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get_aml_regulatory_benchmark

Read-only

AML regulatory benchmarks — FinCEN SAR filing rates, OFAC SDN counts and recent additions, BSA enforcement fine history, travel rule thresholds, and compliance staffing benchmarks. For compliance agents and financial institution risk officers. $0.50 USDC per call.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
focusNo
institution_typeNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. Added

TDQS

A3.5/5.0
Behavior3/5

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

Annotations already declare readOnlyHint=true and destructiveHint=false, and the description is consistent with them. It adds useful context such as the per-call cost ('$0.50 USDC per call') and data coverage, but it does not describe return format, data freshness, or update behavior.

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

Conciseness5/5

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

One tightly worded sentence front-loads the core resource, itemizes the data coverage, names the audience, and states the price. There is no filler or redundant information.

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

Completeness3/5

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

With no output schema and no parameter descriptions, the description gives the essential data scope and cost but omits return-value structure, parameter mapping, and data-cadence details. It is minimally viable for an unfiltered default call, but not fully complete for focused queries.

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 0%, so the description must compensate. It implicitly maps to focus enum values: 'BSA enforcement fine history' aligns with 'enforcement', 'FinCEN SAR filing rates' aligns with 'sar_filing', and 'OFAC SDN counts' aligns with 'ofac'. However, it never names 'focus' or 'institution_type', leaving part of the parameter semantics to inference.

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?

The description opens with 'AML regulatory benchmarks' and itemizes concrete data categories: 'FinCEN SAR filing rates, OFAC SDN counts and recent additions, BSA enforcement fine history, travel rule thresholds, and compliance staffing benchmarks.' This clearly identifies the resource and its scope, distinguishing it from screening tools like get_ofac_sanctions_screening, though it is phrased as a noun phrase rather than an explicit action verb such as 'retrieves'.

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?

The audience line 'For compliance agents and financial institution risk officers' gives context, but the description does not explicitly state when to use this tool versus sibling alternatives or provide exclusions. The usage is implied by the content list rather than directly guided.

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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