refactor: Tilgungsplan-Helfer schedule_for, Kredit-Laufzeit 1–1200 Monate (A14-T5)

- Neuer schedule_for() in app/engine/loans.py: vereinheitlicht Tilgungsplan-Erstellung
- Laufzeit-Validierung in LoanIn und LoanPatch: 1–1200 Monate
- Aufrufstellen aktualisiert (routers/planning.py, services/breakdown.py,
  services/projection_service.py, services/planning_chart.py)
- Keine direkten loan_schedule(Decimal(...)) Aufrufe außerhalb engine/loans.py mehr
- Tests für schedule_for und Laufzeit-Grenzen (1, 1200, sowie 0/-5/1201 Ablehnung)

Co-Authored-By: Claude Haiku 4.5 <noreply@anthropic.com>

finance/app/services/breakdown.py

@@ -5,14 +5,13 @@ Modifikatoren) - dieselbe Datenbasis wie load_scenario_inputs(None).
 """
 from dataclasses import dataclass
 from datetime import date
-from decimal import Decimal
 
 from sqlalchemy import select
 from sqlalchemy.orm import Session
 
 from app.engine.breakdown import (BreakdownRow, Filters, PlainLoan, Summary,
                                   breakdown_rows, summarize)
-from app.engine.loans import loan_schedule
+from app.engine.loans import schedule_for
 from app.models.tables import Category, Scenario
 from app.reserved import SYSTEM_PREFIX
 from app.services.double_count import Konflikt, all_conflicts
@@ -34,10 +33,7 @@ def compute_breakdown(session: Session, month: date, scenario: Scenario | None,
                       filters: Filters) -> Breakdown:
     inputs = load_scenario_inputs(session, scenario)
     names = {c.id: c.name for c in session.execute(select(Category)).scalars()}
-    loans = [PlainLoan(l.id, l.name,
-                       loan_schedule(Decimal(l.principal), Decimal(l.annual_rate_pct),
-                                     l.term_months, l.payout_date, l.repayment_type))
-             for l in inputs.loans]
+    loans = [PlainLoan(l.id, l.name, schedule_for(l)) for l in inputs.loans]
     rows = breakdown_rows(month, inputs.recurring, inputs.planned, loans,
                           inputs.modifiers, filters, category_names=names,
                           loan_category=KREDITRATEN, uncategorized=UNKATEGORISIERT)