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Sanctions Screening

by io.github.pipeworx-io
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Sanctions Screen

sanctions_screen
Read-onlyIdempotent

Screen a person, company, vessel, or aircraft name against the US restricted-party lists — OFAC SDN sanctions, Sectoral Sanctions (SSI), Chinese Military-Industrial Complex (CMIC), BIS Entity List / Denied Persons / Military End User, State ITAR Debarred, and the DHS UFLPA Entity List for Xinjiang forced-labor import bans (~26k entries, synced daily). Fuzzy name matching with a 0-1 relevance score, matched aliases, programs, addresses, and which list each hit is on. Use for KYB / KYC / AML / export-control checks, and to check whether a supplier is subject to the forced-labor import ban before importing. Returns an empty matches array when the name is clear. Handles CYRILLIC names — Russian, Ukrainian, Serbian: the lists are held in Latin script, so a Cyrillic name is romanised into a small candidate set (both conventions: г as g or h, и as i or y, я as ya or ia) and every form is screened, with matched_form on each hit naming the spelling that produced it. So "Сбербанк" returns the same matches as "Sberbank". A name in a script we do NOT romanise (Greek, Arabic, Hebrew, Han, Japanese, Korean, Devanagari, Thai) still cannot be compared, and is refused with clear:null / screened:false rather than reported clear — pass the Latin transliteration used on the list.

Input Schema

NameRequiredDescriptionDefault
listNoRestrict to one list code: SDN | SSI | CMIC | NS-MBS | CAP | PLC | EL | DPL | UVL | MEU | DTC | ISN | UFLPA.
nameYesPerson, company, vessel, or aircraft name to screen, e.g. "Rosneft" or "Huawei Technologies".
typeNoRestrict by entry type: Entity | Individual | Vessel | Aircraft.
limitNoMax matches (1-50, default 10).
countryNo2-letter country code to filter matches by address/nationality, e.g. "CN", "RU", "IR".

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changed
    • changedInput schema / examples
      Previous value: -[
-  {
-    "name": "Rosneft"
-  },
-  {
-    "country": "CN",
-    "limit": 5,
-    "name": "Huawei Technologies",
-    "type": "Entity"
-  }
-]New value: +[
+  {
+    "name": "Rosneft"
+  },
+  {
+    "name": "Сбербанк"
+  },
+  {
+    "country": "CN",
+    "limit": 5,
+    "name": "Huawei Technologies",
+    "type": "Entity"
+  }
+]
  2. Changed1 schema field changed
    • changedInput schema / properties / list / description
      Previous value: -"Restrict to one list code: SDN | SSI | CMIC | NS-MBS | CAP | PLC | EL | DPL | UVL | MEU | DTC | ISN."New value: +"Restrict to one list code: SDN | SSI | CMIC | NS-MBS | CAP | PLC | EL | DPL | UVL | MEU | DTC | ISN | UFLPA."
  3. Changed1 schema field changed
    • addedInput schema / examples
      Added value: +[
+  {
+    "name": "Rosneft"
+  },
+  {
+    "country": "CN",
+    "limit": 5,
+    "name": "Huawei Technologies",
+    "type": "Entity"
+  }
+]
  4. First observed

TDQS

A4.4/5.0
Behavior5/5

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

Annotations mark the tool as read-only, idempotent, and open-world. The description adds considerable behavioral detail beyond that: fuzzy matching with a 0-1 relevance score, matched aliases/programs/addresses/list attribution, empty matches array for clear names, Cyrillic romanisation into candidate sets with matched_form, and explicit refusal behavior (clear:null / screened:false) for non-romanised scripts. No contradiction with annotations.

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 sentence earns its place: core purpose, list scope, matching details, use cases, clear-result semantics, script handling, and refusal edge case. It is front-loaded with the main purpose and then gives operationally critical details. No filler or redundancy.

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?

There is no output schema, so the description must carry the burden of explaining return values. It covers the key elements: empty matches array, relevance score, aliases, programs, addresses, list attribution, matched_form, and the clear:null / screened:false refusal case. It is sufficient for correct invocation, though a complete output shape or pagination isn't detailed.

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 every parameter is already documented in the input schema. The description adds context about matching behavior and output semantics, but not much extra for individual parameters. It also provides examples (Cyrillic, country, limit), which slightly enrich the param meaning. Baseline 3 holds.

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 states a specific verb ('Screen'), a resource ('person, company, vessel, or aircraft name against the US restricted-party lists'), and enumerates the exact lists covered. This clearly distinguishes it from sibling tools like sanctions_entry and sanctions_lists, which focus on individual entries and list metadata rather than screening a name across all lists.

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?

The description explicitly states when to use the tool: 'Use for KYB / KYC / AML / export-control checks, and to check whether a supplier is subject to the forced-labor import ban before importing.' It also gives a key usage constraint: names in non-romanised scripts are refused, so users should pass the Latin transliteration. However, it does not explicitly name alternatives or exclusions, so it stops short of full when/when-not 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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