calc_pnpr

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It explains the output calculation but does not disclose how inputs are handled—e.g., what happens if 'food' vs. 'protein_g'/'phosphorus_mg' is given, whether it looks up nutrients, or how missing values are treated. This is a significant transparency gap for a tool with multiple optional parameters.

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 that immediately states the calculation and its purpose. Every word earns its place; there is no redundancy or filler.

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 has 4 parameters, no annotations, and no schema descriptions, the description is insufficiently complete. It does not explain how the parameters interact, what 'food' expects, or the behavior when only some parameters are provided. Although an output schema exists, the input ambiguity remains unresolved, making this a minimally viable but gap-filled description.

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 0%, so the description must compensate for explaining parameters. While the formula implies protein_g and phosphorus_mg are numerator/denominator, it does not explain the roles of 'food' and 'grams', units, or defaults. The description adds minimal value over the bare schema, leaving the agent guessing about how to invoke the tool correctly.

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 calculates a phosphorus-protein ratio with the formula 'mg 磷 / g 蛋白' and specifies a use case ('用于限磷时挑选蛋白来源'). This is a specific verb+resource+scope, and the tool's purpose is distinct from siblings like lookup_food_nutrients or calc_nutrition_target. However, it does not explicitly differentiate itself from alternatives, so it stops short of a 5.

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 provides clear context for when to use the tool ('when restricting phosphorus to choose protein sources'). It does not mention alternative tools or when not to use it, so it lacks the 'when-not' guidance required for a 5.

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