rechtsklar24

Studienzahlen zum Onlineshop-Recht

get_study_facts

Read-onlyIdempotent

Use for figures about how common legal defects in online shops are: "wie viele Shops haben Fehler", "Studie Rechtsfehler Onlineshops", "wie viele Händler werden abgemahnt", "Abmahnquote", "Widerrufsbelehrung fehlerhaft Prozent". Returns the numbers from rechtsklar24's RechtsRadar-Report 2026 (n = 934 certified shops) and the Händlerbund surveys, each with n, method, publisher and primary source. Aggregate figures only; no shop names.

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": {
      "thema": "<thema>"
    },
    "name": "get_study_facts"
  }
}

Input Schema

Name	Required	Description	Default
`thema`	Yes	rechtsradar_2026 = Gesamtergebnis des Reports; widerrufsbelehrung = Anteil mit Lücken in der Widerrufsbelehrung; abmahnquoten_haendlerbund = Abmahnquoten 2024 und 2025.

Output Schema

Name	Required	Description	Default
`stand`	No
`thema`	Yes
`titel`	Yes
`fakten`	Yes
`methode`	Yes
`info_url`	Yes
`disclaimer`	Yes
`register_url`	Yes

Schema Changelog

Changes observed during successful MCP inspections.

First observedOct 13, 2026

TDQS

A4.1/5.0

Behavior4/5

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

Annotations already declare readOnly, idempotent, non-destructive and closed-world, so the safety profile is covered. The description adds genuinely non-redundant behavior: results are aggregate only with no shop names, and each figure carries n, method, publisher and primary source.

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 the use case before the source detail, and no sentence is filler — the source list and the 'aggregate figures only' caveat both earn their place. The dense run of German example phrases is slightly heavy but functional.

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?

With an output schema present, return-value detail is unnecessary, and the description covers scope, sourcing and the key limitation (no shop names). Complete enough for an agent to call it correctly.

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

Parameters3/5

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

Schema coverage is 100% and the enum values are each documented, so the schema carries the parameter explanation. The description's example phrasings hint at which themes exist but do not map phrases to the enum values, adding little beyond the schema — baseline 3.

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+resource ('Returns the numbers from rechtsklar24's RechtsRadar-Report 2026 and the Händlerbund surveys') and bounds the scope to aggregate study figures. An agent can distinguish this from get_fine_ceilings or get_obligation_dates immediately.

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 opening 'Use for figures about how common legal defects in online shops are' plus five realistic example phrasings make the trigger condition explicit and easy to match against user queries. It does not name the sibling tools it should be preferred over, which keeps it from a 5.

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

All rechtsklar24 tools Inspect

Try in Browser

One endpoint for every MCP toolRayrun runs every MCP server behind one URL and holds the credentials. Each call is decided per client, tool, and argument, then recorded.ray.runAd

Glama MCP Gateway

Add one secure layer between your agents and this server.

Resources

Need Help?