KiHustle JSON Anomaly Window Detection

x402

KiHustle JSON Anomaly Window Detection is a paid API for AI agents from kihustle.tech, paid per call via x402, $0.002/call, status unknown (last checked 2026-09-13).

Detects anomalies within a sliding window of numeric values using a configurable threshold

Price / call$0.002

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StatusUnknown

How this service works

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Output

Returns a JSON object with a 'result' field indicating whether anomalies were found and a 'status' field confirming successful processing. Specific flagged indices or values are implied by the result field.

Example use cases

Spike detection in IoT sensor stream

“I have a list of temperature readings from my IoT sensor — [20.1, 20.3, 20.0, 55.2, 20.4, 19.9, 20.2] — can you run anomaly detection with a window size of 4 and a threshold of 3.0 to catch any sudden spikes?”

Financial metric outlier flagging

“Here are my daily revenue figures for the past two weeks: [1020, 1050, 980, 1100, 1030, 5500, 1010, 990, 1080, 1020, 970, 1040, 1060, 990]. Can you scan them for anomalies using a window of 5 and a threshold of 2.0?”

Monitoring API latency for unusual slowdowns

“I've got a sequence of API response times in milliseconds: [120, 125, 118, 122, 890, 121, 119, 124, 130, 118]. Please run a sliding-window anomaly check with window size 3 and threshold 2.5 so I can see which readings are outliers.”

Technical details

Endpoint

POSThttps://kihustle.tech/nexus/api/v1/json-anomaly-window

When to prefer

Choose this endpoint when you need lightweight, low-latency anomaly detection on a numeric array using a sliding window approach and you want a simple pass/fail or flagged-result output. It is cost-effective at $0.002 per call for periodic monitoring tasks or embedded anomaly checks in automation pipelines. Prefer it over heavier ML-based anomaly detection services when you have a clear threshold value and a well-defined window size.

Side effects

Missing or empty 'values' array returns an error or undefined behavior
Non-integer 'window' value may cause validation failure
Window size larger than the values array may produce no meaningful result
Threshold not provided may fall back to a default or cause a processing error
Network timeout on large arrays

Input

Schema · Request body

Field	Type	Description
values	array
window	integer
threshold	number

Output

Schema · Response

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

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How this service works

Output

Example use cases

Spike detection in IoT sensor stream

Financial metric outlier flagging

Monitoring API latency for unusual slowdowns

Technical details

Endpoint

POSThttps://kihustle.tech/nexus/api/v1/json-anomaly-window

When to prefer

Side effects

Missing or empty 'values' array returns an error or undefined behavior
Non-integer 'window' value may cause validation failure
Window size larger than the values array may produce no meaningful result
Threshold not provided may fall back to a default or cause a processing error
Network timeout on large arrays

Input

Schema · Request body

Field	Type	Description
values	array
window	integer
threshold	number

Output

Schema · Response

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