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GVR2007

Artha

by GVR2007

compare_emi_vs_investment

Compare loan prepayment vs investing your surplus by projecting guaranteed interest savings against expected equity or FD returns, and get a recommendation on the better option.

Instructions

EMI vs Investment Comparator — answers "should I prepay my loan or invest the surplus?" by projecting the loan interest saved (a guaranteed return) against a realistic investment return (equity ~12% or FD) over a horizon, and recommending the better option.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
amountYesSurplus amount available to prepay or invest in ₹
loanRatePctYesLoan interest rate % per annum (e.g. 9)
horizonYearsNoComparison horizon in years (default 5)
compareAgainstNoBenchmark to invest against (default equity)
expectedReturnPctNoOverride expected investment return %
Behavior3/5

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

No annotations are provided, so the description carries the burden. It openly states the methodology (projecting guaranteed interest saved vs realistic investment return over a horizon) and that it issues a recommendation. It stops short of disclosing limitations like tax assumptions or prepayment penalties, but provides a reasonable behavioral sketch for a calculator.

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 sentence that front-loads the purpose and gives enough specificity in the remainder. Every clause contributes to understanding the tool's decision-support role; no filler words or repeated schema details.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

The tool has 5 parameters, no annotations, and no output schema, so the description must carry a balanced load. It does explain the core question and the comparison method, but it omits output format and key assumptions (e.g., tax effects, compounding), making it somewhat incomplete for a decision-critical finance tool.

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 baseline is 3. The description adds context for compareAgainst by specifying 'equity ~12% or FD' and 'over a horizon,' which loosely maps to compareAgainst and horizonYears, but it doesn't materially enhance what the schema already documents for parameters like expectedReturnPct.

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 opens with a clear title and answers a specific financial question ('should I prepay my loan or invest the surplus?'), identifying the resource (loan vs investment comparison) and the core action (projecting and recommending). This distinguishes it from siblings like calculate_fund_returns or get_benchmark_rates, which don't compare prepayment vs investing.

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?

It establishes a clear context: decision-makers with surplus cash weighing loan prepayment against investing, citing equity ~12% or FD as benchmarks. However, it does not name alternative tools or explicitly state when not to use it, so while the context is clear, exclusions are absent.

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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