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

Annotations already cover the safety profile (read-only, idempotent, non-destructive, closed-world), so the description's added value is the 'most-common' aggregation semantics — this returns a typical/derived value rather than a single authoritative record — plus the dual data sources. It doesn't discuss coverage gaps (e.g., missing year, sparse inventory) but adds real context beyond the annotations.

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, followed by the returned fields and a compact usage example. Two sentences plus an example, with essentially no wasted wording; the field list is close to redundant with the output schema but still orienting.

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 simple three-parameter, read-only lookup with an output schema and full annotation coverage, the description is largely sufficient: it explains the derivation, the aggregation behavior, and the e-bike special case. Only the lack of sibling differentiation and parameter naming conventions leaves a small 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 description coverage is 0%, so the description must compensate. It does communicate that year is optional and acts as a narrowing qualifier (bracketed [+year]) and that brand+model identify the bike, but it gives no format guidance (e.g., exact model naming) for the three parameters.

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 concrete resource (aggregated spec sheet for brand+model[+year]) and its provenance (live UK inventory plus catalogue record). It also enumerates the fields returned, so the agent knows exactly what it gets. It does not explicitly distinguish itself from close siblings like get_model_info or compare_bikes, which keeps it from a 5.

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 example question ('what groupset does a Canyon Endurace usually have?') implies the intended use case well. However, there is no explicit when-to-use/when-not guidance and no mention of when to prefer get_model_info, compare_bikes, or search_bikes instead.

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