get_average_efficiency_by_temperature

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It describes a read operation ('Get') but doesn't mention any behavioral traits such as data freshness, rate limits, authentication needs, or what 'average efficiency' entails (e.g., units, calculation method). The description is too vague to fully inform an agent about how the tool behaves beyond its basic purpose.

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 two concise sentences that are front-loaded with the core purpose. Every word earns its place: the first sentence states what the tool does, and the second provides context without redundancy. There's no wasted text or unnecessary elaboration.

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?

Given the tool's complexity (a read operation with no parameters) and the presence of an output schema, the description is minimally adequate. It states the purpose but lacks details on behavioral aspects like data sources or limitations. With no annotations and an output schema, the description should ideally provide more context about what 'average efficiency' means or how results are structured, but it's not entirely incomplete.

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 tool has 0 parameters, and schema description coverage is 100%. The description doesn't need to explain parameters, and it appropriately doesn't mention any. A baseline of 4 is applied since no parameters exist, and the description doesn't incorrectly suggest otherwise.

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 clearly states the tool's purpose: 'Get the average efficiency by temperature for each car.' It specifies the verb ('Get'), resource ('average efficiency by temperature'), and scope ('for each car'). However, it doesn't explicitly differentiate from sibling tools like 'get_efficiency_by_month_and_temperature' or 'get_total_distance_and_efficiency', which prevents a perfect score.

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 provides implied usage context: 'Helps understand how temperature affects vehicle efficiency.' This suggests when to use the tool (for temperature-efficiency analysis) but doesn't explicitly state when not to use it or name alternatives among the many sibling tools. No explicit guidance on prerequisites or comparisons is given.

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