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

Annotations already declare readOnlyHint and openWorldHint, so the safety profile is covered. The description adds useful behavioral detail beyond that: the response is a ranked list of phrases, each carrying the live result count it would return. It doesn't discuss rate limits or the limit parameter's effect, but the added return-value insight is real value.

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 tightly written sentences, front-loaded with the core purpose and followed by the actionable integration tip. No redundancy or filler.

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?

An output schema exists, so return-shape explanation isn't required, and the annotations cover the safety profile. The description covers purpose and downstream usage well; only the undocumented 'limit' parameter leaves a minor gap for a low-complexity two-param tool.

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 carry parameter meaning. It explains 'q' as a partial query, but the optional 'limit' parameter is never mentioned, leaving half the parameters undocumented. Partial compensation warrants a baseline 3.

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 gives a specific verb+resource: 'Prada's own search-box typeahead suggestions for a partial query', producing 'a ranked list of suggested search phrases with the live result count'. It clearly distinguishes this from the product-returning sibling by naming prada_search as the downstream consumer of its output.

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 states the workflow context explicitly - pass a suggestion through to prada_search's q parameter for actual product results - which tells the agent this is an autocomplete-style helper, not a result endpoint. It stops short of an explicit when-not statement (e.g. don't call it with a complete query), so it's a clear 4 rather than a 5.

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