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Register change statistics

get_event_stats
Read-onlyIdempotent

Beispiel: „Wie viele Kapitalerhöhungen gab es seit Jahresbeginn in Tirol?“

Aggregate counts of register changes by type and region, per country. Read-only.

    Parameters (all optional): since / until (default last 30 days); bundesland;
    nace_section; nace_division (AT); legal_form (AT); country ("AT" | "DE" | "all").

    Returns {countries, per_country, windows, notices}, each country's block being its
    own {total, by_type, by_bundesland}. Only AT exposes event statistics today; DE is
    reported in notices as not yet available (never as zero). For the individual
    changes use list_events.

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {},
    "name": "get_event_stats"
  }
}

Input Schema

NameRequiredDescriptionDefault
sinceNo
untilNo
countryNoall
bundeslandNo
legal_formNo
nace_sectionNo
nace_divisionNo

Output Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.1/5.0
Behavior3/5

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

Annotations already declare readOnlyHint, idempotentHint and destructiveHint=false, so the description's 'Read-only' is redundant. It does add genuinely useful behavior beyond annotations: the 30-day default window and the crucial rule that unavailable countries surface in notices rather than as zero counts, which prevents misinterpretation.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Front-loaded with purpose and a motivating example, then parameters, then return shape, then the sibling pointer — a sensible ordering. Minor waste: the German example sentence sits slightly awkwardly before the English purpose statement, but no sentence is superfluous.

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?

Despite an output schema existing, the description still sketches the return structure ({countries, per_country, windows, notices}) and explains the per-country block shape, which adds real value for interpretation. The unresolved date format for since/until is the only material omission for a tool with 7 parameters and no schema descriptions.

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?

With 0% schema description coverage, the description must carry the load and largely does: it gives the 30-day default for since/until, flags AT-only applicability for legal_form and nace_division, and enumerates country values (AT|DE|all). The one gap is the expected date format/type for since and until, which remains undefined.

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?

States a specific verb and resource: aggregate counts of register changes by type and region, per country. It distinguishes itself from the sibling list_events by scope (aggregates vs individual changes) and even leads with a concrete example question that anchors the use case.

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?

Explicitly routes the agent to list_events 'for the individual changes' and notes that only AT currently exposes event statistics while DE is reported in notices rather than as zero. It does not contrast against other aggregate siblings like get_cohort_summary, but the primary alternative is named with its selection condition.

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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