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LiveDataLink

by io.github.blackboxfoundry

kyb_aml_evidence_case_file

Read-onlyIdempotent

Assemble a reusable KYB/AML evidence case file for one company. Combines canonical identity and join keys, GLEIF ownership-chain screening, and public-record standing across sanctions, SEC, EPA, and federal awards, with explicit unavailable-source notes and a reviewer checklist. Informational evidence organization, not legal advice or sanctions clearance.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
einNoOptional EIN hint for nonprofit identity.
leiNoOptional 20-character LEI to anchor the ownership chain.
stateNoOptional 2-letter state.
formatNoCase-file format. Defaults to markdown.
tickerNoOptional SEC ticker hint.
companyYesCompany or organization name.

TDQS

A4.4/5.0
Behavior4/5

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

Annotations already indicate read-only, idempotent, non-destructive behavior, so the bar is lower. The description adds useful behavioral context beyond annotations by promising 'explicit unavailable-source notes and a reviewer checklist' and clarifying 'informational evidence organization,' which helps set expectations about the tool's output and limitations.

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 sentences with no filler. The first sentence immediately states the action and key components, and the second delivers a necessary disclaimer. Every clause earns its place despite the dense source enumeration.

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 tool with six parameters and no output schema, the description covers the assembly purpose, the data sources, and output characteristics (unavailable-source notes, reviewer checklist). It does not describe the precise return format, but the mention of components and 'markdown/json' parameter helps partially mitigate that gap.

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

Parameters4/5

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

Schema coverage is 100%, giving baseline 3. The description adds value by framing the optional hints (ein, lei, state, ticker) as 'canonical identity and join keys,' and by linking LEI to 'GLEIF ownership-chain screening.' This provides semantic context beyond the individual schema property descriptions.

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 opens with a specific verb and resource: 'Assemble a reusable KYB/AML evidence case file for one company.' It then enumerates concrete components (canonical identity/join keys, GLEIF ownership-chain screening, sanctions/SEC/EPA/federal awards standing, unavailable-source notes, reviewer checklist), clearly distinguishing it from more generic sibling dossiers like entity_dossier or beneficial_owner_screen.

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 establishes clear context: this tool is for assembling a comprehensive KYB/AML evidence case file for a single company. It also provides an explicit exclusion boundary ('not legal advice or sanctions clearance'), but it does not name specific alternative tools (e.g., sanctions_screen_entity) for narrower use cases.

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