JSON Outlier Detector (Z-Score)

x402

JSON Outlier Detector (Z-Score) is a paid API for AI agents from kihustle.tech, paid per call via x402, $0.002/call, status unknown (last checked 2026-10-27).

Detects outliers in JSON data using Z-score statistical analysis

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 whether outliers were detected and a status field confirming success. May include Z-score values or flagged data points depending on the input.

Example use cases

Flagging sensor data anomalies

“I have a list of temperature sensor readings — can you run Z-score outlier detection on this JSON to find any unusual spikes or drops: [22.1, 22.4, 22.0, 21.9, 87.3, 22.2, 21.8]?”

Cleaning financial transaction data

“Before I process these transaction amounts, can you check this dataset for statistical outliers using Z-score so I can flag anything that looks suspicious: [150, 145, 160, 155, 4500, 148, 152]?”

QA check on survey response scores

“I've got survey scores from 50 respondents and I want to make sure there are no weird outlier entries before I analyze the results — can you run Z-score outlier detection on this JSON data for me?”

Technical details

Endpoint

POSThttps://kihustle.tech/api/v1/json-outlier-detector-zscore?utm_source=zero.xyz

When to prefer

Choose this endpoint when you need a lightweight, inexpensive ($0.002/call) statistical outlier check on numeric JSON data using the well-established Z-score method. Best suited for quick data quality checks, preprocessing pipelines, or anomaly flagging before further analysis. Prefer this over ML-based anomaly detectors when you need a simple, interpretable, threshold-based statistical approach.

Side effects

Malformed or non-numeric input text causes processing errors
Empty or null text field returns error
Non-JSON or unparseable data in text field may return failure status
Dataset too small to compute meaningful Z-scores
Network timeout on large datasets

Input

Schema · Request body

Field	Type	Description
text	string

Output

Schema · Response

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

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