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

Annotations already cover the safety profile (readOnlyHint, idempotentHint, destructiveHint=false), so the description is not burdened with that. It does add real behavioral value: 'Returns up to 10 ranked vehicles with explicit match reasons, compromises and unknown data rather than pretending every requirement is known,' which tells the agent how the result is constructed and that uncertainty is surfaced.

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?

Three sentences, front-loaded with the core purpose and result contract, with no filler. It is slightly dense with an enumerated list, but every clause carries routing or behavior information.

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?

For a 9-parameter, nested-object tool with no output schema, the description does the important work: it explains the ranking/result shape and the honest handling of unknown data. The main remaining gap is the relationship between the 'requirements' and 'preferences' objects and how hard constraints differ operationally from soft ones.

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 only 22%, so the description must compensate, and it largely does by mapping conversational domains to the parameter space: family size (minBerths), automatic transmission, travel seats, licence/weight limits, fixed/island beds, showers, dimensions, mileage, features, location and budget. It also introduces the hard-vs-soft requirement distinction that the nested schema does not explain. It does not, however, name the actual fields or clarify the separate 'requirements' vs 'preferences' objects.

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 gives a specific verb and resource: 'Match a buyer's hard requirements and softer preferences against current public RoamWorthy stock,' and adds the scope constraint 'current public stock.' It implicitly separates itself from generic search_listings/search_models by framing itself as a ranked conversational matcher, but it never names a sibling to make the routing explicit.

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?

'Use this for conversational requests such as family size, automatic transmission, travel seats...' gives a clear triggering context and enumerates the kinds of user needs it handles. It stops short of stating when NOT to use it or naming the alternative tools (search_listings, get_listing) for direct lookups.

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