"""Break-even calculator for unit economics."""
from __future__ import annotations
from datetime import datetime, timezone
from typing import Any
TOOL_META: dict[str, Any] = {
"name": "break_even_analyzer",
"description": "Computes break-even units, revenue, margin of safety, and estimated time to break even.",
"inputSchema": {
"type": "object",
"properties": {
"fixed_costs_monthly": {"type": "number"},
"variable_cost_per_unit": {"type": "number"},
"price_per_unit": {"type": "number"},
"current_monthly_units": {"type": "integer"},
},
"required": [
"fixed_costs_monthly",
"variable_cost_per_unit",
"price_per_unit",
"current_monthly_units",
],
},
"outputSchema": {
"type": "object",
"properties": {
"status": {"type": "string"},
"data": {"type": "object"},
"timestamp": {"type": "string"},
},
},
}
def break_even_analyzer(
fixed_costs_monthly: float,
variable_cost_per_unit: float,
price_per_unit: float,
current_monthly_units: int,
**_: Any,
) -> dict[str, Any]:
"""Return break-even metrics for the operating plan."""
try:
if price_per_unit <= variable_cost_per_unit:
raise ValueError("price_per_unit must exceed variable_cost_per_unit")
contribution_margin = price_per_unit - variable_cost_per_unit
break_even_units = fixed_costs_monthly / contribution_margin
break_even_revenue = break_even_units * price_per_unit
margin_of_safety = (
(current_monthly_units - break_even_units) / break_even_units if break_even_units else 0
)
months_to_break_even = _months_to_break_even(current_monthly_units, break_even_units)
data = {
"break_even_units": round(break_even_units, 2),
"break_even_revenue": round(break_even_revenue, 2),
"margin_of_safety_pct": round(margin_of_safety * 100, 2),
"months_to_break_even": months_to_break_even,
}
return {
"status": "success",
"data": data,
"timestamp": datetime.now(timezone.utc).isoformat(),
}
except Exception as exc:
_log_lesson("break_even_analyzer", str(exc))
return {
"status": "error",
"data": {"error": str(exc)},
"timestamp": datetime.now(timezone.utc).isoformat(),
}
def _months_to_break_even(current_units: int, break_even_units: float) -> float:
if current_units <= 0:
return float("inf")
if current_units >= break_even_units:
return 0.0
assumed_growth = max(1, current_units * 0.1)
months_needed = (break_even_units - current_units) / assumed_growth
return round(months_needed, 1)
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")
