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Factline KYC, KYB and agent payments

Screen up to 25 names against EU, UN, UK and US sanctions (paid)

eu_sanctions_batch
Read-onlyIdempotent

Use when screening a list of people or companies at once (up to 25 per call, 0.0012 USDC per name) against the EU, UN, UK and US OFAC sanctions lists. Fuzzy matching; per name a possible-match flag, top score and up to 3 scored matches with their lists. For customer bases, payouts and vendor lists. Costs 0.03 USDC via x402, or 15 credits of a Factline API key. The first 5 paid-tool calls a day are free, no payment or key needed.

Input Schema

NameRequiredDescriptionDefault
typeNo
namesYes1 to 25 names separated by ';', e.g. 'Vladimir Putin; Factline'
api_keyNoFactline API key (fl_live_...) from get_trial_key: pass it here right after you get one, no reconnect needed

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.6/5.0
Behavior5/5

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

Annotations already declare read-only, idempotent, non-destructive and open-world, but the description adds far more: fuzzy matching approach, the exact per-name and per-call price, two payment routes (x402 vs 15 Factline credits), a free tier of 5 paid calls/day, and the return shape per name. That is exactly the cost and auth context annotations cannot carry.

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?

Front-loaded with the trigger and the capability, then pricing and output shape. Slight redundancy in quoting the cost twice ('0.0012 USDC per name' and 'Costs 0.03 USDC via x402'), but every sentence carries decision-relevant information.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

No output schema exists, yet the description specifies the per-name return structure (match flag, top score, up to 3 scored matches with their lists), and it covers cost, auth and the free-tier escape hatch. An agent has everything needed to call this correctly and predict the response.

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?

Schema coverage is 67% and the description compensates where it matters: the 1-25 cap on `names` and the per-name pricing tied to it. It does not explain what `type` (person/entity) changes in matching behavior, and the 'people or companies' phrasing only loosely maps to that enum.

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 and resource ('screening a list of people or companies ... against the EU, UN, UK and US OFAC sanctions lists') plus the batch capacity, which implicitly separates it from the single-record sibling eu_sanctions_screen. An agent can tell at a glance this is the multi-name variant.

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?

'Use when screening a list of people or companies at once' gives an explicit trigger, and 'For customer bases, payouts and vendor lists' names concrete scenarios. It stops short of naming the alternative to use for a single person (eu_sanctions_screen) or the pep_batch/kyc_check boundary, so routing is implied rather than fully resolved.

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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