Odometer reading

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

Annotations already disclose readOnly, idempotent, and non-destructive behavior. The description adds a useful semantic detail—'total' distance vs. trip data—and unit ambiguity (kilometers/miles), but does not add further operational context such as data freshness or refresh requirements.

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 concise sentences front-load the core result and add a practical use-case question. There is no redundant detail or filler.

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 zero-parameter getter with an output schema and read-only annotations, the description covers the main use case. It could be slightly more complete by noting how it differs from vehicle_info/status or whether a vehicle must first be selected, but nothing critical 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?

There are no parameters, so the baseline is 4. The description still adds meaning by specifying that the value is total odometer distance and expected in kilometers/miles, which is all an agent needs beyond the empty 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 explicitly states the resource ('odometer') and the value returned ('total distance'), and gives a concrete user-facing question ('how many kilometers/miles are on the car?'). It is clear enough to distinguish from energy, charging, or location getters, though it does not name a sibling.

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 'Use for:' line gives an explicit triggering question, so an agent knows when to select this tool. It does not state exclusions or mention alternatives such as toyota_get_vehicle_info, but for a zero-parameter getter the usage context is clear.

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