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sanctions_screen_address

Read-onlyIdempotent

Match a physical address against listed addresses. Useful for KYC / supplier vetting when the counterparty's name is generic but the address is distinctive.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNoMaximum matches to return. Defaults vary per tool.
addressYesFree-form address string.
sourcesNoRestrict screening to a subset of source lists. Defaults to all four. Allowed: OFAC_SDN, EU_CFSP, UN_SC, BIS_DPL.
thresholdNoMinimum confidence score (0..1) for a result to be returned. Defaults to 0.85.

TDQS

A4/5.0
Behavior3/5

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

Annotations already cover read-only, open-world, idempotent, and non-destructive behavior. The description adds limited behavioral context beyond that, such as the address-vs-name screening nuance, but does not disclose matching semantics, source-list behavior, or result confidence characteristics. No contradiction with annotations exists.

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 short sentences with no filler. The primary action is front-loaded, and the use-case guidance earns its place by helping the agent select the tool.

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 simple read-only screening tool with a clear input schema and annotations, the description provides enough to invoke it correctly. The only notable gap is the absence of an output schema, but the description does not need to explain return values if they are straightforward and the tool purpose is clear.

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 all parameters clearly explained in the input schema. The description adds little parameter-level meaning beyond restating 'physical address' and 'listed addresses', so it appropriately relies on 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?

The description uses a specific verb ('Match') and resource ('physical address') and clarifies the target ('listed addresses'). It clearly distinguishes itself from sibling tools like sanctions_screen_entity by focusing on address-based screening, and adds relevant context for KYC/supplier vetting.

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 gives a clear condition for when this tool is appropriate: 'when the counterparty's name is generic but the address is distinctive.' It does not explicitly name alternative sibling tools or state when not to use it, but the guidance is practical and unambiguous.

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

B3.2/5.0
Disambiguation2/5

Many tools overlap heavily across domains: caselaw_search vs court_case_search vs court_opinion_search, caselaw_citation_lookup vs court_citation_resolver, and a cluster of company due-diligence tools (company_trust_check, counterparty_risk_score, entity_dossier, issuer_diligence_dossier, kyb_aml_evidence_case_file) that all screen a company for sanctions/risk/standing. With 290 tools, an agent will frequently face multiple equally plausible choices for the same user intent.

Naming Consistency3/5

The vast majority of tools follow a clean domain-prefix + snake_case pattern (census_, eia_, fmcsa_, npi_, cfpb_, etc.), but there are notable exceptions: entity_resolve and resolve_entity are reversed duplicates, reg_search (Federal Register) sits next to reg_cfr_search (CFR) with confusingly similar names, and carrier_monitor_recheck deviates from the carrier_vetting_* family.

Tool Count1/5

290 tools is an extreme count under any rubric, far exceeding even the 50+ threshold for the lowest score. While the group-filtering mechanism and meta-tools like list_tool_groups and search_available_datasets mitigate the practical burden, the raw surface is still massively oversized for an agent to select from accurately and efficiently.

Completeness4/5

For a read-only data-aggregation server, coverage is remarkably comprehensive across 59 domains, and generic fallbacks like cdc_dataset_query, eia_series_lookup, fred_observations, and bls_series prevent most dead ends. Minor gaps exist (a single GitHub tool, demo-only property_lookup coverage, no write/update operations anywhere), but the stated data-access purpose is well served.

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