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

Annotations already declare readOnlyHint=true, openWorldHint=true, idempotentHint=true, and destructiveHint=false, so the safety profile is covered. The description adds behavioral context by specifying what the search returns (brand, barcode, categories, image) and the domain scope (Open Beauty Facts), which is valuable beyond the annotations.

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?

A single, compact sentence that front-loads the core action, then details return fields, examples, and source. No wasted words; every clause contributes useful 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 simple search tool with only two parameters, annotations covering safety, and an output schema, the description fully explains the purpose, domain, and expected return fields. An agent has everything needed to select and invoke this tool correctly.

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%: the query parameter is described with examples, and limit has default/maximum documented. The description adds minimal extra parameter meaning beyond the schema (mostly redundant 'by name'), so a baseline of 3 is appropriate.

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 states a specific verb ('Search'), a clear resource ('cosmetics/personal-care products'), and the return fields (brand, barcode, categories, image). It also gives concrete examples (shampoo, lipstick, sunscreen) and names the data source (Open Beauty Facts), making it easy to distinguish from similar food product tools.

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?

While it doesn't explicitly name alternatives, the description clearly indicates this is for cosmetics/personal-care by name, and the sibling tool 'openbeautyfacts.product.barcode' exists for barcode lookups. The context is sufficient for an agent to infer when to use this search tool, though it doesn't provide explicit exclusions.

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