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

Annotations already cover the safety profile (readOnly, idempotent, non-destructive, closed-world), so the description's main added value is the non-obvious behavioral point that optional params expand results into per-version breakdowns rather than filtering them, plus the disclosure of weak-spot output. It does not address data recency, coverage limits, or what an unmatched make/model yields.

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?

Two sentences, front-loaded with the primary resource and its metrics, then the conditional extension. Dense but every clause carries information; a slight restructuring into a bulleted metric list would improve scannability but nothing is wasted.

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?

With no output schema, the description must carry the return-value burden, and it does so by naming each metric returned, including the qualitative weak-spot sections. Given only 2 of 5 params are required, a brief note on required make/model or on no-match behavior would close the remaining gap.

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 80%, so the schema already documents make, model, year and engine. The description nonetheless adds meaning the schema does not: that year/fuel/engine select version-level results, and that each version carries its own grade and failure weak spots. It does not clarify how engine tolerates litres vs. cc beyond the schema's example, or how multiple optional params combine.

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 the specific resource (a car model's MOT reliability, aggregated over all years) and enumerates the returned metrics (grade, first-time pass rate, points vs. typical car, share of UK cars beaten). It implicitly distinguishes itself from get_make_reliability by scoping to a model, but never names that sibling explicitly, so the differentiation requires inference.

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?

The instruction "Give year, fuel and/or engine to also get those versions" is genuine usage guidance for the optional parameters, and the "also get" phrasing correctly signals additive rather than restrictive behavior. However, there is no statement of when to choose this over get_make_reliability or search_cars, and no guidance on failure cases such as an unknown make/model.

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