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

No annotations are provided, so the description must fully disclose behavioral traits. It does state the return values (prices, brands, images), but omits important behaviors such as potential external API latency, error handling, and that results are aggregated from three sources with differing reliability. This leaves the agent with insufficient operational expectations.

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 a single, front-loaded sentence with no wasted words. It conveys the core action, scope, and return fields efficiently, making it easy to parse.

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 a well-described schema but no output schema, the description gives a basic understanding. However, it does not clarify how results are aggregated, what 'source' values mean in practice, or how this tool relates to sibling tools like product_detail and price_comparison, leaving some contextual gaps.

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?

The input schema has 100% parameter description coverage, so the schema already explains limit, query, and source. The description adds no additional parameter-specific meaning beyond what the schema provides, thus baseline 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 uses a specific verb+resource ('Search products by name') and clearly distinguishes this tool from siblings by naming the multi-source scope (Algolia, UPCItemDB, Open Food Facts) and return fields (prices, brands, images). This makes its purpose unmistakable.

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 description implies usage for name-based product searches but provides no explicit guidance on when to choose this tool over alternatives like product_detail or price_comparison. It lacks exclusions or alternative recommendations, so the agent must infer usage from the tool name and siblings.

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