Generate a complete due-diligence report for a Czech IČO. Returns company facts (name, address, legal form, VAT status, bank accounts), statutory body with per-member sanctions check, and a transparent risk score with all triggered red flags.
| Name | Required | Description | Default |
|---|---|---|---|
| ico | Yes | Czech IČO — 7 or 8 digits. | |
| depth | No | basic = ARES + sanctions only; full = + ISIR insolvency + virtual-address probe. | basic |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true and openWorldHint=true, establishing a safe read-only snapshot. The description adds context about the report contents, such as per-member sanctions check and a transparent risk score with triggered red flags, but does not disclose API limitations, data sources, or response size. This adds moderate value beyond the annotations.
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?
Two sentences, front-loaded with the main purpose, then the report contents. Every word earns its place; no filler or repetition.
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?
With no output schema, the description compensates by listing the main report sections, giving an agent a clear expectation of company facts, statutory body details, and risk score. It omits exact output formatting or risk score scale, but for moderate complexity, this is fairly complete.
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?
Schema coverage is 100%, and the schema provides excellent parameter descriptions: ico format ('7 or 8 digits') and depth enum ('basic = ARES + sanctions only; full = + ISIR insolvency + virtual-address probe'). The tool description adds no parameter information, so the schema carries the burden; baseline of 3 applies.
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?
Description opens with 'Generate a complete due-diligence report for a Czech IČO' – a specific verb, resource, and country scope. It enumerates report sections (company facts, statutory body, risk score), distinguishing it from sibling tools like get_eu_dd_report or get_risk_score.
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 clearly sets the context: use for Czech IČO to generate a complete due-diligence report. It does not explicitly mention when to use this over alternatives like get_risk_score or get_eu_dd_report, so it lacks exclusions, but the country and scope are well defined.
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.