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datasets_bbb_scamtracker_reports_facets

Facet the BBB Scam Tracker reports dataset. Returns distribution counts over the stored BBB Scam Tracker reports (dataset id enum value bbb-scamtracker-reports), honoring the same filters as search. Counts are of stored reports.

Instructions

Facet the BBB Scam Tracker reports dataset. Returns distribution counts over the stored BBB Scam Tracker reports (dataset id enum value bbb-scamtracker-reports), honoring the same filters as search. Counts are of stored reports. Facet enum: scam_type, state, country. country enum: USA, CAN.

Input Schema

NameRequiredDescriptionDefault
qNoFull-text match on the report narrative and the business name used, max 256 characters
facetYesFacet enum: scam_type, state, country
stateNo2-letter state or province code of the targeted person
countryNoCountry of the targeted person. Enum: USA, CAN
date_toNoInclusive report-date ceiling, YYYY-MM-DD
max_lossNoCeiling against the reported dollar loss, 0 or greater
min_lossNoFloor against the reported dollar loss, 0 or greater
date_fromNoInclusive report-date floor, YYYY-MM-DD
scam_typeNoExact scam type filter

Schema Changelog

Changes observed during successful MCP inspections.

  1. Addedv1.17.12

TDQS

A3.5/5.0
Behavior3/5

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

No annotations are provided, so the description carries the burden. It discloses the return semantic ('distribution counts over stored reports') and that it shares filters with search, but omits that facet is required and does not state the read-only/non-mutating nature of the operation.

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 the core action and appropriately short. The trailing restatement of the facet enum and the country enum duplicates structured data already in the schema, which is minor waste.

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

Completeness4/5

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

No output schema exists, and the description explains what is returned (counts) plus the available facets, which is the key missing context. Combined with full schema coverage of the input filters, an agent has enough to call this correctly, though a note on required-vs-optional facet handling would complete it.

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

Parameters3/5

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

Schema description coverage is 100%, so the schema already documents all nine parameters. The description merely repeats the facet and country enums already present in the schema and adds no syntax or filtering nuance beyond 'honoring the same filters as search', so the baseline 3 applies.

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

Purpose4/5

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

States a specific verb ('Facet') and resource ('BBB Scam Tracker reports dataset') and clarifies it returns distribution counts rather than records. It distinguishes itself from the record-listing sibling only implicitly by saying it honors the 'same filters as search' without naming the search tool.

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

Usage Guidelines3/5

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

Usage is implied by 'honoring the same filters as search' and the return of counts, which tells an agent this is for aggregation rather than retrieval. However, it never explicitly says when to pick this over datasets_bbb_scamtracker_reports_search or the plain search tool.

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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