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vdalhambra

axiom-calculator-mcp

mortgage_calculator

Read-only

Calculate monthly mortgage payments, total interest, and amortization details to plan home financing with options for property tax and insurance.

Instructions

Calculate monthly mortgage payment, total interest paid, and full amortization summary.

Returns the monthly principal+interest payment, total interest over the loan life, total cost of the home, break-even analysis, and the first 12 months of amortization. Optionally includes property tax and insurance in the total monthly cost.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
home_priceYesTotal home price in your currency
down_payment_pctYesDown payment percentage (e.g., 20 for 20%)
annual_rate_pctYesAnnual interest rate percentage (e.g., 3.5 for 3.5%)
yearsYesLoan term in years (e.g., 15, 20, 30)
monthly_extrasNoAdditional monthly costs: property tax + insurance + HOA (0 if unknown)

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Behavior3/5

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

Annotations already declare readOnlyHint=true, so the agent knows this is a safe calculation tool. The description adds useful context about what gets returned (monthly payment, total interest, amortization summary, break-even analysis) and optional property tax/insurance inclusion, which goes beyond the annotations. However, it doesn't mention computational limits, precision, or error handling.

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 perfectly structured with two focused paragraphs: first states core purpose and outputs, second adds optional feature. Every sentence adds value with zero wasted words, and key information is front-loaded.

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?

Given this is a read-only calculation tool with excellent annotations, 100% schema coverage, and an output schema exists, the description provides complete context. It clearly explains what the tool does, what it returns, and includes the optional tax/insurance feature - nothing essential is missing for agent understanding.

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?

With 100% schema description coverage, the input schema already fully documents all parameters. The description mentions 'optionally includes property tax and insurance' which aligns with the monthly_extras parameter, but adds minimal additional semantic context beyond what's in the schema. Baseline 3 is appropriate when schema does the heavy lifting.

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?

The description clearly states the tool calculates mortgage payments and related financial metrics with specific outputs listed. It distinguishes from sibling tools like 'compound_interest' and 'loan_comparison' by focusing specifically on mortgage amortization calculations.

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

Usage Guidelines4/5

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

The description provides clear context for when to use this tool (calculating mortgage payments, interest, amortization) but doesn't explicitly state when not to use it or name specific alternatives among the sibling tools. The context is sufficient but lacks explicit exclusion guidance.

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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