get_monthly_driving_summary

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 states what data is provided (monthly statistics) but does not cover aspects like read-only nature, performance, error handling, or data freshness. For a tool with no annotations, this leaves significant gaps in understanding its behavior.

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 concise and well-structured with two sentences: the first states the purpose, and the second elaborates on the statistics provided. Every sentence adds value without redundancy, making it front-loaded and efficient.

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 has no parameters, an output schema exists, and no annotations, the description is minimally adequate. It explains what the tool returns (monthly statistics for distance, energy usage, costs) but lacks details on output structure or behavioral context. With an output schema, the description need not explain return values in depth, but it could benefit from more context on usage or limitations.

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%, so there are no parameters to document. The description does not need to add parameter semantics beyond the schema, and it appropriately focuses on the tool's output. A baseline score of 4 is applied as it handles the lack of parameters effectively.

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 monthly driving summary for each car' specifies the verb (get) and resource (monthly driving summary), and 'Provides monthly statistics for distance, energy usage, and costs' elaborates on the content. However, it does not explicitly differentiate from siblings like 'get_daily_driving_patterns' or 'get_total_distance_and_efficiency', which reduces clarity.

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 no guidance on when to use this tool versus alternatives. It does not mention prerequisites, context, or exclusions, nor does it reference sibling tools for comparison. Usage is implied by the purpose but lacks explicit direction.

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