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

Annotations already declare readOnly=true, idempotent=true, openWorld=true, destructive=false, so the safety profile is covered. The description usefully adds the prediction horizon (next hour) and methodology (frequency decay), but says nothing about confidence, limitations, or accuracy.

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?

A single tight sentence with the subject (whale activity prediction) front-loaded and no wasted words. Efficient, though it is arguably terse for a predictive tool.

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?

With an output schema present, return values need not be explained, and the sole parameter is fully documented. The description covers what is predicted and by what method, leaving only accuracy/limitations unaddressed – a minor gap for a read-only prediction tool.

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 single chain parameter has 100% schema description coverage with a full enum, so the schema does the heavy lifting. The description adds no additional parameter semantics, matching the baseline 3 for fully documented schemas.

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?

States a specific verb (projects) and resource (next-hour transfer count and volume) with the method named (frequency decay model). An agent can distinguish it from sibling trackers/alerts like monitor.whale.tracker or monitor.whale.alerts, though it never names them explicitly.

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 predictive framing implies when to use it (forecasting vs. observing), but there are no explicit when/when-not statements and no reference to the sibling monitoring tools. Usage must be inferred from the word 'projects'.

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