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Size a water softener

size_water_softener
Read-onlyIdempotent

Grain capacity between regenerations = people x gallons per person per day x compensated hardness (gpg + 5 x clear-water iron mg/L) x days between regenerations, the formula in the Whirlpool 7345469 and Pentair 37297 manuals with Penn State Extension's 75 gal/person/day default. Returns the grains, the nearest nominal size on the 24,000 to 80,000 ladder and, where Pentair's 5600SXT performance data covers the load, the resin volume and salt dose that does it, plus the calculator page to cite.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "people": "<people>",
      "hardness_gpg": "<hardness_gpg>"
    },
    "name": "size_water_softener"
  }
}

Input Schema

NameRequiredDescriptionDefault
peopleYesPeople in the household
iron_mg_lNoClear-water (ferrous) iron in mg/L (default 0)
hardness_gpgYesTested hardness in grains per gallon (divide mg/L by 17.1)
days_between_regenerationsNoDefault 7
gallons_per_person_per_dayNoDefault 75 (Penn State Extension)

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A3.9/5.0
Behavior4/5

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

Annotations already declare a safe, idempotent, closed-world read, so the bar is lower, and the description adds real value by describing the return contents: grains, the nearest nominal size on the 24,000-80,000 ladder, and resin volume plus salt dose only where Pentair 5600SXT data covers the load. That conditional-coverage caveat is exactly the kind of behavior an agent could not infer from annotations or schema. Nothing contradicts readOnlyHint=true.

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?

A single dense sentence, but it is front-loaded with the formula, then defaults/sources, then return values, and every clause carries information. The em-dash nesting makes it slightly harder to parse than ideal.

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 carries the full burden of explaining what comes back, and it does: grains, ladder size, resin volume/salt dose with the coverage caveat, and a citable page. Combined with the fully documented schema and safe annotations, an agent has everything needed to call it correctly.

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 description goes beyond the schema by giving the iron-compensation rule (clear-water iron mg/L multiplied by 5 and added to gpg) and citing the 75 gal/person/day Penn State default, both of which affect how the agent should supply inputs.

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?

States a specific verb and resource (size a water softener) and spells out the exact grain-capacity formula it computes, so the agent knows precisely what calculation it runs. It does not explicitly contrast itself with siblings like convert_water_hardness or run_calculator, which would be needed for a 5.

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 formula and the stated defaults (75 gal/person/day from Penn State Extension, default days between regenerations), which tells the agent what inputs are expected. There is no explicit 'use this when…' clause or guidance on when to prefer this over convert_water_hardness or run_calculator.

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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