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Proven Plaza Calculators & Open Data

Caulk Calculator (Tubes of Caulk or Sealant per Linear Foot)

calc_caulk
Read-only

How many tubes of caulk or sealant to buy: linear feet per cartridge for your joint width and depth (or a triangular corner bead), and cartridges for the total length. Formula: Cartridge volume = fl oz × 1.80469 cu in. Bead area = width × depth (or leg² ÷ 2). Linear feet per cartridge = volume ÷ (bead area × 12). Cartridges = length × (1 + waste) ÷ feet per cartridge.

Input Schema

NameRequiredDescriptionDefault
shapeNoBead shape; default rect
depth_inNoJoint depth (in); default 0.25
width_inNoJoint width (or bead leg) (in); default 0.25
waste_pctNoWaste (%); default 10
cartridge_flozNoCartridge size (fl oz); default 10.1
joint_length_ftNoTotal joint length (ft); default 100

Schema Changelog

Changes observed during successful MCP inspections.

  1. Added

TDQS

A4/5.0
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 goes further by disclosing the full computation chain (cartridge volume, bead area, feet per cartridge, waste factor), which lets an agent verify and explain results. It stops short of saying how the output is formatted or rounded.

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 answer-oriented statement is front-loaded, followed by the four formulas in execution order. No filler sentences; every clause carries either scope or computation detail, and the formula block is dense but each line earns its place.

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?

All six parameters are optional with schema-documented defaults, there is no output schema, and the description supplies the missing piece by naming the outputs (feet per cartridge, cartridge count) and the math behind them. An agent has enough to call this correctly without further context.

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 would be 3, but the description adds real meaning beyond the schema: it clarifies that the triangular case uses a 'corner bead' with leg² ÷ 2, explaining how shape=tri reinterprets width_in as a leg length, and ties waste_pct directly into the cartridge formula.

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?

The description opens with a specific verb-and-resource statement ('How many tubes of caulk or sealant to buy') and names the two quantities returned: linear feet per cartridge and cartridges for total length. The caulk/sealant resource is distinct enough from the many other calc_* siblings that an agent can route to it, though it never explicitly contrasts itself with adjacent tools like calc_paint or calc_grout.

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?

Usage is implied rather than stated: the reader infers this is for estimating sealant purchases from joint dimensions and total length. There is no explicit when-to-use, when-not-to-use, or named alternative among the sibling calculators, so the agent must derive applicability from the resource name alone.

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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