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by dev.cz-agents

detect_nominee_director

Read-only

Detect "white horse" / nominee director patterns — 3 surface indicators (age outlier, multi-board membership, recent appointment) computable from ARES data alone. Returns indicator breakdown with riskScore 0-100. Pro Compliance tier or higher. For 8-indicator deep analysis including ISIR cross-reference, sanctions, address crowding and phoenix pattern, see detect_nominee_director_rich in @czagents/ddplus.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
icoYesCzech IČO — 7 or 8 digits.

TDQS

A4.5/5.0
Behavior4/5

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

Annotations already indicate readOnlyHint and openWorldHint. The description adds context about the return format (indicator breakdown with riskScore 0-100), the data source (ARES data alone), and an access tier requirement, going beyond the annotations without contradicting them.

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 sentences, front-loaded with the purpose, and includes all relevant details without any fluff. Every sentence earns its place.

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 single-parameter, read-only tool with no output schema, the description covers purpose, indicators, return summary, access tier, and alternative tool. It is complete and self-contained.

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?

The input schema already fully describes the only parameter (ico) with format details. The description does not add parameter-specific information, so the baseline of 3 applies since schema coverage is 100%.

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 detects 'white horse' / nominee director patterns, enumerates the 3 surface indicators, and distinguishes itself from the deeper detect_nominee_director_rich variant. This leaves no ambiguity about the tool's scope.

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?

It explicitly explains when to use this tool ('Pro Compliance tier or higher') and directs users to detect_nominee_director_rich for deeper analysis with 8 indicators and additional data sources. This provides clear alternatives and context.

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

A4.2/5.0
Disambiguation4/5

Most tools have clearly distinct purposes: address crowding, nominee directors, phoenix patterns, owners, statutory chains, timelines, and watch functionality are all separate. However, get_dd_report and get_risk_score overlap significantly (full report vs. just the score), and the three detect_* tools share a similar pattern but apply to different risk types.

Naming Consistency4/5

Tool names predominantly follow a verb_noun pattern (detect_, get_, watch_), but person_companies breaks this convention (noun_noun). The mix of detect_ and get_ verbs is consistent within their respective semantic groups, making the overall pattern readable.

Tool Count5/5

With 12 tools, the server is well-scoped for a due-diligence domain. Each tool addresses a distinct aspect (risk detection, reports, ownership, monitoring) without unnecessary bloat, and the count sits comfortably within the ideal range.

Completeness4/5

The server covers the core due-diligence lifecycle reasonably well: company facts, risk scoring, timeline, ownership, EU lookup, and monitoring onboarding. Minor gaps exist—watch_entity is a stub, and advanced features are explicitly deferred to a companion server (ddplus)—but these are acknowledged and don't break the primary workflows.

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