Charging state and schedules

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

Annotations already mark this as read-only, idempotent, and non-destructive, so the description only needs to add context beyond that. It discloses the tool's behavior on incompatible powertrains: an explicit 'not applicable' error, and it enumerates the returned data cateories (charge level, status, EV range, time to full, schedules). This adds meaningful behavioral detail without contradicting the annotations.

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 compact and front-loaded: it opens with a concise data summary, then gives example use cases, then provides the key powertrain exception and sibling tool. Every sentence earns its place and there is no fluff. The structure makes it easy for an agent to quickly decide whether to call it.

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 read-only tool with an output schema present, this description is complete. It covers what data is available, when to use it, and how to route non-plug-in vehicles to the correct alternative. Nothing needed for selection or invocation 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 has zero parameters, and schema description coverage is 100%, so there are no parameters to document. The description still contributes selection-relevant context by explaining what kind of vehicle and data the tool applies to. A baseline of 4 is appropriate for a zero-parameter tool.

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 uses a specific and informative phrase—'Plug-in battery: charge level, charging status, EV range, time to full, schedules'—making it clear this tool returns charging-related state for plug-in vehicles. It also distinguishes itself from sibling tools by noting that non-plug-in powertrains should use toyota_get_energy instead. This is more than a restatement of the name; it defines the resource and scope.

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 gives explicit example questions the tool answers: 'is it charging? how much EV range? when is the next scheduled charge?' It also states a clear exclusion and routes to an alternative: 'Plug-in hybrids and electric vehicles only — other powertrains get an explicit not applicable error (use toyota_get_energy).' This is exemplary usage guidance.

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