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KiHustle JSON Seasonality Detector
x402
KiHustle JSON Seasonality Detector 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).
Detects seasonality patterns in a time-series array of numeric values given a specified period length
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 seasonality detection outcome and a 'status' field confirming success. The exact seasonality metrics (e.g., detected period strength, seasonal flags) are inferred from the processed values and period parameter.
Example use cases
Monthly revenue seasonality check
“I have 36 months of revenue numbers and want to know if there's a repeating annual pattern — the values are [5200, 4800, 5100, 6000, 6500, 7200, 7800, 7500, 6800, 6100, 5500, 5000, 5300, 4900, 5200, 6100, 6600, 7300, 7900, 7600, 6900, 6200, 5600, 5100, 5400, 5000, 5300, 6200, 6700, 7400, 8000, 7700, 7000, 6300, 5700, 5200], period 12. Can you run a seasonality check on these?”
Weekly website traffic cycle detection
“Here are 8 weeks of daily website visit counts: [300, 420, 450, 430, 410, 200, 190, 310, 430, 460, 440, 420, 210, 195, 305, 425, 455, 435, 415, 205, 192, 308, 428, 458, 438, 418, 208, 193, 312, 432, 462, 442, 422, 212, 196, 316, 436, 466, 446, 426, 216, 198, 320, 440, 470, 450, 430, 220, 200, 325, 445, 475, 455, 435, 225, 202]. Can you detect whether there's a 7-day seasonal cycle in this data?”
Quarterly e-commerce trend analysis
“I want to see if my e-commerce orders follow a quarterly seasonal pattern. Here are my order counts for the past 3 years by week: [200, 210, 195, 230, 220, 215, 205, 240, 250, 245, 260, 280, 200, 212, 198, 233, 223, 218, 208, 243] — analyze with period 13 for quarterly cycles.”
Technical details
Endpoint
POSThttps://kihustle.tech/agents/api/v1/json-seasonality-detectorWhen to prefer
Choose this endpoint when you need a lightweight, low-cost ($0.002 per call) API call to quickly determine if a numeric time series exhibits seasonality for a given period. It is best suited for simple periodic-pattern checks on moderate-length arrays where you already know the candidate period. Prefer more advanced statistical libraries or endpoints if you need decomposition details, multiple period testing, or confidence intervals.
Side effects
- Missing or empty 'values' array causes a processing error
- Non-integer 'period' value may be rejected or cause unexpected results
- Period longer than the values array length may yield unreliable results
- Malformed JSON input body returns an error response
- All-identical values (zero variance) may produce degenerate seasonality output
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| period | integer | |
| values | array |
Output
Schema · Response
{
"type": "json",
"example": {
"result": "processed",
"status": "success"
}
}Tags
x402
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