anomalies

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

Discloses behavioral traits: defines outlier and streak thresholds, defaults to last 30 days and core metrics. However, does not describe output format or whether it modifies data. Without annotations, this is relatively transparent but incomplete.

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?

Two short, front-loaded sentences with no redundancy. Every word adds value, defining behavior and default scope efficiently.

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 moderate complexity with 4 parameters and no output schema, the description covers anomaly types and defaults but omits return format, pagination, or error conditions. Sufficient for basic understanding but not fully complete.

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 coverage is 0%, so description must compensate. It explains z (threshold), start/end (implied by time range), metrics (core vs customized). But does not explicitly describe each parameter's usage or constraints, leaving some ambiguity.

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?

Clearly states the tool detects outlier days and sustained streaks, defining specific criteria (z standard deviations and 5+ consecutive days). Distinguishes itself from siblings like baselines or get_activity by focusing on anomaly detection.

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?

Implies default usage with 'last 30 days of core wellness metrics' but provides no explicit guidance on when to use this tool versus alternatives (e.g., query_metrics, correlate). No when-not or alternative recommendations.

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