Find the EU/international parent company for a Czech IČO. Looks up the company name in ARES, then searches GLEIF (Global LEI Foundation) for a matching LEI-registered entity. Returns LEI, name, country, and confidence level (HIGH/MEDIUM/LOW). Note: GLEIF covers mid/large international firms; SMEs without an LEI will not be found. Pro Compliance tier or higher.
| Name | Required | Description | Default |
|---|---|---|---|
| ico | Yes | Czech IČO — 7 or 8 digits. |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true, so the safety profile is known. The description adds valuable behavioral context: the two-step lookup (ARES then GLEIF), the return fields (LEI, name, country, confidence), and the GLEIF coverage caveat. This goes 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.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is three sentences with no wasted words. It front-loads the purpose, then concisely explains process, output, and limitations. Every sentence earns its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple single-parameter lookup with no output schema, the description covers all essential aspects: the input type, the step-by-step process, the return fields, the coverage limitation, and the access tier requirement. It is complete for the tool's complexity.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema provides full coverage of the single parameter 'ico' with description 'Czech IČO — 7 or 8 digits.' The description repeats 'Czech IČO' but adds no extra format or syntax details beyond the schema. Baseline 3 is appropriate given high schema coverage.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description starts with 'Find the EU/international parent company for a Czech IČO,' which clearly states the verb and resource. It distinguishes itself from sibling tools by detailing the ARES→GLEIF lookup process and the specific output fields.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description gives clear context: use for finding EU parent companies via ARES and GLEIF. It notes the Pro Compliance tier requirement and the GLEIF coverage limitation for SMEs, which implicitly tells users when not to use the tool. No explicit alternative is named, but the guidance is sufficient.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
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.
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.
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.
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.