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ARM Verify — Entity Intelligence API

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screen_sanctions

Screen a company or person against consolidated government sanctions lists and a politically-exposed-person dataset. RETURNS JSON with: screening_result (one of "MATCH", "POSSIBLE_MATCH", "CLEAR"), risk_level ("CRITICAL" for a confirmed match, "HIGH" for a possible match, "LOW" when clear), recommendation ("DO_NOT_PROCEED", "ENHANCED_DUE_DILIGENCE" or "PROCEED"), matches (array, each with list, matched_name, confidence as a percentage string such as "100%", type and id), pep_screening (separate PEP verdict with its own matches), sanctions_lists_checked, total_entries_screened, data_freshness (ISO timestamp of the last refresh) and screening_date. SOURCES: OFAC SDN (US Treasury), UN Security Council Consolidated List, EU Financial Sanctions List, and the UK FCDO UK Sanctions List (UKSL) — approximately 32,600 designations in total, plus roughly 1,000,000 PEP names from OpenSanctions. All lists are re-downloaded from the official government endpoints daily at 03:00 UTC. USE WHEN you must clear a counterparty before payment, onboarding, or any transaction with sanctions exposure. Called via MCP — usage is logged but not billed. For metered billing use the REST API with an API key.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
countryYesISO 3166-1 alpha-2 country code of incorporation, residence or principal operation, uppercase. Examples: "RU", "IR", "GB", "AE". Recorded on the screening report for audit purposes; screening itself runs against every list regardless of country.
thresholdNoMatch confidence threshold 0.5-1.0. Default 0.75. Lower values catch more potential matches; higher values reduce false positives. MATCH requires >=0.90 regardless of threshold.
entity_nameYesFull name of the company or individual to screen. Examples: "Rosneft", "Gazprom PJSC", "Vladimir Putin". Matching is token-based and case-insensitive, and also searches recorded aliases and a.k.a. names.
entity_typeNoWhether the subject is a legal entity or a natural person. Accepts exactly "company" or "individual". Defaults to "company" when omitted.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changed
    • addedInput schema / properties / threshold
      Added value: +{
+  "description": "Match confidence threshold 0.5-1.0. Default 0.75. Lower values catch more potential matches; higher values reduce false positives. MATCH requires >=0.90 regardless of threshold.",
+  "maximum": 1,
+  "minimum": 0.5,
+  "type": "number"
+}
  2. Changed3 schema fields changed
    • changedInput schema / properties / country / description
      Previous value: -"Country of incorporation or operation"New value: +"ISO 3166-1 alpha-2 country code of incorporation, residence or principal operation, uppercase. Examples: \"RU\", \"IR\", \"GB\", \"AE\". Recorded on the screening report for audit purposes; screening itself runs against every list regardless of country."
    • changedInput schema / properties / entity_name / description
      Previous value: -"Entity name to screen"New value: +"Full name of the company or individual to screen. Examples: \"Rosneft\", \"Gazprom PJSC\", \"Vladimir Putin\". Matching is token-based and case-insensitive, and also searches recorded aliases and a.k.a. names."
    • changedInput schema / properties / entity_type / description
      Previous value: -"Type of entity"New value: +"Whether the subject is a legal entity or a natural person. Accepts exactly \"company\" or \"individual\". Defaults to \"company\" when omitted."
  3. Changed3 schema fields changed
    • addedInput schema / properties / country / description
      Added value: +"Country of incorporation or operation"
    • addedInput schema / properties / entity_name / description
      Added value: +"Entity name to screen"
    • addedInput schema / properties / entity_type / description
      Added value: +"Type of entity"
  4. Changed3 schema fields changed
    • removedInput schema / properties / country / description
      Removed value: -"Country of incorporation or operation"
    • removedInput schema / properties / entity_name / description
      Removed value: -"Entity name to screen"
    • removedInput schema / properties / entity_type / description
      Removed value: -"Type of entity"
  5. First observed

TDQS

A4.5/5.0
Behavior5/5

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

With no annotations provided, the description carries the full behavioral burden and does so thoroughly. It discloses the return shape, the specific sanctions lists, approximate dataset sizes, daily refresh time, matching behavior like token-based/case-insensitive matching, and billing distinction between MCP logging and metered REST API usage.

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?

The description is long but every section earns its place: action, return contract, data sources, freshness, use case, and billing. It is front-loaded with the core purpose and output, and the additional details are structured in clearly separated sentences rather than as an unstructured wall of text.

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?

The description is complete for a tool with no output schema: it enumerates all return fields, their possible values and types, source lists, update schedule, expected dataset scale, and invocation context. An agent has enough information to decide when to call it and to interpret its result without guessing.

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?

The input schema already provides 100% parameter coverage with detailed descriptions, examples, and constraints, so the baseline is 3. The description adds overall screening context but does not extend parameter-level semantics beyond what the schema already states.

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?

The description opens with a specific verb and resource: 'Screen a company or person against consolidated government sanctions lists and a politically-exposed-person dataset.' It also defines the use case ('clear a counterparty before payment, onboarding, or any transaction with sanctions exposure'), which separates it from siblings like map_ownership or score_risk by its purpose.

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

Usage Guidelines4/5

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

It explicitly states when to use the tool: 'USE WHEN you must clear a counterparty before payment, onboarding, or any transaction with sanctions exposure.' It gives a clear context but does not name sibling tools or state when not to use it, so it stops short of full alternative-based guidance.

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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