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Handelsregister

by io.github.jkbngb

My API usage

get_my_usage
Read-onlyIdempotent

Your own API-key usage across both registers: call count and weighted compute-units, per tool. Read-only.

    Parameters:
    - window (optional, default "today"): "today" | "yesterday" | "month_to_date" |
      "last_30_days" | "all".

    Returns only the calling key's own usage (totals + per-tool breakdown) for that
    window - never another user's data and never the email behind the key. One meter
    spans AT and DE, since the facade is the single billing point. Use it to check your
    consumption against the plan's rate limits.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
windowNotoday

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

TDQS

A4.7/5.0
Behavior5/5

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

Beyond the existing readOnly/idempotent/destructive annotations, the description adds important behavioral context: it only returns the calling key's own usage, never another user's data, never the email behind the key, and it explains that a single meter spans AT and DE as the billing point. This provides meaningful transparency about limits and privacy.

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 description is well structured and front-loaded: it opens with a clear summary and then provides parameter details and return-scope specifics. It is slightly repetitive around 'own usage' and 'calling key's own usage,' but every section earns its place and nothing is irrelevant.

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 a single optional parameter, existing safety annotations, and an output schema present, the description is complete for making a correct call. It states the call filter, the result scope, the billing-meter behavior, and a practical use case, leaving no important operational gap.

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?

The schema provides only the parameter name, type, and default, with no descriptions. The tool description compensates fully by documenting the optional window parameter, its default value of 'today', and every valid value: today, yesterday, month_to_date, last_30_days, and all.

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 precisely what the tool does: obtain the calling API key's own usage, including call count and weighted compute-units, per tool, and it clarifies the 'both registers' scope. It also distinguishes the tool from siblings by emphasizing 'your own' usage and explicitly excluding other users' data.

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?

The description gives a concrete use case: 'Use it to check your consumption against the plan's rate limits.' It is clear about context but does not explicitly name alternatives or provide when-not-to-use guidance, which keeps it slightly below the top score.

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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