UK Data for Agents

calculate_calorie_intake

Read-onlyIdempotent

Calculates recommended daily calorie intake using the Mifflin-St Jeor equation and macronutrient distribution based on personal characteristics and fitness goals. Returns total daily energy expenditure (TDEE) and grams of protein, carbohydrates, and fats. (cost: 1 credit)

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {},
    "name": "calculate_calorie_intake"
  }
}

Input Schema

Name	Required	Description
`age`	No	number, required, age in years
`sex`	No	string, required, biological sex ('male' or 'female')
`goal`	No	string, required, fitness goal ('maintain', 'lose', 'gain')
`height_cm`	No	number, required, height in centimeters
`weight_kg`	No	number, required, body weight in kilograms
`activity_level`	No	string, required, physical activity level ('sedentary', 'lightly_active', 'moderately_active', 'very_active', 'extra_active')

Schema Changelog

Changes observed during successful MCP inspections.

AddedNov 7, 2026

TDQS

A4/5.0

Behavior4/5

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

With annotations already declaring read-only, idempotent, non-destructive, and open-world behavior, the description adds useful context: it names the formula, describes the returned values, and discloses a 1-credit cost. It does not mention assumptions or limitations of the equation, but the key behavioral facts beyond the annotations are present.

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 two efficient sentences with the purpose and outputs front-loaded. The credit-cost note is short and useful, and there is no redundant wording.

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

Completeness4/5

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

For a read-only calculator with a fully documented schema and no output schema, the description explains the calculation method, outputs, and cost. It is nearly complete, though it could briefly note assumptions or typical use limits of the Mifflin-St Jeor equation.

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?

Schema description coverage is 100%, so each parameter already has documentation. The description only refers generally to personal characteristics and fitness goals and does not add per-parameter meaning beyond the schema; baseline 3 is appropriate.

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 states a specific verb and resource: calculates recommended daily calorie intake. It also names the Mifflin-St Jeor equation, macronutrient distribution, and the exact outputs, making it distinguishable from generic calculators such as calculate_bmi.

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

Usage Guidelines3/5

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

The description implies usage for personal characteristics and fitness goals, but it does not explicitly say when to use this tool versus alternatives such as calculate_bmi. There are no exclusions or prerequisites, so the agent must infer the appropriate context.

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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