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HomeCalc — Canadian Mortgage & Tax Calculators

Debt-to-Income (TDS) Calculator with Debt List

debt_to_income
Read-only

TDS from income, housing costs and an itemised debt list. Credit cards and lines of credit with no payment given default to 3% of the balance; car and personal loans need their real payment. Returns total balance, payments, available credit and GDS/TDS vs 39% / 44%.

Input Schema

NameRequiredDescriptionDefault
debtsNoEvery non-mortgage debt
annualIncomeYesHousehold gross annual income in CAD
housingCostsMonthlyNoMonthly housing costs: mortgage/rent, tax, heat, 50% condo

Schema Changelog

Changes observed during successful MCP inspections.

  1. Added

TDQS

A3.7/5.0
Behavior4/5

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

Annotations already cover the safety profile (readOnly, non-destructive, closed-world), so the bar is lower, and the description still adds real behavior: cards/LOCs with no payment silently default to 3% of balance while car and personal loans require their real payment, and the output includes balances, payments, available credit and GDS/TDS against 39%/44% thresholds. It does not mention rounding, currency handling, or what happens when housing costs are omitted.

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?

Two dense sentences with no filler; the default rule appears before the return-value summary, which is the right order. The final clause packs four return items and two thresholds into one sentence, which is efficient but slightly crowded.

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?

With no output schema, the description usefully enumerates the return payload and names the 39%/44% benchmark ratios. For a three-parameter read-only calculator this is close to complete, with only sibling disambiguation and edge-case behavior (missing housing costs, cap of 30 debts) left implicit in the schema.

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 coverage is 100%, so the schema already documents annualIncome, housingCostsMonthly and the nested debt fields including the 'blank = 3% of balance' rule. The description reinforces the default rule and adds the constraint that car and personal loans need their actual payment, which is only partially spelled out in the schema, so it sits at baseline-plus rather than adding substantial new meaning.

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 computation (total debt service ratio) from three named inputs (income, housing costs, itemised debts) and lists what comes back. An agent can tell it is a ratio calculator rather than a mortgage qualifier or generic debt_service_ratio, though the description never explicitly contrasts itself with the debt_service_ratio sibling.

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 input list (you supply income, housing costs and a debt array) and by the domain rules for defaults, but there is no explicit 'use this when...' or exclusion against debt_service_ratio or mortgage_qualifier. The agent must infer the choice from name and inputs alone.

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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