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LiveDataLink

by io.github.blackboxfoundry

sanctions_search_alias

Read-onlyIdempotent

Search aliases / AKAs across selected lists. Distinct from screen_entity in that only the alias fields are matched, which is helpful when the primary listed name differs sharply from the popular spelling.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNoMaximum matches to return. Defaults vary per tool.
queryYesAlias / AKA to search for.
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

A4.2/5.0
Behavior3/5

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

Annotations already declare readOnlyHint, idempotentHint, and destructiveHint, so the safety profile is covered. The description adds useful behavioral context by noting that only alias fields are matched, but it does not describe result behavior such as matching semantics, confidence scoring, or output shape. This is adequate but not rich.

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?

Two concise sentences with no filler. The core function is front-loaded, and the sibling differentiation is placed immediately after, giving the most decision-relevant information up front.

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 read-only search tool with complete schema documentation and rich annotations, the description covers the essential functional distinction and use case. It does not describe return values, but no output schema exists and the search nature of the tool makes this a minor gap. Slightly more detail on what 'selected lists' means would push this to fully complete.

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%, so the schema fully documents query, limit, sources, and threshold. The description's mention of 'selected lists' weakly maps to the sources parameter but adds no meaningful syntax or format detail beyond the schema. Baseline 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 clearly states the tool searches aliases/AKAs across specified lists, using a specific verb and resource. It also explicitly distinguishes itself from screen_entity by narrowing matching to alias fields only, making its 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 Guidelines5/5

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

The description names the sibling alternative (screen_entity) and explains the exact condition for choosing this tool: when the primary listed name differs sharply from the popular spelling and alias-field matching is desired. This gives an agent actionable routing 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

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.

Resources