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Proven Plaza Calculators & Open Data

Tile Grout Calculator (Pounds and Bags of Grout)

calc_grout
Read-only

How much grout a tile job takes from the tile size, joint width, joint depth and area, in pounds and bags. The grout density is editable so you can match your product. Formula: Each tile plus its joint is a (L + J) × (W + J) module, of which J × (L + W + J) is joint. Joint share = J(L + W + J) ÷ ((L + J)(W + J)). Grout volume (cu ft) = area × joint share × depth(in) ÷ 12; pounds = volume × density × (1 + waste); bags = ⌈pounds ÷ bag size⌉.

Input Schema

NameRequiredDescriptionDefault
bag_lbNoBag size (lb); default 25
area_sqftNoTiled area (sq ft); default 100
waste_pctNoWaste allowance (%); default 10
density_lb_cfNoGrout weight per cubic foot of joint (from your grout data sheet; ~100 sanded, ~85 unsanded) (lb/cu ft); default 100
tile_width_inNoTile width (in); default 12
joint_depth_inNoJoint depth (usually tile thickness) (in); default 0.375
joint_width_inNoJoint width (1/8 in = 0.125) (in); default 0.125
tile_length_inNoTile length (in); default 12

Schema Changelog

Changes observed during successful MCP inspections.

  1. Added

TDQS

A4.2/5.0
Behavior4/5

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

Annotations already declare readOnlyHint=true and openWorldHint=false, so the safety profile is covered. The description adds real behavioral value by disclosing the exact formula, the editable density assumption, and the waste/bag-rounding behavior (⌈pounds ÷ bag size⌉), which tells the agent precisely how inputs map to outputs.

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

Conciseness4/5

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

Front-loads the purpose in the first sentence, then supplies the formula in a compact notation. The formula is dense but every clause maps to a parameter or output, so it largely earns its space.

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

Completeness5/5

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

With no output schema, the description names both return units (pounds and bags) and explains the rounding rule for bags. All eight optional parameters with defaults are semantically covered, so an agent has everything needed to call and interpret the tool.

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

Parameters4/5

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

Schema coverage is 100%, so the baseline is 3, but the formula goes beyond the schema by showing how each input participates: L, W, J, depth, area, density, and waste all appear in the joint-share and volume equations. Density is explicitly flagged as product-dependent (~100 sanded, ~85 unsanded).

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?

States a specific verb and resource — computing grout quantity (pounds and bags) from tile size, joint width, joint depth, and area. This is clearly separable from the sibling calc_flooring_tile, which covers tile count rather than grout consumption.

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 scope (tile job grout amount) implies when to use it, but there is no explicit routing advice versus calc_flooring_tile or other tiling siblings, and no statement of assumptions or prerequisites. Usage is inferable but not guided.

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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