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Dilisense Check Individual

dilisense_check_individual
Read-onlyIdempotent

Screen a person against sanctions/PEP/criminal watchlists (AML/KYC). Returns matching watchlist records with source type, PEP level, citizenship and sanction details. Example: dilisense_check_individual({ names: "Vladimir Putin", _apiKey: "your-key" })

Input Schema

NameRequiredDescriptionDefault
dobNoOptional date of birth to narrow matches, e.g. "1952-10-07"
fuzzyNoEnable fuzzy/approximate name matching (default true). Set false for exact matching only.
namesYesFull name of the individual to screen, e.g. "Vladimir Putin"
genderNoOptional gender filter: "male" or "female"
_apiKeyYesdilisense API key (free at dilisense.com — 100 calls/month)

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A3.6/5.0
Behavior4/5

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

Annotations already cover the safety profile (readOnlyHint=true, idempotentHint=true, destructiveHint=false), so the bar is lower. The description adds genuine value by disclosing what the call returns — matching watchlist records with source type, PEP level, citizenship, and sanction details — and clarifies the screening scope (AML/KYC context). 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?

Two sentences plus a compact inline example. The purpose is front-loaded, the return content follows, and the example proves the calling convention — every element earns its place with zero filler.

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 strong schema coverage, robust annotations, and no output schema, the description covers the essentials: what it does, what it returns, and how to invoke it. The main gap is the missing selection guidance relative to dilisense_check_name/dilisense_check_entity, which is already penalized under usage_guidelines.

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 the baseline is 3. The inline example correctly demonstrates the required params (names and _apiKey) and one representative optional param (dob), adding minor value, but the description itself adds no parameter meaning beyond what the schema already documents.

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?

"Screen a person against sanctions/PEP/criminal watchlists (AML/KYC)" gives a specific verb and resource, and the concrete Putin example anchors it. It implicitly distinguishes from sibling dilisense_check_entity via "a person", but does not explicitly differentiate itself from dilisense_check_name, leaving an ambiguity an agent would have to resolve.

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

Usage Guidelines2/5

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

No when-to-use or when-not-to-use guidance is provided. The description never mentions how this differs from dilisense_check_name or dilisense_check_entity, nor any conditions that should route an agent to those alternatives. The inline example shows call syntax but not selection criteria.

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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