agentic-firmenbuch

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Search companies by representative

search_persons

Read-onlyIdempotent

Find which Austrian companies a person represents by entering their name. Returns official Firmenbuch roles such as Geschäftsführung, Vorstand, Prokura, and Aufsichtsrat.

Instructions

Find the companies a person represents (Geschäftsführung, Vorstand, Prokura, Aufsichtsrat) by NAME over the official register roster. Read-only, public data only.

    Parameters:
    - name (required, min. 3 characters): part of the person's name, case-insensitive
      ("Pöpperl", "Christian Pöpperl").
    - limit (optional, default 50, max 200): maximum companies scanned.

    Returns `persons[]` grouped by the exact name found, each with `companies[]`
    ({fnr, name, city, role}). Name equality is not identity: say so when several people
    share a name. Use for "Welche Firmen führt X?"; for a company's own officers use
    get_company_details.

Input Schema

TableJSON Schema

Name	Required	Description	Default
`name`	Yes
`limit`	No

Output Schema

TableJSON Schema

Name	Required	Description	Default
No arguments

Schema Changelog

Changes observed during successful MCP inspections.

First observedv1.0.0Oct 3, 2026

TDQS

A5/5.0

Behavior5/5

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

Annotations already declare read-only/idempotent/destructive, and the description adds genuinely new behavioral facts: the 3-character minimum, case-insensitive matching, that limit caps companies scanned, that results are grouped by exact name found, and the important caveat that name equality is not identity and should be disclosed to users.

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?

Front-loaded purpose sentence, then a compact parameter block, then return shape, then routing. The German legal-form terms and the identity caveat each earn their space; no filler sentences.

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 two-parameter read tool this covers everything an agent needs: input semantics, the shape of the returned persons[]/companies[] structure, the identity caveat, and the sibling routing. Output schema exists, yet the description's return summary adds grouping/equality nuance rather than duplicating field lists.

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: name is required, min 3 characters, case-insensitive, with concrete examples; limit is optional, default 50, max 200 and means maximum companies scanned. Both parameters gain meaning found nowhere in the schema.

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 action (find the companies a person represents) with the register roles covered (Geschäftsführung, Vorstand, Prokura, Aufsichtsrat) and the data source (official register roster). It is clearly distinguishable from sibling get_company_details, which it explicitly names as the inverse lookup.

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?

Gives explicit routing: use this for 'Welche Firmen führt X?' and use get_company_details when the direction is a company's own officers. It also includes a worked query example, so the when-to-use and when-to-use-the-alternative conditions are both covered.

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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