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nestegg-calculators

Mortgage Affordability

mortgage-affordability
Read-onlyIdempotent

Maximum loan and home price the income supports: the DTI cap on gross monthly income (less existing debts) sets the payment, whose present value at the rate and term is the loan.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
rateYesAnnual interest rate in percent.
dtiPctYesMax share of gross monthly income for the payment, in percent (e.g. 36).
termYearsYesLoan term in years.
downPaymentNoOptional. Cash down payment, added to the loan for the home price (default 0).
annualIncomeYesGross annual income.
monthlyDebtsNoOptional. Existing monthly debt payments (default 0).

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
maxLoanNoMax loan.
maxHomePriceNoMax home price.
maxMonthlyPaymentNoMax payment.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A3.7/5.0
Behavior4/5

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

Annotations already declare readOnlyHint and idempotentHint, covering safety and determinism. The description adds valuable behavioral context by explaining the DTI-cap-to-payment-to-present-value chain, which reveals how inputs are transformed into outputs without contradicting 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.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single well-structured sentence that front-loads the primary output ('Maximum loan and home price') and then succinctly defines the calculation. Every clause is meaningful, with no redundancy or filler.

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?

Given that an output schema exists (documenting return values), annotations cover safety, and the input schema fully documents all parameters, the description is sufficiently complete. It explains the core financial model without needing to repeat schema details. Minor gaps like edge-case behavior are acceptable given the strong structured metadata.

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% with individual parameter descriptions, so baseline is 3. The description goes beyond the schema by linking parameters conceptually: 'gross monthly income (less existing debts)' ties annualIncome and monthlyDebts, and 'home price' implies the role of downPayment. This relational meaning helps an agent understand how parameters interact.

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 clearly states the tool computes the maximum loan and home price supported by income, using DTI, rate, and term. It uses specific financial terminology that distinguishes it from generic present-value or dti tools, though it lacks an explicit action verb like 'calculate' and does not name siblings.

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

Usage Guidelines2/5

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

No explicit when-to-use guidance or comparison to alternatives is provided. The description explains the calculation logic but does not mention when this tool is preferred over related tools like dti, loan-apr, or present-value, making it hard for an agent to choose it correctly among many siblings.

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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