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

With no annotations, the description carries the full behavioral burden. It explains the list semantics: routes observed daily, "therefore judge," and filter behavior including partial city matching and full list behavior. It does not describe return format or error cases, but it is transparent about selection behavior and read-only listing nature.

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?

Three tight sentences with zero wasted wording. The core purpose is front-loaded, usage comes next, and filter behavior closes with an explicit full-list option. Every sentence earns its place.

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 simple two-optional-parameter listing tool with no output schema, the description provides enough to call it correctly: what the list represents, when to call it, and how to filter. An agent can select and invoke it confidently.

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 coverage is 100% and both optional parameters already document the contains-text filtering semantics. The description adds value by stating "partial city name is fine" and "omit both for the full list," which clarifies match behavior beyond the bare 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?

Uses a specific verb and resource: "Lists the routes Piratefly observes daily and can therefore judge." This identifies the resource (watched routes) and explicitly ties it to the judgment capability that distinguishes it from pricing/timing siblings like flight_price_verdict, cheapest_months, and when_to_book.

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 usage guidance: "Call this first, or after any answer saying a route is not watched." It clearly states when in a workflow to invoke the tool, though it does not explicitly enumerate exclusions or contrast sibling tools by name.

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