List Vitals Anomalies

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. The single sentence implies a read-only listing operation but does not mention pagination behavior, data freshness, whether anomalies are precomputed, auth requirements, or how filter_expression affects results.

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 a single front-loaded sentence with no filler or repetition. It states the action and the scope efficiently, and every word contributes meaning.

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 tool is a relatively simple read-only list operation with fully documented parameters and an output schema, so the description reaches minimum viability. However, it lacks usage guidance and behavioral context, and the meaning of 'statistical anomalies' is left undefined, which could confuse agents choosing among related vitals tools.

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 description coverage is 100%, so the parameters are already documented in the input schema and the description adds little beyond the domain context of 'vitals metric sets.' This matches the baseline of 3 where the schema does the heavy lifting.

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 clearly identifies the operation as listing statistical anomalies and scopes it to vitals metric sets, which distinguishes it from raw metric queries like query_vitals or list_metric_sets. However, it does not explicitly contrast with any sibling tool, so differentiation is implicit rather than stated.

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 description provides no guidance on when to use this tool versus alternatives such as query_vitals, list_metric_sets, or get_vitals_freshness. There is no mention of prerequisites, recommended contexts, or exclusions, leaving the agent to infer usage from the name and the one-line description.

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