strategies: spending input is honoured + new "Custom" preset with guardrails

The user noticed the "Annual spending" field was a no-op for Trinity,
GK, VPW, VPW+floor — the strategies internally hardcoded the year-0
withdrawal as `initial_portfolio × initial_rate` (4% / 5.5%) and
ignored what the user typed. Two fixes:

(1) Trinity + GK now use state.initial_withdrawal (= the user's
    spending_target) as the year-0 draw. GK's guardrail anchor
    becomes the implied initial rate (initial_withdrawal /
    initial_portfolio), so the rule shape adapts to the user's
    chosen rate. Both strategies still fall back to their preset
    rate × initial_portfolio when initial_withdrawal isn't set
    (test paths). VPW and VPW+floor stay algorithmic — they're
    "withdraw-what's-sustainable" by design and don't take a
    spending input.

(2) New "custom" preset (SpendingPlanStrategy) exposing all the
    knobs:
    - initial_spend = "Annual spending" input
    - annual_real_adjust_pct = scale last year's withdrawal by N%
      each year (0 = constant real £, +0.02 = 2%/yr healthcare
      creep, -0.005 = -0.5%/yr slow-down with age)
    - guardrail_threshold_pct = if portfolio falls below X% of
      starting NW, trigger a cut (None = disabled)
    - guardrail_cut_pct = cut last year's withdrawal by Y% each
      triggered year

Adjust applies first, then guardrail cut — so a triggered year in
+2% adjust mode goes 40k → 40.8k → 36.7k.

UI: "custom" added to the strategy dropdown; when selected, three
extra fields appear (annual real adjustment %, guardrail trigger
threshold, guardrail cut size) with hints. The existing inputs
(spending, NW seed) drive year 0 across all strategies that use
them. About-the-model panel updated.

10 new tests on SpendingPlanStrategy + adjusted GK tests for the
new spending_target-aware behaviour. 209 backend tests + 7
frontend tests. mypy + ruff + tsc all pass.

Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>

fire_planner/api/schemas.py

@@ -238,6 +238,16 @@ class SimulateRequest(BaseModel):
     #                   recent regime only (~6 years). Glide path is moot.
     returns_mode: str = Field(default="shiller", pattern="^(shiller|manual|wealthfolio)$")
     manual_real_return_pct: Decimal | None = None
+    # Custom spending-plan parameters — only consulted when strategy="custom".
+    # All real-£ / real-fraction. annual_real_adjust_pct = 0 means constant
+    # real spending (Trinity-shape). Non-zero scales last year's withdrawal
+    # multiplicatively each year (e.g. -0.005 for slow-down with age,
+    # +0.02 for healthcare creep). Guardrail cuts spending by
+    # `guardrail_cut_pct` whenever the portfolio falls below
+    # `guardrail_threshold_pct` of its starting value; null disables.
+    annual_real_adjust_pct: Decimal = Decimal("0")
+    guardrail_threshold_pct: Decimal | None = None
+    guardrail_cut_pct: Decimal = Decimal("0.10")
 
 
 class SimulateResult(BaseModel):

fire_planner/api/simulate.py

@@ -105,13 +105,22 @@ def _project(req: SimulateRequest, paths: np.ndarray) -> tuple[SimulationResult,
         ]
         cashflow_adjustments = events_to_cashflow_array(engine_events, req.horizon_years)
 
+    strategy = build_strategy(
+        req.strategy,
+        floor=floor,
+        annual_real_adjust_pct=float(req.annual_real_adjust_pct),
+        guardrail_threshold_pct=(float(req.guardrail_threshold_pct)
+                                 if req.guardrail_threshold_pct is not None else None),
+        guardrail_cut_pct=float(req.guardrail_cut_pct),
+    )
+
     started = time.perf_counter()
     result = simulate(
         paths=paths,
         initial_portfolio=float(req.nw_seed_gbp),
         spending_target=float(req.spending_gbp),
         glide=get_glide(req.glide_path),
-        strategy=build_strategy(req.strategy, floor=floor),
+        strategy=strategy,
         regime=build_regime_schedule(req.jurisdiction, req.leave_uk_year),
         horizon_years=req.horizon_years,
         annual_savings=annual_savings,

fire_planner/scenarios.py

@@ -22,6 +22,7 @@ from fire_planner.glide_path import GLIDE_PATHS
 from fire_planner.simulator import RegimeFn, constant_regime, jurisdiction_schedule
 from fire_planner.strategies.base import WithdrawalStrategy
 from fire_planner.strategies.guyton_klinger import GuytonKlingerStrategy
+from fire_planner.strategies.spending_plan import SpendingPlanStrategy
 from fire_planner.strategies.trinity import TrinityStrategy
 from fire_planner.strategies.vpw import VpwStrategy, VpwWithFloorStrategy
 from fire_planner.tax.base import TaxRegime
@@ -58,7 +59,13 @@ class ScenarioSpec:
                 f"glide-{self.glide_path}")
 
 
-def build_strategy(name: str, floor: float | None = None) -> WithdrawalStrategy:
+def build_strategy(
+    name: str,
+    floor: float | None = None,
+    annual_real_adjust_pct: float = 0.0,
+    guardrail_threshold_pct: float | None = None,
+    guardrail_cut_pct: float = 0.10,
+) -> WithdrawalStrategy:
     if name == "trinity":
         return TrinityStrategy()
     if name == "guyton_klinger":
@@ -69,6 +76,12 @@ def build_strategy(name: str, floor: float | None = None) -> WithdrawalStrategy:
         if floor is None:
             raise ValueError("vpw_floor strategy requires a `floor` value (real GBP)")
         return VpwWithFloorStrategy(floor=floor)
+    if name == "custom":
+        return SpendingPlanStrategy(
+            annual_real_adjust_pct=annual_real_adjust_pct,
+            guardrail_threshold_pct=guardrail_threshold_pct,
+            guardrail_cut_pct=guardrail_cut_pct,
+        )
     raise KeyError(f"Unknown strategy: {name!r}")
 
 

fire_planner/strategies/guyton_klinger.py

@@ -41,17 +41,26 @@ class GuytonKlingerStrategy(WithdrawalStrategy):
         self.initial_rate = initial_rate
 
     def propose_withdrawal(self, state: StrategyState) -> float:
+        # Year 0 = the user's target spending; the implied initial rate
+        # (initial_withdrawal / initial_portfolio) becomes the anchor
+        # the guardrails compare against. Falls back to the preset rate
+        # × initial_portfolio when no target was given.
+        target_initial = (state.initial_withdrawal
+                          if state.initial_withdrawal > 0 else
+                          state.initial_portfolio * self.initial_rate)
         if state.year_idx == 0:
-            return state.initial_portfolio * self.initial_rate
+            return target_initial
         if state.portfolio <= 0:
             return 0.0
+        implied_initial_rate = (target_initial / state.initial_portfolio
+                                if state.initial_portfolio > 0 else self.initial_rate)
         last_w = state.last_withdrawal
         current_rate = last_w / state.portfolio
         years_left = state.horizon_years - state.year_idx
         # Capital-preservation cut: only if more than 15 years remain.
-        if (current_rate > self.initial_rate * CAPITAL_PRESERVATION_RATIO
+        if (current_rate > implied_initial_rate * CAPITAL_PRESERVATION_RATIO
                 and years_left > MIN_HORIZON_FOR_CUT):
             return last_w * (1 - ADJUSTMENT)
-        if current_rate < self.initial_rate * PROSPERITY_RATIO:
+        if current_rate < implied_initial_rate * PROSPERITY_RATIO:
             return last_w * (1 + ADJUSTMENT)
         return last_w

fire_planner/strategies/spending_plan.py

@@ -0,0 +1,62 @@
+"""Custom user-defined spending plan.
+
+A flexible strategy where the user chooses every knob:
+
+- `initial_spend` — year 0 withdrawal in real GBP (taken from
+  `state.initial_withdrawal` if not overridden).
+- `annual_real_adjust_pct` — fraction by which last year's withdrawal
+  scales each subsequent year, on top of inflation. 0.0 = constant
+  real GBP (Trinity-shape). +0.02 = 2%/yr above-inflation creep
+  (e.g. healthcare). -0.005 = -0.5%/yr decreasing spend (slowing
+  down with age).
+- `guardrail_threshold_pct` — if portfolio drops below this fraction
+  of the starting NW, apply a cut. None = no guardrail.
+- `guardrail_cut_pct` — fraction by which to cut last year's
+  withdrawal when triggered. Applied multiplicatively each triggered
+  year — not "snap to threshold-implied rate", just a soft cut.
+
+The cut is checked AFTER the annual adjustment, so a cut + an
+increase don't double-apply: cut wins.
+
+Compared to Guyton-Klinger this is simpler — one threshold, one
+cut size, no prosperity rule. If the user wants the prosperity rule
+behaviour they can pick the GK preset.
+"""
+from __future__ import annotations
+
+from fire_planner.strategies.base import StrategyState, WithdrawalStrategy
+
+
+class SpendingPlanStrategy(WithdrawalStrategy):
+    name = "custom"
+
+    def __init__(
+        self,
+        initial_spend: float | None = None,
+        annual_real_adjust_pct: float = 0.0,
+        guardrail_threshold_pct: float | None = None,
+        guardrail_cut_pct: float = 0.10,
+    ) -> None:
+        self.initial_spend = initial_spend
+        self.annual_real_adjust_pct = annual_real_adjust_pct
+        self.guardrail_threshold_pct = guardrail_threshold_pct
+        self.guardrail_cut_pct = guardrail_cut_pct
+
+    def propose_withdrawal(self, state: StrategyState) -> float:
+        if state.year_idx == 0:
+            # Explicit override wins; otherwise take the user's target.
+            return (self.initial_spend
+                    if self.initial_spend is not None and self.initial_spend > 0 else
+                    state.initial_withdrawal)
+        if state.portfolio <= 0:
+            return 0.0
+
+        proposed = state.last_withdrawal * (1.0 + self.annual_real_adjust_pct)
+
+        if (self.guardrail_threshold_pct is not None
+                and state.initial_portfolio > 0):
+            trigger_at = state.initial_portfolio * self.guardrail_threshold_pct
+            if state.portfolio < trigger_at:
+                proposed = proposed * (1.0 - self.guardrail_cut_pct)
+
+        return max(0.0, proposed)

fire_planner/strategies/trinity.py

@@ -1,9 +1,10 @@
-"""Trinity 4% Safe Withdrawal Rate.
+"""Constant-real-£ withdrawal (the classic 4% rule shape).
 
-Bengen's seminal 1994 paper + the Trinity Study (Cooley/Hubbard/Walz,
+Withdraw `state.initial_withdrawal` in year 0, then keep that real-£
-1998) — withdraw 4% of the starting balance in year 1, then keep the
+amount fixed for the rest of retirement. In a 4% / £1M setup the year-0
-real withdrawal constant for the rest of retirement. In our real-GBP
+draw is £40k, then £40k real every year after. The strategy's
-internal frame this is just "the same number every year".
+`initial_rate` is kept only as a fallback for callers that don't feed
+`state.initial_withdrawal`.
 """
 from __future__ import annotations
 
@@ -20,5 +21,10 @@ class TrinityStrategy(WithdrawalStrategy):
 
     def propose_withdrawal(self, state: StrategyState) -> float:
         if state.year_idx == 0:
+            # Year 0 = the user's target spending. Falls back to
+            # initial_rate × initial_portfolio if no target was provided
+            # (zero or missing) for backwards compatibility.
+            if state.initial_withdrawal > 0:
+                return state.initial_withdrawal
             return state.initial_portfolio * self.initial_rate
         return state.last_withdrawal

frontend/src/api/client.ts

@@ -243,6 +243,10 @@ export interface SimulateRequest {
   }>;
   returns_mode?: 'shiller' | 'manual' | 'wealthfolio';
   manual_real_return_pct?: string | null;
+  // Custom spending-plan params (only consulted when strategy='custom')
+  annual_real_adjust_pct?: string;
+  guardrail_threshold_pct?: string | null;
+  guardrail_cut_pct?: string;
 }
 
 export interface SimulateResult {

frontend/src/pages/WhatIf.tsx

@@ -11,7 +11,7 @@ import { FanChart } from '@/components/FanChart';
 import { gbp, pct } from '@/lib/format';
 
 const JURISDICTIONS = ['uk', 'cyprus', 'bulgaria', 'malaysia', 'thailand', 'uae', 'nomad'];
-const STRATEGIES = ['trinity', 'guyton_klinger', 'vpw', 'vpw_floor'];
+const STRATEGIES = ['trinity', 'guyton_klinger', 'vpw', 'vpw_floor', 'custom'];
 const GLIDES = ['rising', 'static_60_40'];
 const RETURNS_MODES = ['shiller', 'manual', 'wealthfolio'] as const;
 
@@ -35,13 +35,15 @@ const RETURNS_MODE_NOTES: Record<string, string> = {
 // reused in the "About the model" panel at the bottom.
 const STRATEGY_NOTES: Record<string, string> = {
   trinity:
-    'Withdraw 4% of the starting portfolio in year 1, then keep that real-£ amount fixed. Simple and famous, but rigid — never adapts to market crashes.',
+    'Withdraw your "Annual spending" amount in year 1, then keep that real-£ amount fixed. Simple Trinity-style — never adapts to market crashes. Now driven by the spending input you set above (was a hardcoded 4% in earlier versions).',
   guyton_klinger:
-    'Start higher (~5.5%) and follow guardrail rules: cut spending if the portfolio drops too far, raise it if it grows enough. Adapts to markets, sustainable on long horizons.',
+    'Withdraw your "Annual spending" amount in year 1, then follow guardrails: cut by 10% if the implied withdrawal rate exceeds 120% of the starting rate (and >15y left), raise 10% if it drops below 80%. Adapts to markets.',
   vpw:
-    'Variable Percentage Withdrawal — each year, withdraw a percentage based on years left and expected real return (annuity-style). Mathematically can\'t fail, but income swings can be wide.',
+    'Variable Percentage Withdrawal — each year, withdraw a percentage based on years left and expected real return (annuity-style). Ignores the "Annual spending" input — withdrawal is fully algorithmic. Mathematically can\'t fail, but income swings can be wide.',
   vpw_floor:
-    'VPW with a hard real-£ floor: never withdraw less than the floor, even if VPW says you should. Trades guaranteed lifestyle against ruin risk in bad sequences.',
+    'VPW with a hard real-£ floor: never withdraw less than the floor, even if VPW says you should. Ignores "Annual spending" but uses the floor input. Trades guaranteed lifestyle against ruin risk in bad sequences.',
+  custom:
+    'Pick everything: initial spending (the "Annual spending" field above), an annual real-£ adjustment (e.g. -0.5%/yr to spend less as you age), and an optional drawdown guardrail that cuts spending by N% if the portfolio falls below X% of starting NW.',
 };
 
 const GLIDE_NOTES: Record<string, string> = {
@@ -75,6 +77,9 @@ const DEFAULTS: SimulateRequest = {
   seed: 42,
   returns_mode: 'shiller',
   manual_real_return_pct: '0.046',
+  annual_real_adjust_pct: '0',
+  guardrail_threshold_pct: null,
+  guardrail_cut_pct: '0.10',
 };
 
 export function WhatIf() {
@@ -122,11 +127,17 @@ export function WhatIf() {
 
   const onSubmit = (e: React.FormEvent) => {
     e.preventDefault();
+    const isCustom = form.strategy === 'custom';
     sim.mutate({
       ...form,
       floor_gbp: form.strategy === 'vpw_floor' ? form.floor_gbp : null,
       manual_real_return_pct:
         form.returns_mode === 'manual' ? form.manual_real_return_pct : null,
+      // Only send custom-plan params when strategy='custom' to avoid
+      // confusing reads in the persisted history later.
+      annual_real_adjust_pct: isCustom ? form.annual_real_adjust_pct : '0',
+      guardrail_threshold_pct: isCustom ? form.guardrail_threshold_pct : null,
+      guardrail_cut_pct: isCustom ? form.guardrail_cut_pct : '0.10',
     });
   };
 
@@ -221,6 +232,60 @@ export function WhatIf() {
               />
             </Field>
           )}
+          {form.strategy === 'custom' && (
+            <>
+              <Field
+                label="Annual real adjustment %"
+                hint="0 = constant real £ (Trinity shape). Positive grows spending each year (e.g. 0.02 = +2%/yr for healthcare). Negative shrinks (e.g. -0.005 = -0.5%/yr to slow down with age)."
+              >
+                <input
+                  type="number"
+                  value={form.annual_real_adjust_pct ?? '0'}
+                  step="0.001"
+                  min={-0.1}
+                  max={0.1}
+                  onChange={(e) =>
+                    update('annual_real_adjust_pct', e.target.value)
+                  }
+                  className="w-full rounded-md border border-slate-300 bg-white px-3 py-2 text-sm tabular-nums focus:outline-none focus:ring-2 focus:ring-slate-400"
+                />
+              </Field>
+              <Field
+                label="Guardrail trigger: cut spending if NW drops below"
+                hint="Fraction of starting NW that triggers a spending cut. e.g. 0.80 = cut once portfolio falls below 80% of seed. Leave blank to disable."
+              >
+                <input
+                  type="number"
+                  value={form.guardrail_threshold_pct ?? ''}
+                  step="0.05"
+                  min={0}
+                  max={1}
+                  placeholder="(off)"
+                  onChange={(e) =>
+                    update(
+                      'guardrail_threshold_pct',
+                      e.target.value === '' ? null : e.target.value,
+                    )
+                  }
+                  className="w-full rounded-md border border-slate-300 bg-white px-3 py-2 text-sm tabular-nums focus:outline-none focus:ring-2 focus:ring-slate-400"
+                />
+              </Field>
+              <Field
+                label="Guardrail cut size (when triggered)"
+                hint="Fraction by which to cut last year's withdrawal each triggered year. e.g. 0.10 = -10%."
+              >
+                <input
+                  type="number"
+                  value={form.guardrail_cut_pct ?? '0.10'}
+                  step="0.05"
+                  min={0}
+                  max={1}
+                  onChange={(e) => update('guardrail_cut_pct', e.target.value)}
+                  className="w-full rounded-md border border-slate-300 bg-white px-3 py-2 text-sm tabular-nums focus:outline-none focus:ring-2 focus:ring-slate-400"
+                />
+              </Field>
+            </>
+          )}
           <Field
             label="Returns model"
             hint={RETURNS_MODE_NOTES[form.returns_mode ?? 'shiller']}
@@ -328,6 +393,7 @@ function AboutTheModel() {
           <Term name="Guyton-Klinger guardrails">{STRATEGY_NOTES.guyton_klinger}</Term>
           <Term name="VPW">{STRATEGY_NOTES.vpw}</Term>
           <Term name="VPW + floor">{STRATEGY_NOTES.vpw_floor}</Term>
+          <Term name="Custom spending plan">{STRATEGY_NOTES.custom}</Term>
         </Section>
         <Section title="Glide paths (stock/bond mix over time)">
           <Term name="Rising equity">{GLIDE_NOTES.rising}</Term>

tests/test_spending_plan.py

@@ -0,0 +1,87 @@
+"""SpendingPlanStrategy: user-customisable initial spend + annual adjust + guardrail."""
+from fire_planner.strategies.base import StrategyState
+from fire_planner.strategies.spending_plan import SpendingPlanStrategy
+
+
+def state(**overrides: float | int) -> StrategyState:
+    base = dict(
+        portfolio=1_000_000.0,
+        initial_portfolio=1_000_000.0,
+        initial_withdrawal=40_000.0,
+        year_idx=0,
+        horizon_years=60,
+        last_withdrawal=40_000.0,
+        expected_real_return=0.04,
+    )
+    base.update(overrides)
+    return StrategyState(**base)  # type: ignore[arg-type]
+
+
+def test_year_zero_takes_initial_withdrawal() -> None:
+    s = SpendingPlanStrategy()
+    assert s.propose_withdrawal(state()) == 40_000.0
+
+
+def test_year_zero_explicit_override() -> None:
+    s = SpendingPlanStrategy(initial_spend=72_000.0)
+    assert s.propose_withdrawal(state()) == 72_000.0
+
+
+def test_constant_real_with_zero_adjust() -> None:
+    s = SpendingPlanStrategy(annual_real_adjust_pct=0.0)
+    assert s.propose_withdrawal(state(year_idx=10, last_withdrawal=40_000.0)) == 40_000.0
+
+
+def test_positive_annual_adjust_grows_spending() -> None:
+    """+2% real adjust → year 5 spend is last_w × 1.02 (one step from year 4)."""
+    s = SpendingPlanStrategy(annual_real_adjust_pct=0.02)
+    out = s.propose_withdrawal(state(year_idx=5, last_withdrawal=40_000.0))
+    assert abs(out - 40_800.0) < 1e-6
+
+
+def test_negative_annual_adjust_shrinks_spending() -> None:
+    s = SpendingPlanStrategy(annual_real_adjust_pct=-0.005)
+    out = s.propose_withdrawal(state(year_idx=10, last_withdrawal=40_000.0))
+    assert abs(out - 39_800.0) < 1e-6
+
+
+def test_guardrail_not_triggered_when_portfolio_above_threshold() -> None:
+    s = SpendingPlanStrategy(guardrail_threshold_pct=0.80, guardrail_cut_pct=0.10)
+    # portfolio at 90% of starting → above threshold → no cut
+    out = s.propose_withdrawal(state(year_idx=3, portfolio=900_000.0,
+                                     last_withdrawal=40_000.0))
+    assert out == 40_000.0
+
+
+def test_guardrail_triggered_cuts_by_pct() -> None:
+    s = SpendingPlanStrategy(guardrail_threshold_pct=0.80, guardrail_cut_pct=0.10)
+    # portfolio at 70% of starting → below threshold → 10% cut
+    out = s.propose_withdrawal(state(year_idx=3, portfolio=700_000.0,
+                                     last_withdrawal=40_000.0))
+    assert abs(out - 36_000.0) < 1e-6
+
+
+def test_guardrail_combines_with_annual_adjust() -> None:
+    """Adjust applies first, then cut — both fire."""
+    s = SpendingPlanStrategy(
+        annual_real_adjust_pct=0.02,
+        guardrail_threshold_pct=0.80,
+        guardrail_cut_pct=0.10,
+    )
+    out = s.propose_withdrawal(state(year_idx=3, portfolio=700_000.0,
+                                     last_withdrawal=40_000.0))
+    # 40_000 * 1.02 = 40_800; trigger; 40_800 * 0.90 = 36_720
+    assert abs(out - 36_720.0) < 1e-6
+
+
+def test_guardrail_disabled_when_threshold_none() -> None:
+    s = SpendingPlanStrategy(guardrail_threshold_pct=None)
+    out = s.propose_withdrawal(state(year_idx=3, portfolio=10_000.0,
+                                     last_withdrawal=40_000.0))
+    assert out == 40_000.0  # no cut despite tiny portfolio
+
+
+def test_returns_zero_when_portfolio_drained() -> None:
+    s = SpendingPlanStrategy()
+    out = s.propose_withdrawal(state(year_idx=5, portfolio=0.0, last_withdrawal=40_000.0))
+    assert out == 0.0

tests/test_strategies.py

@@ -36,17 +36,30 @@ def test_trinity_doesnt_increase_with_portfolio_growth() -> None:
                                       last_withdrawal=40_000.0)) == 40_000.0
 
 
-def test_gk_year_zero_uses_initial_rate() -> None:
+def test_gk_year_zero_uses_initial_withdrawal() -> None:
+    """Year-0 honours the user's target spending (state.initial_withdrawal),
+    not the strategy's preset rate. The preset rate now only matters as a
+    fallback when initial_withdrawal isn't set."""
     s = GuytonKlingerStrategy(initial_rate=0.055)
-    # 5.5% of 1M = 55,000
+    # state default has initial_withdrawal=40_000 → year 0 returns 40_000.
-    assert s.propose_withdrawal(state()) == 55_000.0
+    assert s.propose_withdrawal(state()) == 40_000.0
+
+
+def test_gk_year_zero_falls_back_to_preset_when_no_target() -> None:
+    s = GuytonKlingerStrategy(initial_rate=0.055)
+    # Override initial_withdrawal=0 → fall back to 5.5% × 1M = 55_000.
+    assert s.propose_withdrawal(state(initial_withdrawal=0)) == 55_000.0
 
 
 def test_gk_capital_preservation_cut() -> None:
-    """Portfolio crashed: current rate now > 120% of 5.5% = 6.6%; > 15y left → cut 10%."""
+    """Portfolio crashed: current rate now > 120% of the implied initial rate (5.5%);
+    > 15y left → cut 10%. Implied rate = initial_withdrawal / initial_portfolio."""
     s = GuytonKlingerStrategy(initial_rate=0.055)
-    # last_w = 55,000; portfolio = 700,000 → rate = 7.86% > 6.6%
+    # initial_withdrawal=55k, initial_portfolio=1M → implied rate = 5.5%.
-    out = s.propose_withdrawal(state(year_idx=5, portfolio=700_000.0, last_withdrawal=55_000.0))
+    # last_w = 55k; portfolio = 700k → current rate = 7.86% > 6.6% guardrail.
+    out = s.propose_withdrawal(state(year_idx=5, portfolio=700_000.0,
+                                     last_withdrawal=55_000.0,
+                                     initial_withdrawal=55_000.0))
     assert abs(out - 49_500.0) < 0.01