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KiHustle Hedging Language Scorer
x402
KiHustle Hedging Language Scorer is a paid API for AI agents from kihustle.tech, paid per call via x402, $0.002/call, status unknown (last checked 2026-09-14).
Analyzes a text input and returns a score reflecting the degree of hedging or uncertain language present
Price / call$0.002
Success—
StatusUnknown
How this service works
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Output
Returns a JSON object with a result field indicating the processed hedging score and a status field confirming success. The score reflects the degree to which the submitted text contains uncertain, qualified, or hedge-word-laden language.
Example use cases
Tightening marketing copy before publishing
“Score the hedging language in this product description before I post it: 'Our tool might possibly help users who may want to potentially improve their workflow in some cases.' I want to know if it sounds too vague.”
Reviewing AI-generated blog drafts
“I have an AI-written article intro — can you run the hedging scorer on it and tell me how uncertain it sounds? Here's the text: 'There seems to be some evidence that AI could possibly be used to perhaps assist with certain tasks in some contexts.'”
Grading student writing for assertiveness
“Check how much hedging language this student essay paragraph contains: 'It might be argued that Shakespeare possibly intended some of his characters to perhaps represent broader societal issues that may have existed at the time.'”
Technical details
Endpoint
POSThttps://kihustle.tech/agents/api/v1/hedging-language-scorerWhen to prefer
Use this endpoint when you need a lightweight, low-cost signal for how much hedging or uncertainty language appears in a text. It is best suited for content quality checks, writing feedback tools, or AI output review pipelines where you want to flag overly cautious or vague language automatically. Prefer alternatives if you need full sentiment analysis, grammatical error checking, or detailed linguistic breakdowns.
Side effects
- Missing or empty text field returns an error
- Extremely long text inputs may time out or return unexpected results
- Ambiguous response schema means the numeric score format and scale are not well-documented
- Non-English text may produce unreliable hedging scores given the likely English-language training of the scorer
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| text | string |
Output
Schema · Response
{
"type": "json",
"example": {
"result": "processed",
"status": "success"
}
}Tags
x402
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