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

Annotations already mark this as read-only, idempotent, and non-destructive, and the description is consistent with those. It adds valuable behavioral detail beyond annotations: reliability tiers by observation count, coverage differences between flight-number ranges, and the low-result branch where the date triggers a route lookup and returns a ready-made plan_starlink_itinerary call.

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 dense but every sentence earns its place: trigger condition, output definition, reliability caveat, fleet-coverage nuance, and schema-relevant guidance. Key decision-relevant content is front-loaded in the first sentence, and the rest directly improves correct invocation.

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?

For a two-parameter, read-only prediction tool with no output schema, this is complete. The agent knows what triggers the call, what the result means, which confidence tiers matter, how fleet split should be sourced, and what happens downstream on low-probability results. Nothing essential is missing.

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 input schema already documents both parameters with 100% coverage, so the baseline is 3. The description meaningfully adds semantics, especially for date: it must be passed when known, affects behavior on low-confidence results, and enables a pre-filled downstream call. It also clarifies flight_number formats and marketing-number preference.

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 trigger ('will my flight have Starlink?'), a temporal condition (too far out or no date), and a concrete output (probability from historical observations). It also implies differentiation from route-level prediction by focusing on flight number and mentions a sibling (get_fleet_stats) without confusion.

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 clearly says when to use the tool: when the user asks about Starlink on a flight with a date too far out or no date. It also gives an explicit alternative call for fleet coverage data (get_fleet_stats). However, it does not explicitly say when not to use it relative to siblings like check_flight or predict_route_starlink, leaving some routing implicit.

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