Tesla Efficiency

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

Annotations are absent, so the description carries the full behavioral burden. It does disclose the metric (Wh/mi), the aggregation window (weekly averages), and the data source (driving data), which helps the agent interpret output. However, it says nothing about auth requirements, data availability behavior, or empty-result handling.

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 metric and resource, zero filler. Every clause adds 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?

An output schema exists so return values need not be described, and the schema fully covers parameters. What is missing is the routing context: with three closely related efficiency tools, the description should say when this plain variant is preferred over the temp/weather breakdowns.

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 all four parameters (days, car_id, end_date, start_date) are already documented in the schema, including defaults and override behavior. The description adds no parameter-level meaning beyond that, so baseline 3 applies.

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?

States a specific resource and metric: energy consumption trends in Wh/mi, aggregated as weekly averages from driving data. Clear what the tool computes, but it does not distinguish itself from close siblings like tesla_efficiency_by_temp or tesla_efficiency_by_weather.

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?

No explicit when-to-use guidance and no alternatives named. An agent must infer from the name that this is the default overall efficiency view versus the temperature/weather variants. Implied usage only.

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