Microapp

coffee-ratio-calculator

Read-onlyIdempotent

Compute the coffee-to-water ratio for popular brew methods (pour-over, French press, AeroPress, cold brew, espresso). Pick a method, enter coffee grams OR water ml, get the other variable plus recommended grind and brew time.

Input Schema

TableJSON Schema

Name	Required	Description
`ratio`	No	Override the default ratio for the chosen brew method. The number is N in '1:N' — grams of water per gram of coffee. Typical range 1.5 (espresso ristretto) to 20 (light pour-over). Omit to use the method's default.
`coffee_g`	No	Coffee grams. Required when solve_for='water'. Must be > 0.
`water_ml`	No	Water in millilitres. Required when solve_for='coffee'. Must be > 0. Water density is taken as 1 g/ml.
`solve_for`	Yes	Which variable to compute. 'water' takes coffee grams as input and returns water ml. 'coffee' takes water ml as input and returns coffee grams.
`brew_method`	Yes	The brew method. Each preset chooses a sensible default coffee-to-water ratio (pour_over 1:16, french_press 1:15, aeropress 1:14, cold_brew 1:8 concentrate, espresso 1:2).

Output Schema

TableJSON Schema

Name	Required	Description
`grind`	Yes	Recommended grind size for this brew method.
`notes`	Yes	Short note about the method.
`ratio`	Yes	Coffee-to-water ratio used (the 'N' in 1:N).
`coffee_g`	Yes	Coffee grams (rounded to 0.1 g).
`water_ml`	Yes	Water in millilitres (rounded to 1 ml).
`water_oz`	Yes	Water in US fluid ounces (rounded to 0.1 oz).
`brew_time`	Yes	Brew-time guideline for this brew method.
`brew_method`	Yes	Brew method id.
`ratio_label`	Yes	Ratio formatted as a 1:N string.
`brew_method_label`	Yes	Display label for the brew method.

Schema Changelog

Changes observed during successful MCP inspections.

AddedMay 21, 2026

TDQS

A4.2/5.0

Behavior4/5

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

Annotations already declare read-only, idempotent, and non-destructive behavior. The description adds that the tool returns recommended grind and brew time beyond the computed variable, and clarifies the OR relationship between coffee and water inputs. No contradiction with annotations.

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?

Two sentences, front-loaded with the action verb and resource, listing methods and succinctly describing input/output. No wasted words.

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?

With a well-documented schema, an output schema present, and low complexity, the description covers the primary workflow and additional outputs. It omits mention of ratio override, but that is already in the schema, so the description is sufficiently complete.

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 for all five parameters. The description summarizes the core relationship ('enter coffee grams OR water ml') but adds little beyond what the schema already specifies, so the baseline 3 applies.

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 uses the specific verb 'Compute' and targets a clear resource: coffee-to-water ratio for popular brew methods. It lists the methods and clarifies it returns the complementary variable plus grind and brew time, distinguishing it from sibling tools like coffee-habit-cost-calculator and recipe-scaler.

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

Usage Guidelines4/5

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

It provides clear context: use this tool to compute the ratio for a chosen brew method, entering either coffee grams or water ml. It implies the use case but does not explicitly name alternatives or exclude cases, so it stops short of a 5.

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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