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

Annotations already declare readOnlyHint=true and destructiveHint=false, but the description adds substantive caveats beyond them: wind is unknown, group riding biases the value low, tagged rides are excluded, and the output is explicitly an estimate rather than a measurement. It also states the return content (estimate, spread, ride count), covering the missing output schema.

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?

Purpose and method are front-loaded and every clause carries information. It is a dense single paragraph, so a sentence break between method, caveats, and race usage would improve scanability, but nothing is wasted.

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 no output schema, the description fully specifies what comes back (estimate plus spread plus number of rides). It also covers the statistical approach, the caveats, and the required follow-up workflow, so an agent has everything needed to call and act on it.

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?

There is a single optional parameter with 100% schema coverage, including its bounds and default (120 days), so the schema already carries the meaning. The description adds nothing about the lookback window, which is acceptable given full coverage but leaves no extra value.

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 and resource (estimate the athlete's effective drag area, CdA in m²) and explains the derivation, distinguishing it clearly from siblings like estimate_thresholds. An agent can tell exactly what this produces without opening the schema.

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?

Gives explicit downstream guidance: to use the result for a race, propose setting it on the event via update_event cda and only after the athlete agrees. It also names the data conditions that select this tool (athlete's own outdoor rides with power) and exclusions (race/group/indoor-tagged rides).

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