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

Annotations already cover readOnly/idempotent/openWorld/non-destructive, so the bar is lower, and the description still adds provenance (live proxy to whatbreaks.uk, aggregated from DfT anonymised MOT results) plus the multi-match fallback behavior. It does not mention latency, rate limits, or data recency beyond the source attribution.

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?

Front-loaded with what the tool returns, then usage context, then the retry hint — three dense sentences with no filler. Slightly packed, but every clause carries 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?

No output schema exists, and the description compensates by sketching the return shape (per-category rates, riskiest components, typical failure mileages, candidate list on ambiguous generations). Combined with annotations covering the safety profile, an agent has enough to call it correctly, though response format and pagination are unmentioned.

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 baseline is 3, but the description adds real meaning: mileage drives interpolation of failure rates, and year resolves the model generation. That clarifies how the two optional parameters interact with the core result rather than just restating field names.

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?

States a specific verb and resource: real UK MOT failure data, broken out as per-category failure rates and riskiest components with typical failure mileages, scoped to one model generation. This is clearly distinguishable from sibling tools like uk_mot_vehicle_search and the various recalls tools.

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?

Gives an explicit usage context ('buying, comparing or maintaining a car sold in the UK') and a concrete recovery path when several generations match (retry with year or exact model name). It does not, however, state when NOT to use it or name an alternative sibling, so routing between this and uk_mot_vehicle_search is still partly inferred.

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