[Premium] Flag outlier points in a numeric series using Z-score (parametric, assumes ~normal) or IQR (robust to skew). Use for monitoring metrics, fraud signals, sensor noise, quality control. Z-score is faster and tighter on near-normal data; IQR is the right default when the distribution has he...
Part of the Oraclaw server.
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AI agents call detect_anomaly to retrieve information from Oraclaw without modifying any data. This is common in research, monitoring, and reporting workflows where the agent needs context before taking action. Because read operations don't change state, they are generally safe to allow without restrictions -- but you may still want rate limits to control API costs.
Even though detect_anomaly only reads data, uncontrolled read access can leak sensitive information or rack up API costs. An agent caught in a retry loop could make thousands of calls per minute. A rate limit gives you a safety net without blocking legitimate use.
Read-only tools are safe to allow by default. No rate limit needed unless you want to control costs.
{
"version": "1",
"default": "deny",
"tools": {
"detect_anomaly": {}
}
}See the full Oraclaw policy for all 17 tools.
These attack patterns abuse exactly the kind of access detect_anomaly gives an agent. Each links to the full case and the policy that stops it:
Other read tools across the catalogue. The same approach applies to each: allow, with a rate cap to control cost.
[Premium] Flag outlier points in a numeric series using Z-score (parametric, assumes ~normal) or IQR (robust to skew). Use for monitoring metrics, fraud signals, sensor noise, quality control. Z-score is faster and tighter on near-normal data; IQR is the right default when the distribution has heavy tails or known outliers. Returns indices + values + the underlying statistics. For projecting a series forward, use predict_forecast. Requires ORACLAW_API_KEY.. It is categorised as a Read tool in the Oraclaw MCP Server, which means it retrieves data without modifying state.
Register the Oraclaw MCP server in PolicyLayer and add a rule for detect_anomaly: allow, deny, rate-limit, or require approval. Point your MCP client at the PolicyLayer proxy URL and the rule is enforced on every call, before it reaches Oraclaw. Nothing to install.
detect_anomaly is a Read tool with low risk. Read-only tools are generally safe to allow by default.
Yes. Add a rate_limit block to the detect_anomaly rule in your PolicyLayer policy. For example, setting max: 10 and window: 60 limits the tool to 10 calls per minute. Rate limits are tracked per agent session and reset automatically.
Set action: deny in the PolicyLayer policy for detect_anomaly. The AI agent will receive a policy violation error and cannot call the tool. You can also include a reason field to explain why the tool is blocked.
detect_anomaly is provided by the Oraclaw MCP server (@oraclaw/mcp-server). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
Deterministic rules across all 17 Oraclaw tools. Per-identity grants. Full audit log. Live in minutes. Nothing to install.
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