list_anomalies

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

Annotations already declare readOnlyHint, destructiveHint, idempotentHint. Description adds beyond: explains metric source, that it includes active anomalies on object and children, scans VMs and sorts descending, and notes API limitations. No contradictions.

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?

Well-structured with summary line, then context, then behavior, then args. Slightly verbose but every sentence adds value. Front-loaded with purpose.

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?

Given output schema exists, description doesn't need to detail return values. It covers behavior, parameter usage, cost implications, and alternatives. Complete for a tool of this complexity with rich annotations.

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?

Schema has no property descriptions (0% coverage), but the description includes an Args section that explains each parameter: resource_id (optional UUID for single resource), limit (max VMs, range 1-100, default 50), target (optional target name). This compensates fully.

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 starts with '[READ] Report per-resource anomaly counts (System Attributes|total_alarms metric)', clearly stating the verb (report) and resource (anomaly counts). It differentiates from siblings by specifying it returns counts of active anomalies and contrasts with list_alerts for root cause.

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?

Explicit when-to-use: with resource_id for a single resource, without for scanning VMs up to limit. Warns about cost ('keep limit modest') and recommends follow-up with list_alerts for root cause. No ambiguity.

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