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Professor Sausages — Trust & Verification

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
NameRequiredDescriptionDefault
listNoWhich OFAC list(s) to screen against.all
nameYesName to screen.
typeNoRestrict to one party type.
limitNoMax candidates to return.
min_scoreNoMinimum fuzzy score (0-100) for a candidate to be returned.
x_paymentNoOptional 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

A4.7/5.0
Behavior5/5

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

Since no annotations are provided, the description carries the full burden of behavioral disclosure. It reveals that the tool is paid, requires a two-step x_payment flow, returns match/possible_match/no_match with scored candidates and matching aliases, and guarantees it never gives a 'silent all-clear.' This goes well beyond the schema and gives agents critical behavioral context.

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?

The description is three dense sentences with no fluff. Each sentence earns its place: the first defines what it does and returns, the second explains the payment flow, and the third directs to the pricing tool. Perfectly sized for the complexity.

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?

Despite having no output schema, the description explains the return types and candidate details sufficiently. It also covers the payment flow, which is essential for a paid tool, and mentions the pricing alternative. This is complete for an agent to decide when and how to invoke it.

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 100%, so the baseline is 3. The description adds operational meaning for x_payment (the two-step terms-then-pay flow) and reinforces fuzzy matching for name and min_score. This extra context elevates it beyond the schema alone.

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?

The description clearly states the tool's action ('Fuzzy-screen a name') and specific target ('full OFAC SDN + Consolidated lists'), which distinguishes it from sibling tools like address_screen or vessel_screen. It also specifies the output categories (match / possible_match / no_match), making the purpose unmistakable.

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?

The description provides explicit payment workflow guidance: call without x_payment to get terms, sign, then call again with x_payment. It also points to the free 'pricing' tool as an alternative for viewing all prices. However, it does not explicitly compare against other screening tools (e.g., sanctions_entity) for when to use name screening over entity screening, though the 'name' focus implies this.

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

A4.4/5.0
Disambiguation5/5

Each tool targets a distinct resource or action: sanctions screening for names, addresses, and vessels; verification for domains, emails, IBANs, phones, and URLs; plus clearly separate meta-tools for discovery, pricing, and requests. Even the closely related sanctions_screen and sanctions_entity have clear separation (search vs. detailed record).

Naming Consistency3/5

Most tools follow a [noun]_[verb] pattern (address_screen, email_check, url_screen), but there are deviations: domain_intel and sanctions_entity are noun_noun, find_data and request_data are verb_noun, and pricing is a single word. The mixed conventions are still readable but not fully consistent.

Tool Count5/5

With 12 tools, the server is well-scoped for its trust and verification purpose. It covers a broad range of verification types without becoming unwieldy, and the inclusion of meta-tools (pricing, find_data, request_data) adds valuable functionality without bloat.

Completeness5/5

The surface appears complete for the stated domain: sanctions screening (name, address, vessel), domain intelligence, email/IBAN/phone/URL checks, and supporting discovery/pricing/feedback tools. The request_data tool also provides a mechanism to fill future gaps, making the set comprehensive.

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