anomaly_scan

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Beyond the readOnlyHint and destructiveHint annotations, the description discloses that it samples over a bounded window, computes mean/stddev/min/max, flags outliers using sigma, and does not persist models. It also notes server-side capping of samples, adding meaningful behavioral context.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is compact and well-structured: a deprecation notice, a clear one-line summary, a brief algorithm explanation, and a concise args list. Every sentence adds value without unnecessary verbosity.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

The description covers the tool's purpose, algorithm, limitations, and all parameters. Although there is no output schema and the return format isn't explicitly described, the tool's behavior is sufficiently clear for a read-only statistical scan. The deprecation notice makes completeness slightly less critical.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The schema provides no descriptions for its 5 parameters, but the description compensates fully with an Args section explaining each parameter's purpose (node_id, endpoint, samples, interval_ms, sigma). This provides complete semantic coverage.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description explicitly states it performs a statistical outlier scan on an OPC-UA node, with a specific verb and resource. It also clearly marks itself as deprecated in favor of opcua_anomaly_scan, distinguishing it from that alternative.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The deprecation notice explicitly directs users to opcua_anomaly_scan instead of this tool, providing a clear alternative. It also clarifies the tool's scope ('Simple statistics only — no ML, no persisted model'), implying when it is appropriate.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.