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

Beyond the read-only and idempotent annotations, it discloses the live-inventory scope, a non-obvious preference for higher-engagement listings, and rationale-bearing recommendations. However, "Returns up to 5 picks" is only consistent with the default because the limit parameter permits values up to 10.

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?

The opening sentence front-loads the resource, scope, and main inputs, followed by compact ranking and output details. The three examples illustrate meaningfully different requests without filler or unnecessary repetition.

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?

Together with the rich input schema and output schema, the description provides enough information for a normal recommendation call and explains its curation bias. Explicit alternatives to broad search tools and an accurate statement of the configurable result limit would make it fully complete.

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?

With 80% schema coverage, most parameters are already documented, while category is largely self-describing through its enum. The examples reinforce how budget, city, and intent combine, but add little parameter syntax or mapping guidance beyond the schema.

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 identifies the operation as curated bike recommendations from Cyclesite's live UK inventory, constrained by budget and intent. The engagement preference and per-pick rationale further distinguish it from raw listing-retrieval siblings such as search_bikes and get_recent_listings.

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 budget-and-intent framing and three concrete example requests make appropriate scenarios clear, including road, e-MTB, and commuting recommendations. It does not explicitly say when to use search or search_bikes instead for exhaustive or directly filtered results, so sibling routing remains implicit.

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