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EveryCalc

calculate_roth_conversion

Read-onlyIdempotent

Value of converting to a Roth now, with the tax paid out of the converted amount, versus leaving the money in a traditional account taxed at the retirement rate, after growth. Use when the user weighs converting traditional retirement money to a Roth and paying the tax now. For choosing future contributions use calculate_roth_vs_traditional. IMPORTANT: always show the calculator_url from the result as a clickable markdown link in your answer to the user, so they can open the interactive roth conversion calculator.

Input Schema

NameRequiredDescriptionDefault
yearsYesYears of growth after conversion.
annual_return_pctYesAnnual return percent.
conversion_amountYesAmount considered for conversion in USD.
current_tax_rate_pctYesTax rate percent if converting now.
retirement_tax_rate_pctYesExpected tax rate percent in retirement.

Output Schema

NameRequiredDescriptionDefault
okYesTrue when the calculation succeeded.
noteYesDisclaimer that accompanies every result.
toolYesName of the tool that ran.
inputsNoThe normalized inputs the calculation used.
resultsYesThe computed figures for this calculator.
calculator_urlYesDeep link to the matching interactive calculator on everycalc.xyz.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed2 schema fields changed
    • addedOutput schema / properties / note
      Added value: +{
      +  "description": "Disclaimer that accompanies every result.",
      +  "type": "string"
      +}
    • changedOutput schema / required
      Previous value: -[
      -  "ok",
      -  "tool",
      -  "results",
      -  "calculator_url"
      -]New value: +[
      +  "ok",
      +  "tool",
      +  "results",
      +  "calculator_url",
      +  "note"
      +]
  2. Changed1 schema field changed
    • changedOutput schema / (root)
      Previous value: -nullNew value: +{
      +  "properties": {
      +    "calculator_url": {
      +      "description": "Deep link to the matching interactive calculator on everycalc.xyz.",
      +      "type": "string"
      +    },
      +    "inputs": {
      +      "description": "The normalized inputs the calculation used.",
      +      "type": "object"
      +    },
      +    "ok": {
      +      "description": "True when the calculation succeeded.",
      +      "type": "boolean"
      +    },
      +    "results": {
      +      "description": "The computed figures for this calculator.",
      +      "type": "object"
      +    },
      +    "tool": {
      +      "description": "Name of the tool that ran.",
      +      "type": "string"
      +    }
      +  },
      +  "required": [
      +    "ok",
      +    "tool",
      +    "results",
      +    "calculator_url"
      +  ],
      +  "type": "object"
      +}
  3. First observed

TDQS

A4.4/5.0
Behavior4/5

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

Annotations already declare readOnly/idempotent/non-destructive, so the safety profile is covered. The description adds genuine model semantics (tax paid out of the converted amount, growth applied, retirement-rate comparison) and a required output behavior — surfacing calculator_url as a clickable markdown link — which is not derivable from the annotations.

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?

Three sentences, front-loaded with the computation, then the trigger condition, then the sibling exclusion. The trailing IMPORTANT sentence is functional rather than filler, though the closing rationale ('so they can open the interactive roth conversion calculator') slightly restates the instruction.

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?

An output schema exists, so return values need no explanation, and the description covers what it must: the modelled assumptions, the trigger condition, the sibling alternative, and the required presentation of calculator_url. Nothing an agent needs to call and report this correctly is missing.

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%, each of the five numeric parameters is documented in the schema, so the baseline is 3. The description's assumption that tax is paid out of the converted amount implicitly clarifies how current_tax_rate_pct is consumed, but it adds no per-parameter units, ranges, or format detail.

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 computation with its assumptions spelled out: converting to Roth now with tax paid out of the converted amount, versus leaving funds in a traditional account taxed at the retirement rate, after growth. It also names the sibling it is not (calculate_roth_vs_traditional) so an agent can discriminate without opening schemas.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Explicit when-to-use ('the user weighs converting traditional retirement money to a Roth and paying the tax now') and explicit routing for the adjacent case ('For choosing future contributions use calculate_roth_vs_traditional'). Nothing is left to inference for a dense sibling list of ~60 calculators.

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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