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Proven Plaza Calculators & Open Data

Paver Calculator (Pavers, Base Gravel & Sand)

calc_paver
Read-only

Number of pavers for a patio, walkway or driveway plus cubic yards of compacted base and bedding sand. Formula: Pavers per sq ft = 144 ÷ (paver length × width); pavers = area × per sq ft × (1 + waste%). Base and sand cubic yards = area × depth(in) ÷ 324.

Input Schema

NameRequiredDescriptionDefault
width_ftNoArea width (ft); default 12
length_ftNoArea length (ft); default 16
waste_pctNoWaste allowance (more for patterns/curves) (%); default 10
base_depth_inNoBase depth (per your design) (in); default 4
sand_depth_inNoBedding sand depth (in); default 1
paver_width_inNoPaver width (in); default 4
paver_length_inNoPaver length (in); default 8

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 safety is covered. The description goes beyond that by disclosing the deterministic computation behavior and the outputs produced (paver count plus cubic yards), which is useful context for a calculation tool.

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 dense sentences: the purpose/scope is front-loaded, then the exact formulas follow. No filler, no repetition of schema fields, and the formula detail earns its place for a calculator.

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?

For a 7-parameter, zero-required, read-only calculator with no output schema, the description covers purpose, method, and the quantities returned. It is nearly complete; only explicit output units/format naming is left implicit.

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 description coverage is 100% with defaults on all seven parameters, so the schema carries parameter meaning. The formulas imply how waste_pct, base_depth_in, and sand_depth_in are consumed, but this adds only marginal meaning beyond the already-complete schema. Baseline 3 is appropriate.

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: pavers count for patio/walkway/driveway plus cubic yards of compacted base and bedding sand. This clearly distinguishes it from the many sibling calculators (calc_mulch_gravel, calc_asphalt, calc_concrete_slab, etc.) by naming the exact material and derived quantities.

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 by the resource named (compute materials for a paver project), but there is no explicit when-to-use, when-not-to-use, or pointer to an alternative sibling calculator. No prerequisites or exclusions are stated.

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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