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

Annotations already establish read-only, idempotent, non-destructive behavior, and the description adds genuinely new context: mixed-number and fraction-character parsing, the measured density table used for gram conversion, and that unmatched lines are reported back. It does not characterize failure modes beyond unmatched lines.

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 dense sentences, front-loaded with the core action and supported by illustrative examples. Every sentence carries information, though the density is on the higher side.

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 return values, and it only partially does so—mentioning reported unmatched lines but not the shape of the successful scaled output (e.g., strings vs. structured quantity/unit/gram triples). For a tool this data-shaping, that gap matters.

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 the schema already documents every parameter thoroughly, making 3 the baseline. The description does add one relationship not encoded in the schema—that factor is an alternative to original_servings/target_servings—but does not elaborate further.

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 names a specific verb and resource (scaling ingredient lines) and gives concrete input examples, so an agent immediately knows what the tool consumes. It does not explicitly contrast itself with the sibling convert_ingredient, which handles single-ingredient conversion, leaving that boundary to inference.

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?

It states the two supported modes clearly: scale by a factor, or scale from original to target servings, plus the optional to_metric_weights mode. It stops short of naming when to prefer this over convert_ingredient or search_ingredients.

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