Distil — Machine-Native Public Data Refinery

Screen Global Sanctions & PEP Lists

get_sanctions_and_pep_screening

Read-onlyIdempotent

Screens corporate entities, contractors, and individuals against US OFAC (SDN), the UK Sanctions List (FCDO), EU Financial Sanctions Files, and the UN Security Council Consolidated List (< 1.2 KB). Uses fuzzy Jaccard string distance to catch spelling variations and aliases, returning immediate compliance verdicts and risk scores. Screens sanctions designations only, not PEP status.

Input Schema

TableJSON Schema

Name	Required	Description
`query`	Yes	Target company name, director name, or entity identifier to screen for statutory sanctions (e.g. 'Sberbank', 'Gazprombank').
`forceFresh`	No	Spend Control: When true, bypasses Edge KV cache and forces a real-time statutory primary registry call (applies 2.5x Freshness Inconvenience Surcharge). Default: false.
`fullResults`	No	Default false returns only the highest-confidence matches (token-bound, capped, fits this tool's advertised <1.2KB budget) with the true total match count always disclosed. Set true to receive every match found instead — for a compliance screening use case, some callers need the complete picture, not a capped subset; the response discloses total match count either way so the caller always knows whether they're seeing the whole list.
`maxAgeHours`	No	Spend Control: Maximum acceptable data age in hours (e.g. 48 for 2 days tolerance). If cache satisfies this, delivers sub-5ms at standard 1.0x Economy rate. Set to 0 to force live primary fetch.
`jurisdiction`	No	Optional jurisdiction filter ('US', 'UK', 'EU', 'UN').

Output Schema

TableJSON Schema

Name	Required	Description	Default
`content`	Yes
`isError`	No

TDQS

A3.7/5.0

Behavior4/5

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

The annotations already declare readOnlyHint, openWorldHint, idempotentHint, and non-destructive behavior, so the bar for additional behavior disclosure is lower. The description adds genuinely useful behavioral context: fuzzy Jaccard matching to catch spelling variations/aliases, immediate verdict/risk-score output, and the explicit exclusion of PEP screening. It does not mention caching, refresh behavior, or spend controls, but those are covered in schema parameter descriptions.

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

Conciseness4/5

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

The description is only three sentences, front-loads the primary purpose, and avoids filler. The phrase '< 1.2 KB' is awkwardly attached to the UN list and reads ambiguously—likely referring to the response budget rather than the list itself. The overall structure is still efficient and well-ordered.

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?

Given rich input schema descriptions, annotations, and an output schema, the description does not need to explain return values or every parameter. It covers the screening subject, the sanctions lists queried, the matching approach, and the output nature. The missing piece is consistency with the tool's 'PEP' name/title, and the ambiguous size constraint, which slightly undermines completeness.

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%, with rich descriptions for all five parameters, including forceFresh, fullResults, maxAgeHours, jurisdiction, and query. The tool description does not add new parameter-level semantics beyond indicating the subject types (corporate entities, contractors, individuals), so the baseline score of 3 is appropriate.

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 clearly states the tool's specific verb and resource: it screens corporate entities, contractors, and individuals against US OFAC, UK FCDO, EU, and UN sanctions lists, returning compliance verdicts and risk scores. It explicitly clarifies that it screens sanctions designations only, not PEP status, which helps differentiate it from sibling tools. However, the tool name and title both prominently include 'PEP', while the description says the opposite, creating avoidable confusion.

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 description implies a clear use case—statutory sanctions screening—and explicitly carves out PEP status as out of scope. It does not name alternative sibling tools or state when another tool should be used instead, such as get_corporate_risk_score. The usage guidance is therefore adequate but mostly implicit.

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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TDQS

A4/5.0

Disambiguation5/5

Each tool maps to a distinct data product: country-specific filings, tender records/search, risk scoring, sanctions screening, and entity graphs. The search/get split cleanly separates discovery from retrieval, and even similar country-specific tools are clearly qualified by region and entity type.

Naming Consistency5/5

All tools use a consistent snake_case verb_noun pattern: get_* for retrieval and search_* for discovery, with country or region qualifiers where applicable. Cross-cutting tools like get_corporate_risk_score and get_tender_intelligence fit the same pattern without feeling out of place.

Tool Count4/5

At 16 tools, the server is slightly above the ideal 3-15 range, but the multi-country, multi-domain scope justifies nearly every tool. The set is heavier than a tightly focused server, yet no tool feels redundant.

Completeness4/5

The set covers the core read-only workflow well: search to find entities or tenders, get to retrieve records, plus analytical tools for risk, sanctions, and tender intelligence. Minor gaps exist, such as no Spanish company registry access and no UK tender search, but these are workable and do not block primary due-diligence workflows.

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