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Counterparty Risk Rollup

counterparty-risk-rollup
Read-only

Screen a counterparty in one call: OFAC + EU sanctions match, GLEIF legal-entity registry, litigation history (US/UK/PL) and a hiring signal from public ATS boards, combined into one row per company with a documented risk score. Keyless sources only. — $0.03/call, x402 (USDC on base).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
checksNoWhich of the four checks to run per company. Sanctions and registry are fast (shared cached list + one API call); litigation and hiring each add one more API call per company.
companiesYesCompany legal names to assess, one per row (a Legal Entity Identifier is also accepted for the registry check). One dataset row comes out per company, combining every check you selected below.
maxConcurrencyNoHow many companies to assess in parallel.
jurisdictionHintNoOptional ISO country code, e.g. "GB", "DE", "PL". Narrows the registry lookup to that country and picks which litigation source is queried (GB/UK -> UK case law, PL -> Poland SAOS, anything else -> US CourtListener, the default). "UK" is accepted as a synonym for "GB" everywhere — it is normalized to the ISO code "GB" before it reaches the registry (GLEIF) lookup, since GLEIF itself only recognizes "GB".

TDQS

A4.2/5.0
Behavior4/5

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

Annotations already declare readOnlyHint=true and destructiveHint=false, so the safety profile is covered. The description adds valuable context: it names the underlying data sources (OFAC, EU, GLEIF, US/UK/PL litigation, ATS boards), states 'Keyless sources only' (no authentication needed), and reveals pricing/call format ($0.03/call via x402). It also notes the output shape (one row per company with a documented risk score), going beyond annotations.

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 exceptionally concise: two sentences (plus a pricing note) pack in purpose, sources, output shape, keyless requirement, and cost. Every clause earns its place, with front-loaded action ('Screen a counterparty in one call') and no filler. Ideal length for quick comprehension.

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?

The description provides enough context for an agent to decide when and how to call: it names all four checks, notes output structure (one row per company, risk score), and gives critical operational constraints (keyless, x402 payment). However, with no output schema, it could be more explicit about the returned risk-score scale or row format, and it leaves out any mention of concurrency limits or error handling, though these are partially covered in the input schema.

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 baseline is 3. The description does not add parameter-specific semantics; it only restates the high-level checks, which are already detailed in the 'checks' parameter description. The schema already explains companies, maxConcurrency, and jurisdictionHint thoroughly, and the description adds no extra parameter-level guidance.

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 ('Screen') with a clear resource ('a counterparty') and explicitly lists the distinct checks (OFAC/EU sanctions, GLEIF registry, litigation history, hiring signal) combined into one row with a risk score. It clearly differentiates from sibling tools like sanctions-screening or litigation-check by emphasizing the single-call rollup nature.

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 clear context: use this for a consolidated counterparty screening in one call, with keyless sources. It implies when to use it instead of individual sibling tools, but it does not explicitly state exclusions (e.g., 'if you only need sanctions, use sanctions-screening'). The context is sufficient for an agent to infer appropriate usage.

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

A3.8/5.0
Disambiguation3/5

Several tools overlap in signal space: hiring-radar, hiring-trend-index, layoff-tracker, and intent-signal-aggregator all touch hiring; funding-alert vs funding-round-tracker, sanctions-screening vs sanctions-update-alert, and rollup tools vs individual checks create boundary ambiguity. However, each has a distinct output format, so descriptions help.

Naming Consistency4/5

Tool names are consistently lowercase with hyphens and descriptive noun phrases (e.g., company-hiring-radar, litigation-check), but pricing_info breaks the pattern with snake_case and a non-descriptive name.

Tool Count3/5

With 20 tools, the server feels heavy and covers a wide range of premium data services, but each tool does target a distinct data source or workflow, so it's borderline rather than excessive.

Completeness4/5

The surface covers company identity, hiring, litigation, sanctions, funding, and patents well, but lacks direct financials, ownership structure, and general news monitoring beyond funding/layoffs, leaving some sales-intelligence gaps.

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