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

Annotations already cover the safety profile (readOnly, idempotent, non-destructive, open-world), and the description adds genuinely new behavior: the meaning of each return value, that assignments publish ~2 days out, that assignments can change via aircraft swaps, and the latency tradeoff versus predict_flight_starlink. This is exactly the context annotations cannot express.

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 trigger condition is front-loaded in the first sentence, followed by return-value semantics and then the routing note. Every sentence carries information the agent needs; nothing is redundant padding.

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?

There is no output schema, so the description must explain returns — and it does, enumerating all four outcome states. Combined with the timing caveat (~2 days out) and the sibling routing note, nothing material is missing 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 100%, so origin, destination, date, and flight_number formats are already fully documented in the schema (including the multi-leg scoping behavior of origin/destination). The description adds no parameter-level detail beyond the schema, so the baseline 3 applies.

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 ('check' a 'flight' for Starlink) and immediately defines the answer space (YES / LIKELY YES / NO / probability estimate). It clearly distinguishes itself from predict_flight_starlink, which it explicitly names.

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 an explicit trigger ('when the user asks "does my flight have Starlink/WiFi?" with a specific flight number and date') and names the alternative for out-of-range dates ('call predict_flight_starlink directly'). It also explains that check_flight falls through to the same estimate with extra latency, so the agent knows exactly when this tool is the right call.

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