KiHustle German Formal Tone Scorer

x402

KiHustle German Formal Tone Scorer is a paid API for AI agents from kihustle.tech, paid per call via x402, $0.002/call, status unknown (last checked 2026-10-20).

Scores or evaluates German text for formal tone adherence (Sie-form / formal register)

Price / call$0.002

Seller volume →—

Success—

StatusUnknown

How this service works

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Output

Returns a JSON object with a 'result' field indicating the processing outcome and a 'status' field ('success' or otherwise). The actual formality score or rating is expected within the result payload, though the schema shows a generic processed/success structure.

Example use cases

German business email formality check

“I just wrote this German client email — can you score how formal it sounds: 'Hiermit bestätigen wir Ihren Auftrag und bitten Sie, die Rechnung innerhalb von 14 Tagen zu begleichen.'?”

German legal document tone validation

“Before I send this German legal notice, please check whether the tone is sufficiently formal: 'Wir fordern Sie auf, die ausstehenden Zahlungen unverzüglich zu leisten.'”

Formal German content QA for chatbot

“We're building a German customer service bot that must always use Sie-form — can you score this response for formal tone: 'Können Sie mir bitte Ihre Bestellnummer mitteilen, damit ich Ihnen weiterhelfen kann.'?”

Technical details

Endpoint

POSThttps://kihustle.tech/api/v1/de-formal-tone-scorer?utm_source=zero.xyz

When to prefer

Choose this endpoint when you specifically need to evaluate German-language text for formal register (Sie-form vs du-form, business vs casual tone). It is purpose-built for German formality assessment rather than generic multilingual sentiment or tone analysis tools. Ideal for workflows involving German business communication, legal documents, or customer-facing content that must meet formal language standards.

Side effects

Empty or missing 'text' field causes processing failure
Very short text may yield unreliable or low-confidence scores
Non-German text input may produce meaningless formality scores
Network timeout for very large text inputs
Ambiguous mixed-register text may return inconsistent scoring

Input

Schema · Request body

Field	Type	Description
text	string

Output

Schema · Response

{
  "type": "json",
  "example": {
    "result": "processed",
    "status": "success"
  }
}

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