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

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false. The description adds useful context about marketplace mode (searches across every brand store without store selection) and the productRef relationship to get_product. No contradictions.

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 description is compact and well-structured: first paragraph introduces the core action, second paragraph gives usage guidance and result handling. No filler or redundant information.

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 read-only search tool with 4 parameters and no output schema, the description covers the essential context: when to use, what the query means, how filters work, and how to follow up via get_product. It is complete for an AI agent to select and invoke the tool effectively.

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 descriptions cover most parameters (75%), so the baseline is 3. The description adds meaning by elaborating on the query parameter with examples and explaining that filters narrow results for a single brand. This enhances the schema's basic descriptions.

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 clearly states the tool searches the catalog by a specific free-text query, with examples of query types. It distinguishes itself from browse_products (open-ended browsing) and get_product (full details via productRef).

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?

Explicitly states when to use: 'only when the shopper names something specific to look for.' It also names the alternative for other cases: 'For open-ended browsing, featured, best sellers, or a collection, use browse_products instead.'

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