KiHustle JSON Rolling Standard Deviation

x402

KiHustle JSON Rolling Standard Deviation is a paid API for AI agents from kihustle.tech, paid per call via x402, $0.002/call, status unknown (last checked 2026-10-15).

Computes a rolling standard deviation over a sliding window of numeric values and returns the result as JSON

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 containing the computed rolling standard deviation output and a 'status' field indicating success. The result reflects the standard deviation computed over the specified sliding window across the provided numeric array.

Example use cases

Financial price volatility tracking

“I have these closing stock prices for the last 10 days: [145.2, 147.8, 144.1, 148.3, 150.0, 149.2, 151.4, 148.7, 152.3, 150.9] — can you compute the rolling standard deviation with a window of 5 so I can see how volatile it's been?”

Sensor data noise detection

“I've got a stream of temperature sensor readings [22.1, 22.4, 23.8, 22.0, 21.9, 24.5, 22.3, 21.8, 22.6, 23.1] and I want to find noisy spikes using a rolling standard deviation over a window of 4 samples.”

Website traffic anomaly analysis

“Here are daily visitor counts for my site over the past two weeks: [340, 355, 362, 290, 410, 398, 375, 360, 512, 340, 355, 349, 370, 388] — run a rolling standard deviation with window 7 so I can see which days had unusually erratic traffic.”

Technical details

Endpoint

POSThttps://kihustle.tech/nexus/api/v1/json-rolling-std-dev?utm_source=zero.xyz

When to prefer

Choose this endpoint when you need a quick, pay-per-call rolling standard deviation calculation without setting up a local statistics library or data pipeline. Ideal for lightweight agents processing time series data, financial signals, or sensor streams that need statistical dispersion computed on the fly. Best for small-to-medium numeric arrays where a sliding window volatility measure is sufficient.

Side effects

Empty or missing 'values' array returns an error or undefined result
Window size larger than the input array length may produce empty or null results
Non-numeric values in the array cause parsing or computation errors
Window size of zero or negative integer is likely invalid and may return an error
Malformed JSON request body returns a 400-level error

Input

Schema · Request body

Field	Type	Description
values	array
window	integer

Output

Schema · Response

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

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