get_efficiency_by_month_and_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 mentions analysis but doesn't specify whether this is a read-only operation, if it requires authentication, what data format is returned, or any performance characteristics. For a tool with zero annotation coverage, this leaves significant behavioral gaps.

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 efficiently structured in two sentences: the first states the core functionality, and the second adds analytical context. Every sentence earns its place without redundancy or unnecessary elaboration, making it appropriately front-loaded and concise.

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 (analysis of efficiency by month and temperature) and the presence of an output schema, the description is minimally adequate. It explains what the tool does but lacks details on behavioral traits, usage context, or output interpretation. With no annotations and rich sibling tools, it should provide more guidance to be fully complete.

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 with 100% schema description coverage, so the schema fully documents the absence of inputs. The description doesn't need to compensate for any parameter gaps, and it appropriately doesn't mention parameters. A baseline of 4 is applied since no parameters exist.

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 with a specific verb ('Get') and resource ('efficiency by month and temperature for each car'), and adds analytical context ('Analyzes how seasonal temperature changes affect vehicle efficiency'). However, it doesn't explicitly differentiate from siblings like 'get_average_efficiency_by_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 no guidance on when to use this tool versus alternatives. With multiple sibling tools related to efficiency and temperature analysis, there's no indication of specific use cases, prerequisites, or comparisons to tools like 'get_average_efficiency_by_temperature' or 'get_monthly_driving_summary'.

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