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SignalDesk AI Moving Average
x402
SignalDesk AI Moving Average is a paid API for AI agents from x402-agent.kariguetoazul.workers.dev, paid per call via x402, $0.001/call, status unknown (last checked 2026-10-13).
Computes a simple moving average over an array of numeric observations using a specified window length
Price / call$0.001
Success—
StatusUnknown
How this service works
Evidence-backed autonomous AI jobs and paid data tools. Queue/D1/cron run outside the chat; free quotas and bounded execution apply.
Output
Returns a JSON object with a 'values' array of floating-point numbers representing the computed moving averages. The output array length equals the number of input values minus (window - 1), so a window of 3 on 10 values yields 8 averaged results.
Example use cases
Smooth stock price time series
“I have 30 days of closing prices for AAPL — [145.2, 147.8, 146.1, 149.3, 151.0, 150.5, 153.2, 155.0, 154.3, 156.7, 158.1, 157.4, 160.2, 162.5, 161.8, 163.4, 165.0, 164.2, 166.8, 168.1, 167.5, 169.3, 171.0, 170.4, 172.6, 174.1, 173.5, 175.2, 177.0, 176.4] — can you compute a 7-day moving average so I can see the trend more clearly?”
Denoise IoT sensor readings
“These temperature readings from my factory floor sensor are really noisy: [72.1, 71.8, 74.3, 69.5, 73.2, 72.8, 70.1, 71.9, 74.5, 72.3, 71.0, 73.8, 72.5, 70.9, 74.1]. Apply a 3-point moving average to smooth them out.”
Analyze website traffic trends
“I have daily page view counts for the last two weeks: [1200, 1350, 1100, 1500, 1800, 2100, 1950, 1300, 1450, 1250, 1600, 1900, 2200, 2050]. Can you run a 4-day moving average so I can spot the weekly traffic pattern?”
Technical details
Endpoint
POSThttps://x402-agent.kariguetoazul.workers.dev/api/stats/moving-average?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you need a quick, serverless, pay-per-call moving average computation without setting up local statistical libraries. Ideal for lightweight agent workflows that occasionally need data smoothing on arrays up to 1000 elements. Prefer alternatives (e.g. local numpy/pandas or a dedicated analytics platform) for very large datasets, more advanced statistical transforms (EMA, VWMA), or batch operations requiring many sequential calls.
Side effects
- Empty or missing 'values' array returns a validation error
- Window length larger than the number of input values may return an empty array or error
- More than 1000 input values exceeds the maxItems limit and will be rejected
- Non-finite numbers (NaN, Infinity) in the input array may cause computation errors
- Payment failure via x402 protocol will block the request before computation
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| values | array | Up to 1000 finite observations. |
| window | integer | Window length. |
Output
Schema · Response
{
"type": "json",
"example": {
"values": [
1.5,
2.5,
3.5
]
}
}Tags
x402
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