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screen_sanctions

Screen an entity against official OFAC, UN Security Council, EU Consolidated, and UK HMT sanctions lists. Data downloaded directly from government sources.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
countryYesCountry of incorporation or operation
entity_nameYesEntity name to screen
entity_typeNoType of entity

TDQS

A3.7/5.0
Behavior3/5

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

With no annotations, the description carries the behavioral disclosure burden. It does add useful context by stating that the data originates directly from government sources, but it does not indicate whether the tool returns a boolean, a list of matches, or a report, nor does it mention matching behavior or potential side effects.

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 two concise sentences with no wasted words. The core function and target lists are front-loaded, and the data-source note is placed as a meaningful secondary detail.

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

Completeness3/5

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

For a simple screening tool with three parameters, the description is near complete. However, with no output schema and no statement about what the response contains (e.g., matches or a concise screening decision), an agent still has to guess at the expected return behavior.

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%, and all parameter descriptions are adequate, which establishes a baseline of 3. The description adds no extra parameter-level details beyond the schema, so a 3 is appropriate.

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 action ('Screen an entity') and names the exact resources (OFAC, UN Security Council, EU Consolidated, UK HMT sanctions lists). This clearly distinguishes it from sibling tools like map_ownership, score_risk, and verify_entity.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The use case is implied: use this tool when you need to screen an entity against sanctions lists. However, there is no explicit 'use when' statement, no mention of when to use another tool, and no exclusions such as specifying verification or risk scoring are provided.

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

A3.9/5.0
Disambiguation5/5

Each tool targets a distinct intelligence function: ownership mapping, jurisdiction risk scoring, sanctions screening, and entity verification. While some data sources overlap, the purpose and output of each tool are clearly separable.

Naming Consistency5/5

All tool names follow a consistent verb_noun pattern: map_ownership, score_risk, screen_sanctions, verify_entity. The verb clearly indicates the action and the noun clearly indicates the subject, making the naming predictable and intuitive.

Tool Count5/5

Four tools is a well-scoped set for an entity intelligence API. Each tool covers a meaningful and distinct part of the domain without redundancy or bloat.

Completeness4/5

The core entity intelligence workflow is covered: verify the entity, check ownership, assess risk, and screen for sanctions. Minor gaps exist, such as no explicit search/discovery tool or historical monitoring, but the primary lifecycle is complete.

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