Tesla Query History

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

Annotations already establish read-only, idempotent, non-open-world behavior. The description adds meaningful context beyond that: it uses a local snapshot database and avoids calling Tesla or waking the car, which is important operational behavior. It does not describe data freshness or staleness, but it adds real value over 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?

Two short sentences, front-loaded with the data source and followed by the key operational constraint. There is no wasted text.

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?

The tool has a complete input schema and an output schema, so return values need not be explained. The description covers the source and non-wake behavior, but it omits any note on snapshot freshness or data lag, which would help an agent decide when local history is appropriate.

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 the schema already documents metric, dates, bucket, and vin semantics. The description does not add parameter-level meaning beyond the schema, which is acceptable given full schema coverage.

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 identifies the resource as a time series from the local snapshot database and distinguishes it from live/wake tools by saying it does not call Tesla or wake the car. It is clear enough for an agent to recognize historical local data retrieval, though it does not explicitly use a query/retrieve verb.

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 phrase 'Does not call Tesla or wake the car' strongly implies when this tool is preferable: when avoiding vehicle wake-up or live API calls. However, it gives no explicit alternatives or when-not guidance versus siblings like tesla_usage or tesla_get_odometer.

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