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

Annotations already declare readOnly, openWorld, idempotent, and non-destructive behavior. The description adds real operational context beyond those annotations: data is LIVE, scoped to the current service day, aggregated per route, and sorted worst-affected first. It does not describe exact output fields, but the aggregate nature is clear.

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 three short sentences, each carrying distinct value: what is counted, why it is authoritative and live, and the ordering of results. There is no filler or repetition of schema 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?

For a tool with only two optional, fully documented parameters and no required fields, the description provides enough operational context for correct invocation: live data, current service day, per-route counts, and worst-affected-first ordering. The absence of an output schema is adequately compensated because the result shape is implied.

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 fully documents both optional parameters, route_code and min_canceled, including examples. The description does not add parameter-level guidance, but with 100% schema coverage the baseline score of 3 is appropriate.

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 names the specific resource (LA Metro service cancellations) and operation (reporting canceled trips counted per route), and immediately distinguishes it from schedule/GTFS data by calling it the authoritative live signal. It also discloses the sort order, so an agent can tell exactly what this tool returns.

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?

The description explicitly states when this tool is the right choice: it is authoritative for 'is LA Metro dropping trips on my line today,' a question that schedule or GTFS feeds cannot answer. It does not name sibling tools as alternatives, but the use-case boundary is clear enough to route an agent correctly.

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