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Proven Plaza Calculators & Open Data

Dehumidifier Size Calculator (Pints per Day by Room Size)

calc_dehumidifier_size
Read-only

What size portable dehumidifier you need, in pints per day, from the ENERGY STAR chart for your space size and how damp it is, with a liters and gallons conversion. Formula: Pick the ENERGY STAR range for the condition and size (under or over 2,000 sq ft), then take the top of the range, or the water your current unit removes per day if that is higher. Liters = pints × 0.4732; gallons = pints ÷ 8.

Input Schema

NameRequiredDescriptionDefault
area_sqftNoArea to dehumidify (sq ft); default 1000
conditionNoCondition without a dehumidifier; default very
pints_emptied_per_dayNoWater you empty now, if replacing a unit (optional) (pints/day); default 0

Schema Changelog

Changes observed during successful MCP inspections.

  1. Added

TDQS

A4.1/5.0
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 description's job is to add computational context, which it does: it names the data source, the band-selection logic, and the 'top of range, or your current unit's output if higher' rule. That rule is the kind of behavior an agent cannot derive from annotations or schema.

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-loaded with the answer type, then the method. The formula sentence is long and compresses three steps and two conversions, but each clause carries information; nothing is redundant with the schema.

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, and the description still tells the agent what comes back (pints/day plus liters and gallons) and how it is computed, which is sufficient for a 3-param read-only calculator. Minor gap: defaults are only in the schema, not restated, which is acceptable.

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 baseline is 3; the description goes beyond by explaining the 2,000 sq ft band split and clarifying that pints_emptied_per_day only overrides when it exceeds the chart value. That gives real meaning to an optional parameter the schema only labels 'if replacing a unit'.

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 ('what size portable dehumidifier you need, in pints per day') and anchors it to a named authority (ENERGY STAR chart). An agent can distinguish this from the many other calc_* sizing tools without inspecting the schema.

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 context is implied by 'your space size and how damp it is', but there is no explicit when-to-use/when-not guidance and no routing against nearby siblings like calc_ac_btu or calc_pool_heater_size. An agent can infer the scenario but gets no exclusion criteria.

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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