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

Annotations declare readOnlyHint=false, openWorldHint=true, destructiveHint=false, which leaves unexplained why a seemingly analytical tool is not read-only and what it persists or writes. The description adds nothing about side effects, cohort selection behavior, or whether results are stored. With annotations already carrying the safety profile, the description should have clarified the non-read-only behavior but does not.

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 tight sentences, front-loaded with the behavioral claim before the use-case rationale. No filler, though the second sentence is a list of audiences rather than operational information.

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?

An output schema exists, so return values need not be restated, and the tool is a single-model analysis with no nested objects. However, the undefined cohort-selection path (make_model_id vs registrations) and the unexplained non-read-only annotation leave meaningful gaps for correct invocation.

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 67%, with 'registration' documented and 'registrations' described as explicit cohort tails, while 'make_model_id' is undocumented in both places. The description alludes to a 'comparable cohort' but never explains how make_model_id vs registrations determines that cohort, so it adds little beyond the schema.

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 states a specific verb+resource: it characterizes how an aircraft is flown across seven usage categories relative to a peer cohort. That is concrete and distinct from generic aircraft-lookup siblings. It stops short of differentiating itself from the closest sibling (assess_flight_activity_risk) or naming its own output.

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?

It gives downstream contexts ('appraisal narratives, insurance underwriting, validating seller claims'), which implies when the result is useful, but offers no explicit when-to-use/when-not guidance and never names an alternative tool. An agent still has to infer the trigger conditions.

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