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AnChainAI
by AnChainAI

search_ofac

Search the OFAC sanctions list to find exact matches for individuals, entities, vessels, or aircraft using names, crypto wallet addresses, and other identifiers.

Instructions

Search the OFAC sanctions database using exact field matching across names, identifiers, and related attributes.

Args: type: Entity type (individual, entity, vessel, aircraft) name: Full name first_name: First name (for individuals) last_name: Last name (for individuals) id: Crypto wallet addresses or identification numbers address: Street address city: City name state: State or province country: Country or nationality

Cost: 10 credits

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
idNo
cityNo
nameNo
typeNo
stateNo
addressNo
countryNo
last_nameNo
first_nameNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Behavior3/5

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

With no annotations, the description carries the full burden. It discloses the exact-match behavior and cost (10 credits), which is useful. However, it does not clarify whether fields are combined with AND/OR, whether at least one parameter is required, or the behavior when no filters are provided. These are meaningful gaps for a search tool with all-optional parameters.

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 front-loaded with a clear purpose statement, followed by a compact parameter list and cost note. Every line serves a purpose; 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?

The description covers purpose, parameters, and cost, and the output schema exists to explain return values. However, it omits guidance on how to combine multiple filters and whether an empty search is valid. Given the tool's complexity (9 optional parameters), this leaves some ambiguity around invocation patterns.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters5/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%, but the description compensates fully by explaining each parameter: type, name, first/last name, id, address, city, state, country. It even provides examples for type and id, adding real semantic value beyond the bare schema field names.

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?

Description clearly states the verb ('Search'), the resource ('OFAC sanctions database'), and the method ('exact field matching'), which distinguishes it from fuzzy siblings like fuzzy_search_ofac. It is specific and immediately understandable.

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 phrase 'exact field matching' gives clear context for when to use this tool over fuzzy alternatives, though it does not explicitly name alternatives or state when not to use it. The sibling 'fuzzy_search_ofac' is implied as the contrasting choice, so usage context is clear but not fully explicit.

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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