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

Annotations already declare readOnlyHint=true, destructiveHint=false, openWorldHint=false. The description adds real context beyond them: the return shape ('search_inventory product shape plus a similarity score in [0, 1]') and an auth note ('No credentials needed'). It does not cover ranking order or pagination behavior, but the added return/auth detail clears the lowered bar.

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?

Three tight sentences: purpose first, return shape second, auth third. The example query earns its place by illustrating the natural-language input. No 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?

With no output schema, the description compensates by naming the return shape and similarity score, and it flags the auth requirement. What remains thin is the relationship to the sibling search_inventory and ranking/pagination behavior, but for a read-only search tool this is close to 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?

Schema description coverage is 100%, so all five parameters including the enum-constrained condition are documented in the schema itself. The description only illustrates the query parameter through an example and adds no syntax, filtering, or limit semantics beyond what the schema provides.

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+resource ('Semantic catalog search') and the ranking mechanism ('ranks listings by similarity to a natural-language description'), with a concrete example query. It implies but never names its obvious sibling search_inventory, so the agent must infer the split between semantic and keyword search.

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 phrase 'natural-language description' and the example 'something like AirPods but cheaper' implicitly signal when semantic search is preferred over exact-match search, but there is no explicit when-to-use/when-not or named alternative among the many siblings (search_inventory in particular). Usage is left to inference.

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