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macro_calc

Calculate daily macronutrient targets for protein, carbohydrates, and fat using body metrics and activity level to support your fitness goal: maintain, lose, or gain weight.

Instructions

Calculate daily macronutrient targets (protein, carbs, fat).

Parameters:
    weight — Weight in kg.
    height — Height in cm.
    age — Age in years.
    sex — 'male' (default) or 'female'.
    activity — Activity level (default: 'sedentary').
    goal — 'maintain' (default), 'lose', or 'gain'.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
weightYes
heightYes
ageYes
sexNomale
activityNosedentary
goalNomaintain

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior2/5

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

No annotations are provided, and the description lacks behavioral details such as the algorithm used (e.g., Mifflin-St Jeor), assumptions (e.g., activity level definitions), or output format. For a mathematical calculator, this transparency is insufficient.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is concise, with a clear verb and resource, followed by a bulleted parameter list. No unnecessary words or repetition. Efficiently structured.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness2/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool has 6 parameters (3 required) and an output schema (not shown in description), the description should indicate what the output contains. It fails to describe return values or validation rules, making it incomplete for a non-trivial calculator.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The description adds basic meaning to parameters (e.g., 'weight — Weight in kg') but with 0% schema coverage, it should explain valid values for 'activity' and 'goal'. The defaults are noted, but no enumeration or context is given, leaving ambiguity.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool's purpose: 'Calculate daily macronutrient targets (protein, carbs, fat).' It uses a specific verb ('Calculate') and resource ('macronutrient targets'), and it distinguishes itself from sibling health calculators like BMR or TDEE.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides no guidance on when to use this tool versus alternatives (e.g., bmr_calc, tdee_calc). It does not mention prerequisites, exclusions, or context. Users must infer usage from the parameter list.

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

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