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

Annotations only declare readOnlyHint and openWorldHint, so the safety profile is covered. The description adds genuinely useful behavior beyond that: results are ranked, each suggestion carries a live result count, demonstrating the autocomplete is backed by real query execution rather than static terms.

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 tight sentences that front-load the core function and then the integration hint. No filler, and the most load-bearing information (typeahead over partial queries) comes first.

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 an output schema present, the description does not need to enumerate return fields, and it appropriately focuses on what the tool is and how its output feeds prada_search. Nothing essential for correct invocation is missing.

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% for both parameters, so q ('partial search query') and limit (default 10, max 20) are already documented in the schema. The description reinforces the partial-query nature of q but adds no format or syntax detail beyond the structured fields. 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 ('Prada's own search-box typeahead suggestions for a partial query') and describes the returned artifact (ranked suggested phrases with live result counts). It is clearly distinguishable from prada_search, which it names explicitly.

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?

It tells the agent the input is a partial query and that a suggested phrase can be passed straight into prada_search's q parameter, which routes the agent between the two tools. It stops short of explicit when-not guidance, but the usage context is clear.

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