feat: add family financial planner with global childcare data

Made-with: Cursor

evals/test_family_planner.py

@@ -0,0 +1,67 @@
+import sys
+import os
+sys.path.insert(0, os.path.join(os.path.dirname(__file__), '..', 'tools'))
+from family_planner import plan_family_finances
+
+
+def test_family_plan_austin_one_child():
+    result = plan_family_finances(
+        current_city="Austin",
+        annual_income=120000,
+        portfolio_value=94000,
+        num_planned_children=1,
+    )
+    assert result is not None
+    assert result["monthly_cost_breakdown"]["childcare_monthly"] > 0
+    assert result["monthly_cost_breakdown"]["total_new_monthly_costs"] > 1000
+    assert "honest_assessment" in result
+    assert "alternatives" in result
+    assert "is_feasible" in result["income_impact"]
+
+
+def test_family_plan_two_children():
+    result = plan_family_finances(
+        current_city="Austin",
+        annual_income=120000,
+        partner_income=80000,
+        num_planned_children=2,
+    )
+    one_child = plan_family_finances("Austin", 120000, num_planned_children=1)
+    assert (
+        result["monthly_cost_breakdown"]["childcare_monthly"]
+        > one_child["monthly_cost_breakdown"]["childcare_monthly"]
+    )
+
+
+def test_family_plan_partner_reduces_hours():
+    result = plan_family_finances(
+        current_city="Austin",
+        annual_income=150000,
+        partner_income=80000,
+        partner_work_reduction=0.5,
+        num_planned_children=1,
+    )
+    assert result["monthly_cost_breakdown"]["income_reduction_monthly"] > 0
+
+
+def test_family_plan_international_cheaper():
+    result_berlin = plan_family_finances("Berlin", 120000, num_planned_children=1)
+    result_austin = plan_family_finances("Austin", 120000, num_planned_children=1)
+    assert (
+        result_berlin["monthly_cost_breakdown"]["childcare_monthly"]
+        < result_austin["monthly_cost_breakdown"]["childcare_monthly"]
+    )
+
+
+def test_family_plan_shows_alternatives():
+    result = plan_family_finances("Austin", 120000, num_planned_children=1)
+    assert "alternatives" in result
+    # Austin should suggest Williamson County as cheaper
+    assert len(result["alternatives"]) > 0
+
+
+def test_family_plan_what_helps():
+    result = plan_family_finances("Austin", 80000, num_planned_children=1)
+    assert "what_helps" in result
+    assert len(result["what_helps"]) > 0
+    assert "disclaimer" in result

tools/family_planner.py

@@ -0,0 +1,217 @@
+"""
+Family Financial Planner
+Models the financial impact of having children for any city worldwide.
+Source: US Dept of Labor + Care.com 2024 averages
+"""
+
+CHILDCARE_ANNUAL = {
+    "san francisco": 31000, "san-francisco": 31000,
+    "seattle": 26000,
+    "new york": 29000, "new-york": 29000, "nyc": 29000,
+    "boston": 28000,
+    "washington dc": 27000, "dc": 27000,
+    "los angeles": 24000, "la": 24000,
+    "chicago": 22000,
+    "portland": 22000,
+    "denver": 20000,
+    "minneapolis": 20000,
+    "austin": 18000,
+    "travis county": 18000,
+    "atlanta": 18000,
+    "miami": 19000,
+    "nashville": 17000,
+    "raleigh": 17000,
+    "williamson county": 16000,
+    "round rock": 16000,
+    "cedar park": 16000,
+    "dallas": 16000,
+    "houston": 16000,
+    "hays county": 15000,
+    "san marcos": 15000,
+    "kyle": 15000,
+    "phoenix": 15000,
+    "bastrop county": 14000,
+    "caldwell county": 13000,
+    "lockhart": 13000,
+    "london": 22000,
+    "toronto": 18000,
+    "sydney": 16000,
+    "berlin": 4000,
+    "paris": 5000,
+    "tokyo": 8000,
+    "amsterdam": 6000,
+    "stockholm": 5000,
+    "default": 18000,
+}
+
+
+def _estimate_monthly_take_home(annual_salary: float, city: str = "") -> float:
+    if annual_salary <= 44725:
+        federal = 0.12
+    elif annual_salary <= 95375:
+        federal = 0.22
+    elif annual_salary <= 200000:
+        federal = 0.24
+    else:
+        federal = 0.32
+    fica = 0.0765
+    no_tax = [
+        "tx", "wa", "fl", "nv", "tn", "wy", "sd", "ak",
+        "texas", "washington", "florida", "austin", "seattle",
+        "dallas", "houston", "nashville", "miami",
+    ]
+    state = 0.0 if any(s in city.lower() for s in no_tax) else 0.05
+    return (annual_salary * (1 - federal - fica - state)) / 12
+
+
+def plan_family_finances(
+    current_city: str,
+    annual_income: float,
+    partner_income: float = 0,
+    portfolio_value: float = 0,
+    num_planned_children: int = 1,
+    timeline_years: int = 5,
+    partner_work_reduction: float = 0.0,
+) -> dict:
+    """Model the financial impact of having children."""
+
+    city_lower = current_city.lower()
+
+    # Step 1: Get childcare cost
+    annual_childcare = CHILDCARE_ANNUAL.get("default", 18000)
+    for key in CHILDCARE_ANNUAL:
+        if key in city_lower or city_lower in key:
+            annual_childcare = CHILDCARE_ANNUAL[key]
+            break
+    monthly_childcare = (annual_childcare / 12) * num_planned_children
+
+    # Step 2: Get median rent for city
+    RENT_LOOKUP = {
+        "austin": 2100, "travis": 2100,
+        "williamson": 1995, "round rock": 1995,
+        "hays": 1937, "san marcos": 1937,
+        "bastrop": 1860, "caldwell": 1750,
+        "seattle": 2400, "san francisco": 3200,
+        "new york": 3800, "boston": 3100,
+        "denver": 1900, "chicago": 1850,
+        "miami": 2800, "nashville": 1800,
+        "los angeles": 2900, "dallas": 1700,
+        "london": 2800, "tokyo": 1800,
+        "berlin": 1600, "paris": 2200,
+    }
+    rent = 2000
+    for key, val in RENT_LOOKUP.items():
+        if key in city_lower:
+            rent = val
+            break
+
+    # Step 3: Calculate income
+    total_income = annual_income + partner_income
+    reduced_partner = partner_income * (1 - partner_work_reduction)
+    effective_income = annual_income + reduced_partner
+    income_reduction = partner_income - reduced_partner
+
+    # Step 4: Monthly financials
+    take_home_before = _estimate_monthly_take_home(total_income, current_city)
+    take_home_after = _estimate_monthly_take_home(effective_income, current_city)
+
+    food_clothing = 800 * num_planned_children
+    healthcare = 300 * num_planned_children
+    family_rent = rent * 1.3
+
+    total_new_costs = monthly_childcare + food_clothing + healthcare
+
+    surplus_before = take_home_before - (rent * 1.8)
+    surplus_after = take_home_after - (family_rent * 1.6) - total_new_costs
+
+    # Step 5: Income needed to maintain current surplus
+    current_surplus = take_home_before - (rent * 1.8)
+    income_needed = effective_income
+    test_income = effective_income
+    while True:
+        test_take_home = _estimate_monthly_take_home(test_income, current_city)
+        test_surplus = test_take_home - (family_rent * 1.6) - total_new_costs
+        if test_surplus >= current_surplus or test_income > 500000:
+            income_needed = test_income
+            break
+        test_income += 5000
+
+    # Step 6: Alternatives (cheaper nearby option for Austin users)
+    alternatives = []
+    if "austin" in city_lower or "travis" in city_lower:
+        wilco_childcare = CHILDCARE_ANNUAL.get("williamson county", 16000)
+        wilco_rent = 1995
+        savings = (
+            (annual_childcare - wilco_childcare) / 12
+            + (rent - wilco_rent)
+        )
+        if savings > 0:
+            alternatives.append({
+                "option": "Move to Williamson County",
+                "monthly_savings": round(savings),
+                "note": f"Saves ~${savings:,.0f}/mo vs Austin City",
+            })
+
+    # Step 7: International comparison
+    intl = {
+        "austin": annual_childcare,
+        "berlin": CHILDCARE_ANNUAL["berlin"],
+        "paris": CHILDCARE_ANNUAL["paris"],
+        "stockholm": CHILDCARE_ANNUAL.get("stockholm", 5000),
+        "note": "Western Europe has heavily subsidized childcare",
+    }
+
+    # Honest assessment
+    if surplus_after > 0:
+        honest_assessment = (
+            f"Having {num_planned_children} child(ren) in {current_city} adds "
+            f"~${round(total_new_costs):,}/mo in costs. "
+            f"You would have ${round(surplus_after):,}/mo surplus after family expenses — "
+            f"this is financially feasible."
+        )
+    else:
+        shortfall = abs(round(surplus_after))
+        honest_assessment = (
+            f"Having {num_planned_children} child(ren) in {current_city} adds "
+            f"~${round(total_new_costs):,}/mo in costs. "
+            f"Your current income leaves a ${shortfall:,}/mo shortfall after family expenses. "
+            f"You'd need ~${income_needed:,}/yr combined income to maintain your current lifestyle."
+        )
+
+    return {
+        "family_plan": {
+            "city": current_city,
+            "num_children": num_planned_children,
+            "timeline_years": timeline_years,
+        },
+        "monthly_cost_breakdown": {
+            "childcare_monthly": round(monthly_childcare),
+            "food_clothing_misc": round(food_clothing),
+            "healthcare_increase": round(healthcare),
+            "housing_increase_for_space": round(family_rent - rent),
+            "total_new_monthly_costs": round(total_new_costs),
+            "income_reduction_monthly": round(income_reduction / 12),
+        },
+        "income_impact": {
+            "take_home_before_kids": round(take_home_before),
+            "take_home_after_kids": round(take_home_after),
+            "monthly_surplus_before": round(surplus_before),
+            "monthly_surplus_after": round(surplus_after),
+            "is_feasible": surplus_after > 0,
+            "income_needed_to_maintain_surplus": round(income_needed),
+        },
+        "honest_assessment": honest_assessment,
+        "alternatives": alternatives,
+        "what_helps": [
+            f"Family member childcare eliminates ${round(monthly_childcare):,}/mo in costs",
+            "Nanny share splits childcare cost ~50%",
+            "Employer childcare benefits (check your benefits package)",
+            "Dependent Care FSA saves taxes on up to $5,000/yr",
+        ],
+        "international_comparison": intl,
+        "disclaimer": (
+            "Cost estimates vary significantly by provider. "
+            "Actual costs depend on childcare type and location."
+        ),
+        "data_source": "US Dept of Labor + Care.com 2024 averages",
+    }