feat(calibration): complete step 1 data inspection with data quality v1

src/shared/schemas/api.py

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+# src/shared/schemas/api.py
+from pydantic import BaseModel
+from typing import Optional
+
+class BotStatus(BaseModel):
+    state: str                  # INIT/RUNNING/ERROR (derivado)
+    heartbeat_ts: Optional[str] = None
+    last_ts: Optional[str] = None

src/shared/schemas/broker.py

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+# src/shared/schemas/broker.py
+from pydantic import BaseModel
+from typing import Dict, Any, Optional
+
+class Position(BaseModel):
+    symbol: str
+    position_id: str
+    qty: float
+    avg_entry: float
+
+class BrokerSnapshot(BaseModel):
+    initial_cash: float
+    cash: float
+    commission_rate: float
+    slippage_rate: float
+    realized_pnl: float
+    equity: float
+    positions: Dict[str, Position]
+    last_price: Dict[str, float]
+    trades_count: int
+    updated_at: str

src/shared/schemas/loop.py

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+# src/shared/schemas/loop.py
+from pydantic import BaseModel
+from typing import List, Optional
+
+class LoopState(BaseModel):
+    last_ts: Optional[str] = None
+    equity_curve: List[float] = []
+    equity_timestamps: List[str] = []

src/shared/schemas/metrics.py

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+# src/shared/schemas/metrics.py
+from pydantic import BaseModel
+
+class EquityMetrics(BaseModel):
+    cagr: float
+    max_drawdown: float
+    calmar_ratio: float
+    volatility: float
+    time_in_drawdown: float
+    ulcer_index: float

src/shared/schemas/trades.py

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+# src/shared/schemas/trades.py
+from pydantic import BaseModel
+from typing import Dict, Any
+
+class TradeRow(BaseModel):
+    symbol: str
+    side: str
+    qty: float
+    price: float
+    fee: float
+    notional: float
+    realized_pnl: float
+    timestamp: str
+    meta: Dict[str, Any]