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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.
Install with Codex or Claude Copy this prompt, paste it into Codex, Claude, or another assistant, and let it review the skill page and install it for you.
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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.