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Handelsregister

by io.github.jkbngb

Find peer companies (incl. cross-border)

find_peers
Read-onlyIdempotent

Companies most similar to a given one - optionally ACROSS THE BORDER. Read-only.

    Parameters:
    - company_id (required): "AT:{fnr}" or "DE:{court}_{type}{number}" (bare national
      ids accepted), from a search card.
    - n (optional, default 10): how many peers per country.
    - cross_border (optional, default false): when true, additionally returns
      ``peers_abroad`` - the companies in the OTHER country whose registered purpose
      is semantically closest to the reference company's activity text.

    Returns {company_id, country, peers_home, home_envelope, peers_abroad?, notes}.
    ``peers_home`` uses the home register's own peer logic (AT: same size class,
    same industry preferred, nearest by Bilanzsumme; DE: semantic-first by registered
    purpose). ``peers_abroad`` is a MEANING-based match, not a size or financial
    benchmark - the honest cross-border comparison given the countries' different
    data depth (see notes). Empty peers_home means the id is unknown or the company
    lacks the data its register ranks by. For a strict filtered list use
    search_companies; for aggregates use the country server's cohort tools.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
nNo
company_idYes
cross_borderNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

TDQS

A5/5.0
Behavior5/5

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

Beyond the read-only/idempotent/destructive annotations, the description richly explains behavioral semantics: empty peers_home indicates an unknown id or missing ranking data, peers_abroad is a meaning-based rather than financial match, and differing data depth between countries is acknowledged. This goes far beyond what annotations alone convey.

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?

The description is well-structured: purpose and read-only status are front-loaded, then parameters, then return semantics, then routing to alternatives. Although detailed, every sentence adds necessary information rather than padding.

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?

Given three parameters, 0% schema description coverage, and the tool's nuanced cross-border behavior, the description covers all needed information: input format, response envelope, empty-result meaning, and when another tool fits. The agent can make a correct invocation decision without further context.

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 parameter section carries full weight. It defines the company_id format with examples, notes that bare national ids are accepted, clarifies n is per country, and explains cross_border's effect on the response. This fully compensates for the schema's lack of parameter documentation.

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 names a specific operation and resource: finding companies most similar to a given one, with optional cross-border peers. It distinguishes itself from siblings by describing what it returns and explicitly pointing to search_companies as the strict-filter alternative.

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?

It explains when to enable cross_border, clarifies that peers_home uses each register's own peer logic, and routes non-peer use cases elsewhere: 'For a strict filtered list use search_companies; for aggregates use the country server's cohort tools.' This is explicit guidance an agent can act on.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

All Handelsregister toolsInspect
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TDQS

A4.8/5.0
Disambiguation4/5

Each tool has a distinct primary purpose, with clear pointers to the right tool for the job. The main possible confusion is between describe_fields/get_coverage and search_companies/search_person, but the descriptions actively disambiguate those boundaries.

Naming Consistency5/5

All tool names follow a consistent lowercase snake_case verb_noun pattern: describe_fields, export_companies_csv, get_company_details, list_events, search_companies. Even ping fits the predictable style as a simple liveness verb.

Tool Count5/5

Eleven tools is well-scoped for a unified company-register facade. Each tool covers a distinct part of the surface: schema, coverage, search, detail, persons, peers, events, statistics, export, and diagnostics.

Completeness5/5

The read-only domain is covered thoroughly: lookup, detail, person search, similarity, event feeds, aggregate stats, and export all exist. Unsupported country-specific features are handled with notices and coverage metadata rather than missing tooling.

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