calc.engineer

loan amortization

loan_amortization

Computes a full loan amortization schedule given principal, annual interest rate, and term in months. Returns the fixed monthly payment, total interest, total payments, and a month-by-month breakdown of principal vs interest. Supports optional extra monthly payments — shows months saved and interest saved. Works for mortgages (30yr/15yr), auto loans, personal loans, and student loans. All currency-agnostic. Use with /run?page=1&page_size=12 to paginate the schedule array for context-friendly agent consumption.

Input Schema

TableJSON Schema

Name	Required	Description
`principal`	Yes	Loan principal amount in dollars (or any currency unit).
`term_months`	Yes	Loan term in months. Max 600 (50 years). Common values: 360 (30yr), 180 (15yr), 60 (5yr auto).
`extra_payment`	No	Optional fixed extra monthly payment toward principal. Defaults to 0.
`annual_rate_pct`	Yes	Annual interest rate as a percentage (e.g., 6.5 for 6.5%).

Output Schema

TableJSON Schema

Name	Required	Description
`schedule`	Yes	Month-by-month amortization schedule.
`payoff_months`	Yes	Actual number of months to pay off (may be less than term with extra payments).
`interest_saved`	Yes	Interest saved by extra payments vs. full term. 0 if no extra payments.
`total_interest`	Yes	Total interest paid over the life of the loan.
`total_payments`	Yes	Sum of all payments over the life of the loan.
`monthly_payment`	Yes	Fixed monthly payment (excluding extra payments).
`total_extra_paid`	Yes	Total extra payments made.

TDQS

A4.5/5.0

Behavior5/5

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

With no annotations, the description fully informs about tool behavior: computation, returns, support for extra payments with savings breakdown, and pagination. It discloses currency-agnostic nature and no destructive actions, meeting the full burden.

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 four sentences, front-loaded with core purpose, and each sentence adds distinct value (outputs, extras, loan types, pagination). No fluff or redundancy.

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 4 parameters and an output schema (confirmed by context), the description covers inputs, outputs, optional extra payment effects, loan types, and pagination. It is complete for an agent to decide and invoke the tool correctly.

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%, so the schema already documents all parameters. The description adds minimal extra semantics (e.g., currency-agnostic, pagination hint) but does not significantly enhance parameter understanding beyond the schema.

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 computes a full loan amortization schedule given principal, rate, and term, listing specific outputs. It distinguishes itself from sibling tools which are mostly electronic/engineering calculators, making its purpose unambiguous.

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 concrete usage context by listing applicable loan types (mortgage, auto, personal, student) and mentions pagination for schedule output. It does not explicitly state when not to use or name alternatives, but given the sibling list, this is sufficient for an agent.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

All calc.engineer tools Inspect

Try in Browser

RayrunBuild, deploy, and operate MCP servers without becoming an infrastructure team.ray.runAd

Glama MCP Gateway

Add one secure layer between your agents and this server.

TDQS

A3.9/5.0

Disambiguation4/5

Despite 89 tools, each has a clearly distinct purpose with detailed descriptions that often reference related tools. Overlap exists (e.g., multiple LoRa/RF tools), but the descriptions are sufficient to distinguish them. Some confusion possible among similar-sounding tools like attenuator_pi and attenuator_tee, but the descriptions explicitly compare them.

Naming Consistency4/5

Consistent underscore-separated lowercase naming. Most tools follow a verb_noun pattern (e.g., capacitor_charge, wire_gauge) or noun_noun (power_cost). Minor inconsistencies such as 'bmi_calculator' vs 'solar_sizing' but overall predictable.

Tool Count2/5

89 tools is far too many for a single MCP server. This scope is more appropriate for multiple specialized servers. The sheer number will slow agent selection and increase cognitive load, reducing coherence.

Completeness3/5

Covers many domains (RF, solar, PCB, networking, math, etc.) but lacks depth in some areas (e.g., no three-phase power, no airflow calculations). Some domains have comprehensive coverage (LoRa/Meshtastic), but others feel incomplete for the tool count.

Resources

Need Help?