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Claimondo — Kfz-Gutachter finden & Termin buchen

Telefon-Rückruf anfordern

claimondo_rueckruf

Fordert einen kostenlosen Telefon-Rückruf durch einen Claimondo-Berater an — der zweite Funnel-Arm neben claimondo_melde_schaden, für Kunden die lieber angerufen werden (oder wenn kein Slot passt / Daten fehlen). Legt einen Lead + Rückruf-Task in der Dispatch-Queue an; ein Berater meldet sich i. d. R. < 15 Min telefonisch.

Erfrage Name + Telefonnummer + (optional) Schadenart/Anliegen/PLZ. Rufe dies NUR mit einwilligung_erteilt=true auf, NACHDEM der Nutzer der Datenverarbeitung + dem telefonischen Kontakt (Verarbeitung teils über einen KI-Dienst in den USA) ausdrücklich zugestimmt hat.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
ortNoOptional: Stadt/Adresse, falls keine PLZ bekannt.
plzNoOptional: PLZ, wo das Fahrzeug steht.
nameYesName des Kunden.
telefonYesTelefonnummer des Kunden für den Rückruf.
anliegenNoOptional: kurze Schilderung des Anliegens.
schadenartNoOptional: Schadenart / Unfalltyp für den Kontext.
wunschzeitNoOptional: Wunschzeit für den Rückruf (ISO-8601). Ohne → schnellstmöglich.
einwilligung_erteiltYesMUSS true sein. NUR setzen, nachdem der Nutzer der Datenverarbeitung + dem telefonischen Kontakt (Verarbeitung teils über einen KI-Dienst in den USA) ausdrücklich zugestimmt hat.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
okYes
wannYes
statusYes
hinweisYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. Added

TDQS

A4.7/5.0
Behavior5/5

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

Annotations are minimal (all false hints), so the description carries the full burden of disclosing side effects. It clearly states that the tool 'Legt einen Lead + Rückruf-Task in der Dispatch-Queue an' (creates a lead and callback task), indicating a write operation. It also discloses that processing is partly via an AI service in the USA, which is critical for consent/privacy. It additionally mentions the expected response time (<15 min). These are meaningful behavioral traits beyond what annotations provide, and there is no contradiction with annotations.

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 two well-structured paragraphs with no filler. The first sentence states the core purpose and differentiation; the second covers usage constraints and consent. Every sentence earns its place, and the critical consent requirement is front-loaded in the second paragraph. It is appropriately sized for the tool's complexity.

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 the 8 parameters (3 required), 100% schema coverage, and an existing output schema, the description provides everything an agent needs: purpose, usage criteria, side effects, consent requirement, and a mention of the dispatch queue. It does not need to describe return values because the output schema handles that. The description is complete for correct invocation.

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 description coverage is 100%, so the baseline is 3. The description adds minimal extra meaning: it summarizes the required fields (Name + Telefonnummer) and mentions optional fields (Schadenart/Anliegen/PLZ), and reinforces the consent condition for einwilligung_erteilt. However, the schema already describes each parameter and the consent condition in detail. The description does not introduce new parameter semantics beyond what the schema already provides, so it stays at the baseline.

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 opens with a clear verb+resource: 'Fordert einen kostenlosen Telefon-Rückruf durch einen Claimondo-Berater an' (requests a free phone callback). It explicitly names the sibling tool 'claimondo_melde_schaden' as the alternative funnel arm, and distinguishes when to use this tool: for customers who prefer to be called or when no slot fits/data is missing. It also states the concrete side effect (creating a lead + callback task), so an agent can unambiguously tell this tool apart from its siblings without opening schemas.

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?

The description provides explicit when-to-use guidance: it contrasts with claimondo_melde_schaden and gives the conditions for choosing this tool ('für Kunden die lieber angerufen werden (oder wenn kein Slot passt / Daten fehlen)'). It also states the hard prerequisite: must only be invoked with einwilligung_erteilt=true after user consent. No ambiguity remains about when this tool is appropriate.

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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