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FinanceGenius.AI

Calculate loan EMI

calculate_emi
Read-only

Calculate EMI for a loan with year-by-year amortisation schedule.

    Args:
        principal: Loan amount in rupees.
        annual_rate: Annual interest rate as a percentage (e.g. 10.5 for 10.5%).
        tenure_months: Loan tenure in months.

    Returns:
        Monthly EMI, total interest, total payment, and amortisation schedule.
    

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
principalYes
annual_rateYes
tenure_monthsYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.1/5.0
Behavior4/5

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

Annotations already declare readOnlyHint=true, openWorldHint=false and destructiveHint=false, so safety is covered. The description nonetheless adds genuinely useful behavior beyond the annotations by specifying the return contents (monthly EMI, total interest, total payment, amortisation schedule), which matters because no output schema exists.

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?

The one-line summary is front-loaded and the Args/Returns layout is standard and scannable. It is slightly verbose relative to the information conveyed, but nothing is redundant or wasted.

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?

For a pure-computation read-only tool with three required scalar params and no output schema, the description supplies the units, the interpretation of each input, and the expected outputs. Nothing an agent needs in order to call it correctly is missing.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters5/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%, so the description carries the full burden — and it does: principal in rupees, annual_rate as a percent (with a concrete 10.5 example), tenure_months in months. This resolves the realistic ambiguities (currency, percent vs decimal, month vs year) that the bare schema leaves open.

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 verb (calculate) and resource (loan EMI) and adds scope detail — year-by-year amortisation schedule — that separates it from the other numerical siblings like calculate_cagr, calculate_sip, and calculate_fd_maturity. An agent can identify the tool without opening the schema.

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?

There is no guidance on when to use this tool versus the many sibling calculators, no prerequisites, and no exclusions. Usage must be inferred entirely from the tool name and the word 'loan'.

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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