Sausage Trust

OFAC sanctions name screen

sanctions_screen

Fuzzy-screen a name against the full OFAC SDN + Consolidated lists. Returns match / possible_match / no_match with scored candidates and the aliases that matched — never a silent all-clear. Paid: call without x_payment to receive this call's exact terms (amount, asset, network), sign them, then call again with x_payment. The free pricing tool lists every price at once.

Input Schema

TableJSON Schema

Name	Required	Description	Default
`list`	No	Which OFAC list(s) to screen against.	all
`name`	Yes	Name to screen.
`type`	No	Restrict to one party type.
`limit`	No	Max candidates to return.
`min_score`	No	Minimum fuzzy score (0-100) for a candidate to be returned.
`x_payment`	No	Optional signed x402 payment payload (base64, what the X-PAYMENT header carries). Omit to receive the exact payment terms; sign them (e.g. @x402/fetch) and call again with this argument to settle and get the data.

TDQS

A4.4/5.0

Behavior5/5

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

The description discloses key behavioral traits: it returns scored candidates with aliases and never gives a silent all-clear, and it explains the two-step payment process. Since no annotations are provided, the description carries the full burden and does so comprehensively.

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, front-loaded with the core function, then returns behavior and payment workflow. No filler or redundancy.

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 the absence of annotations and output schema, the description provides essential context: result types, payment terms, and a pointer to pricing. The schema covers parameter details, so the description is adequately complete for the tool's complexity.

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?

All six parameters have schema descriptions (100% coverage), so the baseline is 3. The description adds context about the payment flow for x_payment and the result types, but does not add significant new details beyond the schema.

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?

Clearly states the tool's function with a specific verb ('fuzzy-screen') and resource ('name against OFAC SDN + Consolidated lists'), and differentiates from sibling tools like address_screen and email_check by focusing on name screening. Mentioning the output classification (match/possible_match/no_match) further clarifies its purpose.

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?

Provides clear context for when to use this tool—when you need to screen a name against OFAC lists. It also gives explicit guidance on the payment workflow and points to the free pricing tool as an alternative for price discovery. However, it does not explicitly exclude other tools or list alternatives like sanctions_entity.

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

A4.2/5.0

Disambiguation5/5

Each tool targets a distinct resource type (crypto address, domain, email, IBAN, phone, URL, vessel, entity name) or a distinct purpose (pricing, data discovery, data request). Overlapping sanctions tools are clearly differentiated by target: address_screen for addresses, sanctions_screen for names, vessel_screen for vessels, and sanctions_entity for detailed records after screening.

Naming Consistency3/5

Most data-check tools follow a consistent object_verb pattern (e.g., address_screen, email_check, phone_check). However, find_data and request_data invert the order, domain_intel uses a noun instead of a verb, and pricing stands alone as a gerund, creating mixed conventions.

Tool Count5/5

12 tools is well within the ideal range for a data-screening server. Each tool covers a distinct verification task, and the additional meta tools (pricing, find_data, request_data) are useful entry points without bloating the core purpose.

Completeness4/5

The server covers a comprehensive set of screening and validation tasks across sanctions, domain, email, phone, IBAN, and URL. It includes a discovery tool (find_data) and a suggestion tool (request_data) to fill gaps, though an IP checker or company registry lookup could be considered minor omissions.

Resources

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