limit
      Added value: +{
      +  "description": "Values per page, 1 to 1000, defaults to 50",
      +  "type": "integer"
      +}
    • addedInput schema / properties / min_complaints
      Added value: +{
      +  "description": "Floor against total_complaints (BBB's three-year complaint count), 0 or greater",
      +  "type": "integer"
      +}
    • addedInput schema / properties / min_rating_rank
      Added value: +{
      +  "description": "Numeric floor against the denormalized rating rank (A+=12 down to F=0), e.g. 10 for 'A- and above'",
      +  "type": "integer"
      +}
    • addedInput schema / properties / offset
      Added value: +{
      +  "description": "Values to skip, 0 or greater, defaults to 0; offset + limit must be <= 10000. Request offset + limit next while has_more is true",
      +  "type": "integer"
      +}
    • changedInput schema / properties / run_id / description
      Previous value: -"Exact crawl run id filter"New value: +"Exact crawl run id filter, e.g. bbb-20260906. Use the values returned by facet=run_id"
    • changedInput schema / properties / state / description
      Previous value: -"Exact 2-letter state/province filter"New value: +"Exact 2-letter state or province code as in the profile URL, e.g. tx (case-insensitive). Use the values returned by facet=state"
  3. Changed2 schema fields changedv1.17.5
    • addedInput schema / properties / facet / enum
      Added value: +[
      +  "category",
      +  "state",
      +  "city",
      +  "rating",
      +  "accredited",
      +  "entity_type",
      +  "run_id"
      +]
    • addedInput schema / properties / rating / enum
      Added value: +[
      +  "A+",
      +  "A",
      +  "A-",
      +  "B+",
      +  "B",
      +  "B-",
      +  "C+",
      +  "C",
      +  "C-",
      +  "D+",
      +  "D",
      +  "D-",
      +  "F"
      +]
  4. Addedv1.16.0

TDQS

A4.6/5.0
Behavior4/5

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

No annotations exist, so the description must carry the behavioral burden, and it does well: default 50 values per page, limit up to 1000, offset with an offset+limit<=10000 ceiling, paging while has_more is true, and value encoding (1/0 for accredited and has_alerts). It also explains that country is parsed from profile URLs while address_country is derived from addresses. It stops short of stating read-only semantics explicitly, but the disclosure is otherwise thorough.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Front-loaded with purpose, then facet enum, then pagination and return fields, then the routing advice. Dense but well ordered and every sentence carries information; only the slight length keeps it from a 5.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

With no output schema and no annotations, the description still tells the agent what comes back (values with counts, total, total_values, missing) and how to page through everything up to 1000 per request. For a 17-parameter tool this is complete enough to call correctly without guessing.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100%, giving a baseline of 3, and the description adds genuine meaning beyond the schema: facet values are ordered most-frequent-first, the distinction between parsed (`country`) and derived (`address_country`) facets, and how the counts relate to total/missing. This helps an agent interpret the parameters, not just fill them.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

States a specific verb (facet) and resource (BBB businesses dataset), and explains precisely what it returns: the values of one field with per-value record counts. It also anchors the dataset via the enum value `bbb-businesses`, letting an agent distinguish it from the sibling search tools.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Gives an explicit when-to-use (splitting a search that would exceed 10,000 records) plus concrete recipes: `facet=state` for all states/provinces and `facet=city` with a state filter. It also ties back to the search tool by stating it honors the same filters, so the relationship to alternatives is clear.

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

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