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Proven Plaza Calculators & Open Data

Paint Calculator (Gallons for Walls)

calc_paint
Read-only

Gallons of wall paint from room perimeter and height, minus doors and windows, for any number of coats. Formula: Paintable area = perimeter × height − 20 sq ft per door − 15 sq ft per window. Gallons = area × coats ÷ label coverage.

Input Schema

NameRequiredDescriptionDefault
coatsNoCoats; default 2
doorsNoDoors; default 1
windowsNoWindows; default 2
wall_height_ftNoWall height (ft); default 8
wall_perimeter_ftNoRoom perimeter (ft); default 48
coverage_sqft_per_galNoCoverage (from your can label) (sq ft/gal); default 350

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.2/5.0
Behavior4/5

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

Annotations declare readOnlyHint=true and openWorldHint=false, so the safety profile is covered. The description goes beyond that by revealing the exact deterministic computation, including the fixed per-door (20 sq ft) and per-window (15 sq ft) deductions — genuine behavioral context for a calculator.

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 tight sentences, front-loaded with the output and inputs, then the formula. Every clause earns its place with no filler.

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?

No output schema exists, but the description names the computed result ('Gallons = area × coats ÷ label coverage'), which effectively documents the return. It omits rounding/precision details, a minor gap for a pure deterministic calculator.

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 description coverage is 100%, so the baseline is 3, but the description adds meaning the schema does not: the hardcoded 20 sq ft/door and 15 sq ft/window deductions and that gallons derive from perimeter × height ÷ label coverage.

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+resource+unit: 'Gallons of wall paint from room perimeter and height, minus doors and windows, for any number of coats.' This clearly distinguishes it from siblings like calc_drywall or calc_flooring_tile, which compute different materials.

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 formula implies the scope (paintable wall area), so an agent can infer this is for wall-painting estimates, but there is no explicit when-to-use/when-not guidance or reference to a sibling for adjacent tasks.

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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