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

Annotations already cover the safety profile (readOnly, idempotent, openWorld, non-destructive), but the description adds real behavioral substance: it caps results at five matches, returns a verdict per match plus a 'say' line, and explains that brand-stated ingredient sources override unnamed labels and are quoted in brand_statement. That is meaningful beyond the structured fields.

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 sentences, front-loaded with purpose and source before the return-shape detail and the brand_statement nuance. The third sentence is dense and fairly niche but does explain a real behavior, so it earns its space without bloat.

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 carries the burden of describing returns, and it does so reasonably: up to five matches, verdicts, a 'say' line, and brand_statement. It is essentially complete for an agent to call and interpret the tool, with only minor gaps like ordering or empty-result behavior.

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 q (name/brand/barcode) and country (slug, default, Amazon-store effect) are already fully documented. The description adds no syntax or format detail beyond the schema, so the 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 states a specific verb and resource ('Find products by name and check them') plus the data source (Open Food Facts), so the agent knows exactly what it does. It does not, however, differentiate itself from the close siblings check_product_by_barcode and ask_is_it_halal, which appear to overlap heavily.

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?

Usage is implied by 'by name or brand' and the example query, suggesting it is used when the agent has a name/brand rather than a barcode. But there is no explicit when-to-use, when-not, or routing to the obvious alternative (check_product_by_barcode) for barcode lookups, so guidance 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.