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EU Business Data (VAT, EORI, company, sanctions, KYB)

screen_sanctions

Screen a person or company name against official EU, UN, OFAC SDN and UK sanctions lists. Fuzzy matching with transliteration; returns candidate matches with 0-100 scores, list, programme, DOB. A potential match needs human review; this is a screening aid, not legal advice.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
nameYes
countryNo
thresholdNo
birth_yearNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A3.8/5.0
Behavior4/5

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

With no annotations, the description carries the full burden and does well: it discloses fuzzy matching with transliteration, the 0-100 scoring model, and the returned fields (list, programme, DOB), plus an explicit human-review requirement. It omits auth/prerequisite and rate-limit behavior, but for a read-only screening operation that is a minor gap.

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?

Three sentences, zero waste, correctly front-loaded: purpose first, then matching/return behavior, then the risk caveat. Every sentence earns its place and nothing is repeated from the schema.

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?

No output schema and no annotations, so the description must cover behavior and returns, which it largely does. But with 4 parameters at 0% schema coverage, the missing explanation of threshold/country/birth_year leaves an agent under-informed on how to construct a correct call.

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

Parameters2/5

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, and it only partially does: the name input is implied by 'Screen a person or company name' and the 0-100 output scores loosely relate to threshold. The country, threshold (default 85), and birth_year parameters are entirely unexplained in both schema and description, leaving three of four parameters opaque.

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?

States a specific verb (Screen) and resource (sanctions lists) and names the exact list sources (EU, UN, OFAC SDN, UK). None of the sibling tools (verify_vat, verify_eori, lookup_company, kyb_check) do sanctions screening, so an agent can route unambiguously without opening the schema.

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 intended scenario is implied (screen a person/company name) and the description adds the key operational caveat that a match needs human review and is a screening aid rather than legal advice. However, it never names alternatives or states when NOT to use this tool (e.g., vs kyb_check for broader KYC), leaving selection guidance to inference.

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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