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

Annotations already cover read-only, idempotent and open-world behaviour, so the description focuses on what they cannot convey: the official DVSA source and a cost of 10 credits, which matters for call budgeting. It also previews the return content (latest reading and number of readings).

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?

One front-loaded sentence carries the check, its meaning, the data source, the return fields and the cost. It is dense but has no filler; only the parenthetical cost might be separated for scannability.

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 single-parameter, read-only lookup with no output schema, the description explains the data source and the shape of the result, which is most of what an agent needs. The absence of any note on missing-record behaviour or result framing keeps it short of a 5.

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% and there is a single 'plate' parameter documented as a required UK registration, so the description adds nothing further about the input. Baseline 3 applies.

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 — checks whether a UK car's recorded mileage ever went backwards between MOT tests — and frames the anomaly as clocking. This clearly separates it from the sibling uk_mot_history, which presumably returns raw test records.

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?

Usage is implied by the anomaly it detects (clocking detection), and the DVSA provenance hints at the data domain, but the description never says when to pick this over uk_mot_history or uk_vehicle, nor what to do if no records are found.

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