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by io.github.jkbngb
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Cohort summary (AT + DE)

get_cohort_summary
Read-onlyIdempotent

Beispiel: „Wie groß ist eine typische GmbH in Vorarlberg?“

Aggregate statistics for a cohort of companies, per country. Read-only.

    Parameters:
    - dimension (required): "gkl" (UGB size class, AT only), "bundesland", or
      "legal_form" (alias size_gkl -> gkl).
    - value (required): the cohort value (e.g. bundesland "Wien", legal_form "GmbH").
    - country (optional, default "all"): "AT" | "DE" | "all".

    Returns {countries, dimension, value, per_country, notices}. ``bundesland`` and
    ``legal_form`` fan out to every supporting country; ``gkl`` is Austrian-only (no German
    size-class facet) and excludes DE with a notice. Each country's own cohort payload sits
    under ``per_country`` (the registers aggregate different metrics, so they are reported
    side by side, not force-merged). For one company use get_company_details; for a filtered
    list use search_companies.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "dimension": "<dimension>",
      "value": "<value>"
    },
    "name": "get_cohort_summary"
  }
}

Input Schema

NameRequiredDescriptionDefault
valueYes
countryNoall
dimensionYes

Output Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. Added

TDQS

A4.5/5.0
Behavior4/5

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

Annotations already declare readOnly/destructive/idempotent, so the safety profile is covered. The description adds genuinely non-obvious behavior: bundesland and legal_form fan out to all supporting countries, gkl is Austrian-only and drops DE with a notice, and per_country results are deliberately not force-merged because registers measure different metrics. That is real added context, though it does not mention limits on cohort size or empty-result handling.

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?

The parameter and return bullets are tight and informative, and the sibling routing is placed last where it belongs. The leading German sample question is evocative but slightly indirect as an opener, and the 'Returns {countries, dimension, value, per_country, notices}' line partly restates the output schema.

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?

With an output schema present the description need not enumerate return fields, and it spends its space instead on cross-country fan-out rules and the AT-only gkl edge case. Combined with rich annotations, an agent has everything needed to choose the dimension/value and interpret the per-country payload.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters5/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%, so the description carries the full burden and does: it enumerates the three legal dimension values with their meanings, notes the size_gkl -> gkl alias, gives concrete value examples ('Wien', 'GmbH'), and documents the country enum and its 'all' default. Nothing about the three parameters is left ambiguous.

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 states a specific operation (aggregate statistics) on a specific resource (a cohort of companies), scoped per country, and explicitly contrasts it with get_company_details and search_companies. An agent can distinguish it from the list/lookup siblings without opening the schema.

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?

It names two alternatives with the condition that selects them: 'For one company use get_company_details; for a filtered list use search_companies.' That is clear routing guidance. It does not address other aggregate-shaped siblings such as benchmark_company, find_peers, or get_event_stats, so the exclusions are incomplete.

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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