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Compliance Check

by dev.hatchloop

verify_company_record

Read-onlyIdempotent

Free, live lookup of a company official registry record. Queries the GLEIF global LEI registry (primary, 2.6 million legal entities worldwide) and SEC EDGAR (US public companies) to return the official legal name, LEI, entity status, jurisdiction, registered address, and registry authority. Never fabricates: if the company is not found in these free registries, returns an honest not_found with the sources that were queried.

EXAMPLE USER QUERIES THAT MATCH THIS TOOL: user: "Is Apple Inc a real registered company?" -> call verify_company_record({"name": "Apple Inc", "country": "US"}) user: "Look up the LEI for Volkswagen AG" -> call verify_company_record({"name": "Volkswagen AG", "country": "DE"}) user: "Verify this LEI: 529900HNOAA1KXQJUQ27" -> call verify_company_record({"name": "Volkswagen AG", "lei": "529900HNOAA1KXQJUQ27"})

WHEN TO USE: Use when you need to verify that a company exists as a registered legal entity and retrieve its official registry details -- before signing a contract, qualifying a vendor, validating a counterparty, or populating a due-diligence record. Accepts a legal name plus optional country filter or a direct LEI for a precise lookup. WHEN NOT TO USE: Do not use to verify private companies not registered with GLEIF or SEC. Do not use as an exhaustive fraud-detection tool; this is a first-pass existence check against free public registries, not a full KYC screen. COST: free within the daily quota, then $0.02 per call LATENCY: ~800ms

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
leiNoOptional 20-character Legal Entity Identifier for a direct, precise lookup.
nameYesLegal company name to look up, e.g. Apple Inc or Volkswagen AG.
countryNoOptional ISO 3166-1 alpha-2 country filter (e.g. US, DE, GB). Narrows GLEIF results to one jurisdiction.

TDQS

A4.9/5.0
Behavior5/5

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

Annotations already declare readOnly/idempotent/non-destructive, so the bar for added behavioral context is lower but the description still adds significant value: it explicitly states 'Never fabricates' and describes the honest not_found return with queried sources. It also discloses data sources, cost, and latency, giving the agent clear expectations about behavior on failure.

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 well structured with clear sections: core function, examples, WHEN TO USE, WHEN NOT TO USE, COST, LATENCY. Every section contributes unique information, and the core definition is front-loaded. No redundant or tautological content.

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

Completeness5/5

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

For a 3-parameter lookup with no output schema, the description is fully complete: it specifies invocation examples, required and optional parameters, data sources, returned fields, not-found behavior, use cases, exclusions, and cost/latency. An agent has everything needed to select and invoke the tool correctly.

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 description coverage is 100%, so baseline is 3. The description goes beyond the schema by explaining the interaction of parameters: 'Accepts a legal name plus optional country filter or a direct LEI for a precise lookup,' and it includes three concrete example calls mapping user intents to parameter combinations. This adds practical semantics not present in the schema alone.

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: 'Free, live lookup of a company official registry record.' It names the exact registries queried (GLEIF and SEC EDGAR) and the returned fields (legal name, LEI, status, jurisdiction, address, registry authority). It also distinguishes the tool from sanction/compliance siblings by positioning it as first-pass existence verification, not a full KYC screen.

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?

Provides explicit 'WHEN TO USE' with concrete scenarios (before signing a contract, qualifying a vendor, validating a counterparty, populating due-diligence records) and 'WHEN NOT TO USE' with clear exclusions (private companies not in GLEIF/SEC, exhaustive fraud detection). These conditions are sufficient for an agent to decide between this tool and the sibling compliance/sanction tools.

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

A4.4/5.0
Disambiguation4/5

Most tools target clearly distinct compliance subdomains: messaging compliance, sanctions screening, trade restrictions, company verification, and cost preview. The main overlap is between map_trade_restriction and screen_sanctions, since both screen parties against sanctions lists, but their descriptions differentiate trade-level screening from dedicated name screening well enough.

Naming Consistency4/5

Tool names mostly follow a consistent snake_case verb_noun pattern: check_compliance, get_outcome, get_status, preview_cost, screen_sanctions, verify_company_record. self_test is the one minor deviation since it reads more like a noun than an imperative verb_object name, but it does not break the overall pattern.

Tool Count5/5

Eight tools is a well-scoped size for a compliance pre-flight server. Each tool has a distinct role, and the count is neither bloated nor too thin for the apparent domain.

Completeness4/5

The core compliance workflows are covered: messaging pre-flight checks, sanctions screening, cross-border trade restrictions, company registry verification, and cost/status helpers. The main gaps are intentional exclusions like PEP screening, export-control product classification, and consent management, which are documented but prevent the set from being a fully comprehensive compliance suite.

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