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Carbon & Cashmere Anomaly Detection API (ETH)
x402
Carbon & Cashmere Anomaly Detection API (ETH) is a paid API for AI agents from api.carbon-cashmere.de, paid per call via x402, $0.01/call, status unknown (last checked 2026-09-15).
Detects statistical anomalies in Ethereum market data using STL decomposition, z-score analysis, and Isolation Forest ML ensemble, returning a severity rating and top anomaly drivers.
Price / call$0.01
Success—
StatusUnknown
How this service works
Professional crypto market intelligence. Real-time prices, signals, and market scoring.
Output
Returns a JSON object with an anomaly_flag (boolean), anomaly_score (0–1), severity label (e.g. 'elevated'), STL residual z-score and seasonal strength, z-scores for volume/funding/returns, an Isolation Forest outlier score and is_outlier flag, and a ranked list of top contributing features with their values and contribution weights. Includes a disclaimer noting data is for informational research only.
Example use cases
ETH unusual activity pre-trade check
“Before I put on a large ETH position, can you check whether Ethereum is currently flagging any anomalous behavior? I want to know the severity, the anomaly score, and which factors — volume, funding rate, or returns — are driving it most.”
Ethereum market conditions alert scan
“Run an anomaly scan on Ethereum's market data for me and let me know if anything looks statistically out of the ordinary right now. If there's a flag, tell me how severe it is and what's contributing the most to the signal.”
ETH outlier detection for research report
“I'm putting together a crypto market research note and need to know if Ethereum has been behaving like a statistical outlier lately. Pull the anomaly score, the isolation forest result, and break down which features — like funding rate or volume — are showing the biggest deviations.”
Technical details
Endpoint
GEThttps://api.carbon-cashmere.de/v1/anomaly/ETHWhen to prefer
Use this endpoint when you need a multi-method statistical anomaly assessment for ETH specifically — combining STL decomposition, z-scores across volume/funding/returns, and an Isolation Forest ML outlier score in one call. Prefer this over simple price APIs when you need a composite anomaly signal with severity classification and feature attribution, rather than raw price data.
Side effects
- Invalid or unsupported symbol in URL path — 404 or empty response
- Payment not processed — 402 Payment Required if x402 header is missing or underfunded
- Rate limiting or service unavailability — 429 or 503 responses
- Stale or missing underlying data causing null or incomplete z-score fields
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| properties | string |
Output
Schema · Response
{
"type": "json",
"example": {
"_meta": {
"disclaimer": "Informational research data only — not investment advice."
},
"symbol": "BTC",
"methods": {
"stl": {
"residual_z": 2.1,
"seasonal_strength": 0.34
},
"zscore": {
"volume_z": 3.1,
"funding_z": -1.2,
"returns_z": 2.8
},
"isoforest": {
"score": -0.18,
"is_outlier": true
}
},
"severity": "elevated",
"top_drivers": [
{
"value": 3.1,
"feature": "volume_z",
"contribution": 0.42
}
],
"anomaly_flag": true,
"anomaly_score": 0.73
}
}Tags
x402
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