Detect anomalies in task data across duration, progress, float, and dates using statistical analysis
AI agents call detect_outliers to retrieve information from Project Management AI Analysis without modifying anything — typically the context-gathering step in research, monitoring, and reporting workflows, before the agent takes action elsewhere.
This tool performs statistical analysis on existing project data to identify anomalies. It retrieves and examines task metrics (duration, progress, float, dates) without creating, modifying, deleting, or executing any actions. The operation is purely observational with no side effects on the underlying data or external systems.
From the tool's definition Tool description states it 'Detect[s] anomalies in task data' using 'statistical analysis', with no mention of modification, deletion, or execution capabilities. The verb 'detect' and the analytical nature indicate data retrieval and analysis only.
Attacks that exploit this kind of access
Detect anomalies in task data across duration, progress, float, and dates using statistical analysis. It is categorised as a Read tool in the Project Management AI Analysis MCP Server, which means it retrieves data without modifying state.
Register the Project Management AI Analysis MCP server in PolicyLayer and add a rule for detect_outliers: 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 Project Management AI Analysis. Nothing to install.
detect_outliers 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_outliers 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_outliers. 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_outliers is provided by the Project Management AI Analysis MCP server (pm-mcp-servers). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
Every MCP server has a record like this.
Type a name, get the same breakdown: verified identity, auth posture, risk grade, capabilities, recommended policy.
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