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

Annotations already declare read-only, idempotent, non-destructive, and closed-world behavior. The description adds useful behavioral detail beyond those annotations: parsing mixed numbers and fraction characters, using USDA FoodData Central values, and applying FDA label rounding.

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 dense sentence with the core action front-loaded. The parenthetical parsing detail and nutrition sourcing/rounding are relevant and no sentence is wasted.

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?

There is no output schema, so the description appropriately states that total and per-serving nutrition are recomputed. It does not specify the exact response fields or error behavior, but it is complete enough for an agent to understand and invoke the tool.

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 coverage is 100%, so parameter meanings are already well documented. The description still adds value by clarifying that factor and original-to-target-servings are alternative scaling modes and by noting mixed-number and fraction-character parsing.

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?

States a specific verb and resource: scales ingredient lines and recomputes nutrition. It clearly conveys the scaling-plus-nutrition purpose, though it does not explicitly differentiate itself from sibling tools such as calculate_recipe_nutrition.

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?

Explains the two supported scaling modes: by a factor, or from original to target servings. This gives clear usage context, but it does not state when to prefer this tool over the related nutrition-calculation or rounding siblings.

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