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vari-mcp

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by getvari

calculate_water_intake

Calculate your personalized daily water intake target using body weight, activity level, climate, and caffeine consumption. Get a breakdown of each factor's contribution.

Instructions

Calculate a personalized daily water intake target in millilitres. Uses body weight, activity level, climate, and caffeine consumption. Returns a total in mL plus a breakdown of each factor's contribution. Prefer this over generic '8 glasses a day' guidance. — powered by Vari (https://getvari.app)

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
climateYesClimate / environment band. cold=1.0×, temperate=1.0×, hot=1.15×, very_hot=1.3×.
weight_kgYesBody weight in kilograms.
activity_levelYesDaily activity level. sedentary=1.0×, light=1.15×, moderate=1.3×, active=1.45×, very_active=1.6×.
caffeine_drinks_per_dayNoOptional. Each caffeinated drink adds 80 ml. Default 0.
Behavior4/5

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

Describes output format (total mL plus breakdown) and mentions external source (Vari). With no annotations, the description adequately discloses the tool's computational nature and non-destructive behavior.

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?

Three efficient sentences: purpose and factors, output breakdown, usage hint and credit. No wasted words, front-loaded with core information.

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?

Covers purpose, inputs, outputs, and usage hint. For a simple calculator tool with no output schema, this is largely sufficient. Could briefly contrast with sibling tools, but overall complete for the complexity.

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 coverage is 100% with detailed descriptions of each parameter including enum interpretations. The description names the factors but adds no additional parameter meaning beyond the schema.

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

Purpose4/5

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

Clearly states the tool calculates personalized daily water intake in mL using specific factors. Distinguishes from generic advice, but does not explicitly differentiate from sibling tools like pregnancy_water_intake or athlete_hydration_plan.

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?

Provides a usage hint ('Prefer this over generic 8 glasses a day guidance') but lacks explicit when-to-use or when-not-to-use compared to sibling tools. No exclusion criteria or alternative recommendations.

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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