"""Compare current vs proposed loan scenarios."""
from __future__ import annotations
import math
from datetime import datetime, timezone
from typing import Any
TOOL_META: dict[str, Any] = {
"name": "refinancing_analyzer",
"description": "Evaluates refinance savings, break-even, and NPV for proposed loan terms.",
"inputSchema": {
"type": "object",
"properties": {
"current_loan": {"type": "object"},
"proposed_loan": {"type": "object"},
"discount_rate": {"type": "number", "default": 0.05},
},
"required": ["current_loan", "proposed_loan"],
},
"outputSchema": {
"type": "object",
"properties": {
"status": {"type": "string"},
"data": {"type": "object"},
"timestamp": {"type": "string"},
},
},
}
def refinancing_analyzer(
current_loan: dict[str, Any],
proposed_loan: dict[str, Any],
discount_rate: float = 0.05,
**_: Any,
) -> dict[str, Any]:
"""Return refinance recommendation metrics."""
try:
remaining_balance = float(current_loan.get("remaining_balance", 0.0))
current_rate = float(current_loan.get("rate", 0.0))
remaining_months = int(current_loan.get("remaining_months", 0))
current_payment = float(current_loan.get("monthly_payment", 0.0))
proposed_rate = float(proposed_loan.get("rate", 0.0))
proposed_term = int(proposed_loan.get("term_months", remaining_months))
closing_costs = float(proposed_loan.get("closing_costs", 0.0))
if remaining_months <= 0 or proposed_term <= 0:
raise ValueError("Loan terms must be positive")
proposed_payment = _monthly_payment(remaining_balance, proposed_rate, proposed_term)
monthly_savings = current_payment - proposed_payment
break_even_months = math.ceil(closing_costs / monthly_savings) if monthly_savings > 0 else math.inf
total_interest_current = current_payment * remaining_months - remaining_balance
total_interest_proposed = proposed_payment * proposed_term - remaining_balance + closing_costs
total_interest_savings = total_interest_current - total_interest_proposed
npv_savings = _npv(monthly_savings, discount_rate / 12, min(remaining_months, proposed_term)) - closing_costs
refinance_recommended = monthly_savings > 0 and npv_savings > 0
data = {
"refinance_recommended": refinance_recommended,
"monthly_savings": round(monthly_savings, 2),
"break_even_months": break_even_months if break_even_months != math.inf else None,
"total_interest_savings": round(total_interest_savings, 2),
"npv_savings": round(npv_savings, 2),
}
return {
"status": "success",
"data": data,
"timestamp": datetime.now(timezone.utc).isoformat(),
}
except Exception as exc:
_log_lesson("refinancing_analyzer", str(exc))
return {
"status": "error",
"data": {"error": str(exc)},
"timestamp": datetime.now(timezone.utc).isoformat(),
}
def _monthly_payment(principal: float, rate: float, months: int) -> float:
monthly_rate = rate / 12
if monthly_rate == 0:
return principal / months
return principal * (monthly_rate * (1 + monthly_rate) ** months) / ((1 + monthly_rate) ** months - 1)
def _npv(cash_flow: float, rate: float, periods: int) -> float:
if rate == 0:
return cash_flow * periods
return cash_flow * (1 - (1 + rate) ** -periods) / rate
def _log_lesson(skill_name: str, error: str) -> None:
with open("logs/lessons.md", "a", encoding="utf-8") as handle:
handle.write(f"- [{datetime.now(timezone.utc).isoformat()}] {skill_name}: {error}\n")
