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research.ofac-entity-search

Read-onlyIdempotent

Compare a business or organization name with separately named Entity records and aliases in the official OFAC SDN and Consolidated Non-SDN files, returning deterministic candidate scores, program tags, source hashes, and freshness evidence without issuing an allow or block verdict.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
entity_nameYesOrganization or business name to compare with separately named OFAC Entity records
max_resultsNoMaximum candidate records to return after deterministic ranking
minimum_scoreNoMinimum API Acre similarity score to return; this is not OFAC's interactive-search score
include_weak_aliasesNoInclude aliases that OFAC labels weak and warns may create false positives

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
dataYesStructured OFAC entity candidate evidence result
metaYes
serviceYes
versionYes
request_idYesUnique request identifier

TDQS

A4.2/5.0
Behavior4/5

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

Annotations already declare the tool as read-only, idempotent, and non-destructive. The description adds valuable context beyond annotations by stating it 'returns deterministic candidate scores, program tags, source hashes, and freshness evidence without issuing an allow or block verdict,' which clarifies output type and decisional boundaries. This is useful, though not exhaustive.

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 a single sentence but packs all essential information: the action, the source, the output elements, and a critical caveat (no verdict). It is concise without being under-specified, and every phrase contributes meaning.

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?

For a list-search tool with an output schema and strong annotations, the description is complete. It specifies the input type (business/organization), the data source (OFAC SDN and Non-SDN), and the nature of the output. It could mention pagination or rate limits, but these are not essential for core use.

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%, with detailed parameter descriptions (e.g., 'minimum_score' notes it is not OFAC's interactive-search score). The tool description adds no additional parameter context, so it relies on the schema. Baseline 3 applies.

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 uses a specific verb ('Compare') and clearly defines the resource ('business or organization name' against 'official OFAC SDN and Consolidated Non-SDN files'). It also distinguishes itself from sibling tools by naming the exact OFAC dataset and the unique output (candidate scores, program tags, source hashes, freshness evidence), making it unambiguous.

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 clearly implies use for OFAC sanctions list screening against business/organization names, which provides context. However, it does not explicitly state when not to use it or mention alternative tools like research.lei-entity-search, so it stops short of full guidance.

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

A3.8/5.0
Disambiguation4/5

Tools are grouped into clear domain prefixes (crypto, data, developer, document, research, web) and each tool name describes a specific function; however, a few umbrella tools like web.full-audit and data.contract overlap with their more targeted counterparts, creating minor ambiguity.

Naming Consistency5/5

All tool names follow a consistent pattern: a domain prefix, a dot, and a hyphenated lowercase compound name (e.g., crypto.base-block-inspect, web.seo-audit). This makes naming predictable and easy to scan.

Tool Count1/5

At 63 tools, the surface area is very large and exceeds the 50+ threshold for extreme mismatch. While the tools are organized into six domains, the sheer number makes it difficult for an agent to select efficiently, and some tools are bundled combinations of others.

Completeness5/5

Each domain offers a thorough set of operations: crypto covers address, account, block, contract, events, gas, and transaction inspection; data covers cleaning, conversion, schema, and validation; developer covers code review, dependency/license audits, and test generation; research covers SEC, OFAC, GLEIF, and USAspending; web covers extraction, SEO, security, and performance. No obvious dead ends exist for the read-only/inspection purpose.

Resources