Search Danish Food Data

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

Annotations already declare readOnlyHint=true and idempotentHint=true, so the description need not repeat safety traits. It adds useful behavioral context by specifying the return format (per-100g calories/macros) and source attribution, which helps the agent interpret results. It does not disclose any additional edge cases or rate limits, but the provided annotations lower the 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?

The description is three sentences, front-loaded with the core action and scope, followed by return details and a usage hint. Every sentence contributes essential information with zero filler or redundancy.

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?

Given the tool complexity (search across two data sources, no output schema), the description adequately covers purpose, usage, return format, and source attribution. It does not explain result ordering, pagination, or empty-result behavior, but these are secondary for a search tool and the annotations cover safety.

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 67% (query and danishOnly have descriptions; limit lacks one). The description reinforces query semantics with examples (rugbrød, leverpostej) but does not add meaningful detail about limit or danishOnly beyond the schema. With coverage above 50%, 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 clearly states the tool's purpose with a specific verb ('Search') and resource ('Danish food/nutrition data by keyword'). It explicitly names the two data sources (Open Food Facts and DTU Frida) and notes the return type (per-100g calories and macros), which distinguishes it from sibling tools like barcode lookup or food details.

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 gives a clear usage scenario ('Use this to get real Danish nutrition values before logging a meal elsewhere') and explains the scope (keyword search across Danish food data). It does not explicitly state when not to use it or mention alternative tools, but the context and sibling names make the intended use clear.

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