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

With no annotations provided, the description carries the full burden of behavioral disclosure. It explains in detail what the tool returns, how detail levels affect the response, and even mentions the info_url for sharing. It does not explicitly state side effects or read-only status, but for a calculation tool this is less critical. The description adds significant behavioral insight beyond a simple summary.

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 long but every sentence contributes useful information, especially around response fields and detail levels. It is front-loaded with the core purpose, then structured logically from general to specific. The length is justified by the complexity of the tool, and there is no redundant filler.

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 (5 parameters, nested objects, 3 detail levels) and no output schema, the description is exceptionally complete. It fully describes the response structure, the meaning of each detail level, and even includes examples and URL behavior. This leaves the agent well-equipped to understand what the tool does and what to expect.

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%, with all parameters already well-described. The description adds some extra context for the 'detail' parameter by enumerating exact field differences at each level, and for origin/destination via examples. However, it does not add substantial new semantic meaning for most parameters beyond what the schema already provides, so a baseline score of 3 is appropriate.

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 a specific action: 'Calculate European road toll costs for heavy trucks and commercial vehicles.' It names the resource (European road tolls) and the target audience (heavy trucks/commercial vehicles). This distinguishes it from the sibling tool 'get_quota', which is evidently about quota checking.

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 gives clear context for when to use the tool (toll calculation in Europe) and implicitly excludes other uses by specifying vehicle types. It does not explicitly mention the alternative 'get_quota', but the sibling is clearly unrelated, so the context is sufficient for an agent to select this tool for toll calculations.

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