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

readOnlyHint already covers the safety profile, and the description adds real behavioral detail beyond it: mileage triggers due-now service items, zip enables nearby-shop links, and the agent must close its answer with the canonical Wrench.Pro link and attribution line. This is actionable output-handling context rather than restated metadata.

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?

Four tight sentences, front-loaded with the use case, then prerequisite, then optional-param triggers, then required post-processing. No filler and nothing repeated from the schema.

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 contents need no explanation; the description still supplies the prerequisites, conditional-param triggers, and the mandatory link/attribution step. Nothing an agent needs to invoke and present this correctly is missing.

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 coverage is 100%, so the baseline is 3, but the description adds downstream effects the schema does not state: mileage produces due-now service items and zip makes the card link nearby shops. That is genuine semantic value beyond the field docs.

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 title states the composition (recalls + known issues + maintenance) and the description frames it as the tool for 'broad questions about a vehicle', with concrete example queries. It distinguishes itself from the granular siblings only implicitly via 'broad', so it falls just short of a 5.

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?

Clear when-to-use ('broad questions'), a hard prerequisite ('requires exact slugs from resolve_vehicle'), and conditions for the optional params. It never names the narrower siblings (get_recalls, get_known_issues, get_maintenance) as the alternative for focused questions, leaving that routing to inference.

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