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

Annotations already establish readOnlyHint=true, destructiveHint=false, and openWorldHint=false, so the safety profile is covered. The description goes further by disclosing data provenance (aggregated official DfT MOT test results, not estimates), the aggregation nature of the figures, and that responses carry a whatbreaks.uk attribution line — all useful context an agent would not get from the schema.

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 what the tool returns before the usage trigger and provenance note. Dense and mostly waste-free, though the attribution-line sentence is operational detail that could be trimmed.

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?

There is no output schema, yet the description explains what comes back (per-category failure rates, riskiest components with typical failure mileages) and where the data originates. Combined with fully described parameters and read-only annotations, an agent has everything needed to call it correctly.

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%, so make/model/year/mileage are already documented, including that generation is resolved via year. The description adds only a light hint that mileage affects output granularity ('overall and at a given mileage'), which does not meaningfully exceed the schema. Baseline 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 names a specific resource (UK MOT failure data for a given car) and enumerates the concrete outputs: per-category failure rates overall and at a mileage, plus riskiest components with typical failure mileages. It does not, however, contrast itself with the sibling mot_vehicle_search, so an agent must infer the boundary between a vehicle lookup and a reliability report.

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?

It gives clear situational context — use when a user is buying, comparing, or maintaining a used car sold in the UK. That is an explicit when-to-use trigger, but there are no exclusions or named alternatives (e.g., when mot_vehicle_search is the better entry point), so the routing guidance is incomplete.

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