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Prometiam Risk Intelligence

Screen a name for sanctions

sanctions_screen
Read-only

Screen a person or entity name against 44,000+ active sanctions and export-control designations with trigram fuzzy match. Covers six sanctions lists — EU consolidated, UN, OFAC, the UK Sanctions List (FCDO), the French Registre des gels, and the Australian DFAT Consolidated List (Department of Foreign Affairs and Trade website – www.dfat.gov.au, CC BY 4.0) — plus 11 US export-control lists (BIS Entity List, Denied Persons, Unverified, Military End User; State ITAR-Debarred and Nonproliferation; OFAC SSI, CMIC, MBS, PLC, CAPTA). Refreshed daily. Returns matches with a match score (0–100, by match type as on company search: 100 the name is the query, 80–99 it starts with it, 50–79 it holds the words, under 50 only parts of words), source list, aliases and the country as an ISO code (country_as_listed keeps the spelling as listed); the same entity on several lists is one row per list unless group is entity. Names in non-Latin scripts (Cyrillic, Greek, Arabic and others) are transliterated to Latin letters, in the query and in the listed names, before matching, so a name in its own script and in Latin spelling match the same entity. Use threshold to control match strictness. BETA.

Input Schema

NameRequiredDescriptionDefault
nameYesName to screen.
limitNo
thresholdNoMinimum match-confidence percentage (50–100, default 80).
entity_typeNoRestrict to one entity type. Omit to screen all types.
include_pepNoAlso screen against politically exposed persons (BETA, Spain only, from Wikidata) and return a separate pep block. Membership is by OCCUPATION, not office: 44% of the set has no recorded office and local officials (6,108) outnumber national ones (3,191). Every hit carries positions[], pep_tier and has_current_office — read them rather than treating a match as a determination. Deceased people are never returned (a date of death on Wikidata, or born 100 or more years ago with no recorded death, counts as deceased). Holds no relatives or close associates, so on its own it does not satisfy a FATF PEP obligation.
pep_min_tierNoOnly return PEP hits at or above this tier. Omit to receive every hit, including those with no recorded office.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A3.7/5.0
Behavior4/5

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

Annotations cover the safety profile (readOnly, non-destructive, open-world), and the description adds genuinely new behavior: daily refresh cadence, the exact list coverage, Latin transliteration of non-Latin scripts on both sides of the match, and the one-row-per-list dedup rule. The mention of 'unless group is entity' references a parameter absent from this schema, which mildly muddies the disclosure, and neither rate limits nor the BETA caveat's practical consequences are explained.

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

Conciseness3/5

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

Purpose and match-score rules are front-loaded, but the middle is a bloated enumeration of all 17 lists plus a licensing attribution and dfat.gov.au URL that cost tokens without helping tool selection. Several clauses are run-on and one references a nonexistent 'group' parameter.

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 correctly carries the return contract — match score bands, source list, aliases, ISO country codes, and one-row-per-list behavior — which is exactly what an agent needs to interpret results. The main gap is that pagination via limit is left entirely unexplained for a call that can return up to 100 rows.

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?

With 83% schema coverage the baseline is 3, but the description earns a bump by explaining what the threshold number actually means — the 100/80–99/50–79/under-50 match-type banding gives the agent real intuition for setting it. limit is never discussed in the description, and the include_pep/pep_min_tier semantics live almost entirely in the schema.

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?

Opens with a specific verb and resource — 'Screen a person or entity name against 44,000+ active sanctions and export-control designations' — and names the matching method (trigram fuzzy). It never routes against siblings like sanctions_screen_batch or sanctions_entity, so an agent must infer that this is the single-name variant, but the operation itself is unmistakable.

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 rather than stated: 'Use threshold to control match strictness' and 'Omit to screen all types' tell the agent how to tune an already-chosen call, not when to choose this tool over sanctions_entity or sanctions_screen_batch. No exclusions, prerequisites, or cost/latency guidance are given.

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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