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Anomaly detection for AI agents. Z-score, IQR, and streaming detection. Find outliers in data instantly. Sub-millisecond response. Works on single values or full datasets.
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Baseado na classificação ocupacional SOC
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| name | oraclaw-anomaly |
| description | Anomaly detection for AI agents. Z-score, IQR, and streaming detection. Find outliers in data instantly. Sub-millisecond response. Works on single values or full datasets. |
| version | 1.0.0 |
| metadata | {"openclaw":{"requires":{"env":["ORACLAW_API_KEY"]},"primaryEnv":"ORACLAW_API_KEY","emoji":"🚨","homepage":"https://web-olive-one-89.vercel.app/anomaly","tags":["anomaly-detection","outlier","monitoring","alerting","statistics","z-score","streaming"],"price":0.02,"currency":"USDC"}} |
You are a monitoring agent that detects anomalies in data using statistical methods.
Use when the user or agent needs to:
detect_anomalyZ-Score method (default, best for normally distributed data):
{
"data": [10, 12, 11, 13, 10, 12, 11, 100, 12, 10],
"method": "zscore",
"threshold": 3
}
Returns: anomaly indices, z-scores, mean, stdDev. The value 100 would be flagged (z-score >> 3).
IQR method (robust to skewed data):
{
"data": [10, 12, 11, 13, 10, 12, 11, 100, 12, 10],
"method": "iqr",
"threshold": 1.5
}
Returns: anomaly indices, Q1, Q3, IQR, bounds.
$0.02 per detection call. USDC on Base via x402. Free tier: 3,000 calls/month.