feat: include current holdings in pre-market AI prompt (#170)

- Add current_holdings parameter to generate_playbook() and _build_prompt()
- Inject '## Current Holdings' section into Gemini prompt with qty, entry
  price, unrealized PnL%, and holding days for each held position
- Instruct AI to generate SELL/HOLD scenarios for held stocks even if not
  in scanner candidates list
- Allow held stock codes in _parse_response() valid_codes set so AI-
  generated SELL scenarios for holdings pass validation
- Add 6 tests covering prompt inclusion, omission, and response parsing

Closes #170

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>

src/db.py

@@ -237,28 +237,6 @@ def get_open_position(
     return {"decision_id": row[1], "price": row[2], "quantity": row[3]}
 
 
-def get_open_positions_by_market(
-    conn: sqlite3.Connection, market: str
-) -> list[str]:
-    """Return stock codes with a net positive position in the given market.
-
-    Uses net BUY - SELL quantity aggregation to avoid false positives from
-    the simpler "latest record is BUY" heuristic.  A stock is considered
-    open only when the bot's own recorded trades leave a positive net quantity.
-    """
-    cursor = conn.execute(
-        """
-        SELECT stock_code
-        FROM trades
-        WHERE market = ?
-        GROUP BY stock_code
-        HAVING SUM(CASE WHEN action = 'BUY' THEN quantity ELSE -quantity END) > 0
-        """,
-        (market,),
-    )
-    return [row[0] for row in cursor.fetchall()]
-
-
 def get_recent_symbols(
     conn: sqlite3.Connection, market: str, limit: int = 30
 ) -> list[str]:

src/main.py

@@ -32,7 +32,6 @@ from src.core.risk_manager import CircuitBreakerTripped, FatFingerRejected, Risk
 from src.db import (
     get_latest_buy_trade,
     get_open_position,
-    get_open_positions_by_market,
     get_recent_symbols,
     init_db,
     log_trade,
@@ -107,6 +106,82 @@ def _extract_symbol_from_holding(item: dict[str, Any]) -> str:
     return ""
 
 
+def _extract_held_codes_from_balance(
+    balance_data: dict[str, Any],
+    *,
+    is_domestic: bool,
+) -> list[str]:
+    """Return stock codes with a positive orderable quantity from a balance response.
+
+    Uses the broker's live output1 as the source of truth so that partial fills
+    and manual external trades are always reflected correctly.
+    """
+    output1 = balance_data.get("output1", [])
+    if isinstance(output1, dict):
+        output1 = [output1]
+    if not isinstance(output1, list):
+        return []
+
+    codes: list[str] = []
+    for holding in output1:
+        if not isinstance(holding, dict):
+            continue
+        code_key = "pdno" if is_domestic else "ovrs_pdno"
+        code = str(holding.get(code_key, "")).strip().upper()
+        if not code:
+            continue
+        if is_domestic:
+            qty = int(holding.get("ord_psbl_qty") or holding.get("hldg_qty") or 0)
+        else:
+            qty = int(holding.get("ovrs_cblc_qty") or holding.get("hldg_qty") or 0)
+        if qty > 0:
+            codes.append(code)
+    return codes
+
+
+def _extract_held_qty_from_balance(
+    balance_data: dict[str, Any],
+    stock_code: str,
+    *,
+    is_domestic: bool,
+) -> int:
+    """Extract the broker-confirmed orderable quantity for a stock.
+
+    Uses the broker's live balance response (output1) as the source of truth
+    rather than the local DB, because DB records reflect order quantity which
+    may differ from actual fill quantity due to partial fills.
+
+    Domestic fields (VTTC8434R output1):
+        pdno          — 종목코드
+        ord_psbl_qty  — 주문가능수량 (preferred: excludes unsettled)
+        hldg_qty      — 보유수량 (fallback)
+
+    Overseas fields (output1):
+        ovrs_pdno     — 종목코드
+        ovrs_cblc_qty — 해외잔고수량 (preferred)
+        hldg_qty      — 보유수량 (fallback)
+    """
+    output1 = balance_data.get("output1", [])
+    if isinstance(output1, dict):
+        output1 = [output1]
+    if not isinstance(output1, list):
+        return 0
+
+    for holding in output1:
+        if not isinstance(holding, dict):
+            continue
+        code_key = "pdno" if is_domestic else "ovrs_pdno"
+        held_code = str(holding.get(code_key, "")).strip().upper()
+        if held_code != stock_code.strip().upper():
+            continue
+        if is_domestic:
+            qty = int(holding.get("ord_psbl_qty") or holding.get("hldg_qty") or 0)
+        else:
+            qty = int(holding.get("ovrs_cblc_qty") or holding.get("hldg_qty") or 0)
+        return qty
+    return 0
+
+
 def _determine_order_quantity(
     *,
     action: str,
@@ -114,10 +189,11 @@ def _determine_order_quantity(
     total_cash: float,
     candidate: ScanCandidate | None,
     settings: Settings | None,
+    broker_held_qty: int = 0,
 ) -> int:
     """Determine order quantity using volatility-aware position sizing."""
-    if action != "BUY":
-        return 1
+    if action == "SELL":
+        return broker_held_qty
     if current_price <= 0 or total_cash <= 0:
         return 0
 
@@ -388,8 +464,10 @@ async def trading_cycle(
             if entry_price > 0:
                 loss_pct = (current_price - entry_price) / entry_price * 100
                 stop_loss_threshold = -2.0
+                take_profit_threshold = 3.0
                 if stock_playbook and stock_playbook.scenarios:
                     stop_loss_threshold = stock_playbook.scenarios[0].stop_loss_pct
+                    take_profit_threshold = stock_playbook.scenarios[0].take_profit_pct
 
                 if loss_pct <= stop_loss_threshold:
                     decision = TradeDecision(
@@ -407,6 +485,22 @@ async def trading_cycle(
                         loss_pct,
                         stop_loss_threshold,
                     )
+                elif loss_pct >= take_profit_threshold:
+                    decision = TradeDecision(
+                        action="SELL",
+                        confidence=90,
+                        rationale=(
+                            f"Take-profit triggered ({loss_pct:.2f}% >= "
+                            f"{take_profit_threshold:.2f}%)"
+                        ),
+                    )
+                    logger.info(
+                        "Take-profit override for %s (%s): %.2f%% >= %.2f%%",
+                        stock_code,
+                        market.name,
+                        loss_pct,
+                        take_profit_threshold,
+                    )
     logger.info(
         "Decision for %s (%s): %s (confidence=%d)",
         stock_code,
@@ -467,12 +561,20 @@ async def trading_cycle(
     trade_price = current_price
     trade_pnl = 0.0
     if decision.action in ("BUY", "SELL"):
+        broker_held_qty = (
+            _extract_held_qty_from_balance(
+                balance_data, stock_code, is_domestic=market.is_domestic
+            )
+            if decision.action == "SELL"
+            else 0
+        )
         quantity = _determine_order_quantity(
             action=decision.action,
             current_price=current_price,
             total_cash=total_cash,
             candidate=candidate,
             settings=settings,
+            broker_held_qty=broker_held_qty,
         )
         if quantity <= 0:
             logger.info(
@@ -892,12 +994,20 @@ async def run_daily_session(
             trade_pnl = 0.0
             order_succeeded = True
             if decision.action in ("BUY", "SELL"):
+                daily_broker_held_qty = (
+                    _extract_held_qty_from_balance(
+                        balance_data, stock_code, is_domestic=market.is_domestic
+                    )
+                    if decision.action == "SELL"
+                    else 0
+                )
                 quantity = _determine_order_quantity(
                     action=decision.action,
                     current_price=stock_data["current_price"],
                     total_cash=total_cash,
                     candidate=candidate_map.get(stock_code),
                     settings=settings,
+                    broker_held_qty=daily_broker_held_qty,
                 )
                 if quantity <= 0:
                     logger.info(
@@ -1864,22 +1974,38 @@ async def run(settings: Settings) -> None:
                         except Exception as exc:
                             logger.error("Smart Scanner failed for %s: %s", market.name, exc)
 
-                    # Get active stocks from scanner (dynamic, no static fallback)
-                    # Also include current holdings so stop-loss / take-profit
-                    # can trigger even when a position drops off the scanner.
+                    # Get active stocks from scanner (dynamic, no static fallback).
+                    # Also include currently-held positions so stop-loss /
+                    # take-profit can fire even when a holding drops off the
+                    # scanner.  Broker balance is the source of truth here —
+                    # unlike the local DB it reflects actual fills and any
+                    # manual trades done outside the bot.
                     scanner_codes = active_stocks.get(market.code, [])
-                    held_codes = get_open_positions_by_market(db_conn, market.code)
-                    # Union: scanner candidates first, then holdings not already present.
-                    # dict.fromkeys preserves insertion order and removes duplicates.
-                    stock_codes = list(dict.fromkeys(scanner_codes + held_codes))
-                    if held_codes:
-                        new_held = [c for c in held_codes if c not in set(scanner_codes)]
-                        if new_held:
-                            logger.info(
-                                "Holdings added to loop for %s (not in scanner): %s",
-                                market.name,
-                                new_held,
+                    try:
+                        if market.is_domestic:
+                            held_balance = await broker.get_balance()
+                        else:
+                            held_balance = await overseas_broker.get_overseas_balance(
+                                market.exchange_code
                             )
+                        held_codes = _extract_held_codes_from_balance(
+                            held_balance, is_domestic=market.is_domestic
+                        )
+                    except Exception as exc:
+                        logger.warning(
+                            "Failed to fetch holdings for %s: %s — skipping holdings merge",
+                            market.name, exc,
+                        )
+                        held_codes = []
+
+                    stock_codes = list(dict.fromkeys(scanner_codes + held_codes))
+                    extra_held = [c for c in held_codes if c not in set(scanner_codes)]
+                    if extra_held:
+                        logger.info(
+                            "Holdings added to loop for %s (not in scanner): %s",
+                            market.name, extra_held,
+                        )
+
                     if not stock_codes:
                         logger.debug("No active stocks for market %s", market.code)
                         continue

src/strategy/pre_market_planner.py

@@ -75,6 +75,7 @@ class PreMarketPlanner:
         market: str,
         candidates: list[ScanCandidate],
         today: date | None = None,
+        current_holdings: list[dict] | None = None,
     ) -> DayPlaybook:
         """Generate a DayPlaybook for a market using Gemini.
 
@@ -82,6 +83,10 @@ class PreMarketPlanner:
             market: Market code ("KR" or "US")
             candidates: Stock candidates from SmartVolatilityScanner
             today: Override date (defaults to date.today()). Use market-local date.
+            current_holdings: Currently held positions with entry_price and unrealized_pnl_pct.
+                Each dict: {"stock_code": str, "name": str, "qty": int,
+                            "entry_price": float, "unrealized_pnl_pct": float,
+                            "holding_days": int}
 
         Returns:
             DayPlaybook with scenarios. Empty/defensive if no candidates or failure.
@@ -106,6 +111,7 @@ class PreMarketPlanner:
                 context_data,
                 self_market_scorecard,
                 cross_market,
+                current_holdings=current_holdings,
             )
 
             # 3. Call Gemini
@@ -118,7 +124,8 @@ class PreMarketPlanner:
 
             # 4. Parse response
             playbook = self._parse_response(
-                decision.rationale, today, market, candidates, cross_market
+                decision.rationale, today, market, candidates, cross_market,
+                current_holdings=current_holdings,
             )
             playbook_with_tokens = playbook.model_copy(
                 update={"token_count": decision.token_count}
@@ -230,6 +237,7 @@ class PreMarketPlanner:
         context_data: dict[str, Any],
         self_market_scorecard: dict[str, Any] | None,
         cross_market: CrossMarketContext | None,
+        current_holdings: list[dict] | None = None,
     ) -> str:
         """Build a structured prompt for Gemini to generate scenario JSON."""
         max_scenarios = self._settings.MAX_SCENARIOS_PER_STOCK
@@ -241,6 +249,26 @@ class PreMarketPlanner:
             for c in candidates
         )
 
+        holdings_text = ""
+        if current_holdings:
+            lines = []
+            for h in current_holdings:
+                code = h.get("stock_code", "")
+                name = h.get("name", "")
+                qty = h.get("qty", 0)
+                entry_price = h.get("entry_price", 0.0)
+                pnl_pct = h.get("unrealized_pnl_pct", 0.0)
+                holding_days = h.get("holding_days", 0)
+                lines.append(
+                    f"  - {code} ({name}): {qty}주 @ {entry_price:,.0f}, "
+                    f"미실현손익 {pnl_pct:+.2f}%, 보유 {holding_days}일"
+                )
+            holdings_text = (
+                "\n## Current Holdings (보유 중 — SELL/HOLD 전략 고려 필요)\n"
+                + "\n".join(lines)
+                + "\n"
+            )
+
         cross_market_text = ""
         if cross_market:
             cross_market_text = (
@@ -273,10 +301,20 @@ class PreMarketPlanner:
                     for key, value in list(layer_data.items())[:5]:
                         context_text += f"  - {key}: {value}\n"
 
+        holdings_instruction = ""
+        if current_holdings:
+            holding_codes = [h.get("stock_code", "") for h in current_holdings]
+            holdings_instruction = (
+                f"- Also include SELL/HOLD scenarios for held stocks: "
+                f"{', '.join(holding_codes)} "
+                f"(even if not in candidates list)\n"
+            )
+
         return (
             f"You are a pre-market trading strategist for the {market} market.\n"
             f"Generate structured trading scenarios for today.\n\n"
             f"## Candidates (from volatility scanner)\n{candidates_text}\n"
+            f"{holdings_text}"
             f"{self_market_text}"
             f"{cross_market_text}"
             f"{context_text}\n"
@@ -308,7 +346,8 @@ class PreMarketPlanner:
             f'}}\n\n'
             f"Rules:\n"
             f"- Max {max_scenarios} scenarios per stock\n"
-            f"- Only use stocks from the candidates list\n"
+            f"- Candidates list is the primary source for BUY candidates\n"
+            f"{holdings_instruction}"
             f"- Confidence 0-100 (80+ for actionable trades)\n"
             f"- stop_loss_pct must be <= 0, take_profit_pct must be >= 0\n"
             f"- Return ONLY the JSON, no markdown fences or explanation\n"
@@ -321,12 +360,19 @@ class PreMarketPlanner:
         market: str,
         candidates: list[ScanCandidate],
         cross_market: CrossMarketContext | None,
+        current_holdings: list[dict] | None = None,
     ) -> DayPlaybook:
         """Parse Gemini's JSON response into a validated DayPlaybook."""
         cleaned = self._extract_json(response_text)
         data = json.loads(cleaned)
 
         valid_codes = {c.stock_code for c in candidates}
+        # Holdings are also valid — AI may generate SELL/HOLD scenarios for them
+        if current_holdings:
+            for h in current_holdings:
+                code = h.get("stock_code", "")
+                if code:
+                    valid_codes.add(code)
 
         # Parse market outlook
         outlook_str = data.get("market_outlook", "neutral")

tests/test_db.py

@@ -1,6 +1,6 @@
 """Tests for database helper functions."""
 
-from src.db import get_open_position, get_open_positions_by_market, init_db, log_trade
+from src.db import get_open_position, init_db, log_trade
 
 
 def test_get_open_position_returns_latest_buy() -> None:
@@ -58,87 +58,3 @@ def test_get_open_position_returns_none_when_latest_is_sell() -> None:
 def test_get_open_position_returns_none_when_no_trades() -> None:
     conn = init_db(":memory:")
     assert get_open_position(conn, "AAPL", "US_NASDAQ") is None
-
-
-# --- get_open_positions_by_market tests ---
-
-
-def test_get_open_positions_by_market_returns_net_positive_stocks() -> None:
-    """Stocks with net BUY quantity > 0 are included."""
-    conn = init_db(":memory:")
-    log_trade(
-        conn=conn, stock_code="005930", action="BUY", confidence=90,
-        rationale="entry", quantity=5, price=70000.0, market="KR",
-        exchange_code="KRX", decision_id="d1",
-    )
-    log_trade(
-        conn=conn, stock_code="000660", action="BUY", confidence=85,
-        rationale="entry", quantity=3, price=100000.0, market="KR",
-        exchange_code="KRX", decision_id="d2",
-    )
-
-    result = get_open_positions_by_market(conn, "KR")
-    assert set(result) == {"005930", "000660"}
-
-
-def test_get_open_positions_by_market_excludes_fully_sold_stocks() -> None:
-    """Stocks where BUY qty == SELL qty are excluded (net qty = 0)."""
-    conn = init_db(":memory:")
-    log_trade(
-        conn=conn, stock_code="005930", action="BUY", confidence=90,
-        rationale="entry", quantity=3, price=70000.0, market="KR",
-        exchange_code="KRX", decision_id="d1",
-    )
-    log_trade(
-        conn=conn, stock_code="005930", action="SELL", confidence=95,
-        rationale="exit", quantity=3, price=71000.0, market="KR",
-        exchange_code="KRX", decision_id="d2",
-    )
-
-    result = get_open_positions_by_market(conn, "KR")
-    assert "005930" not in result
-
-
-def test_get_open_positions_by_market_includes_partially_sold_stocks() -> None:
-    """Stocks with partial SELL (net qty > 0) are still included."""
-    conn = init_db(":memory:")
-    log_trade(
-        conn=conn, stock_code="005930", action="BUY", confidence=90,
-        rationale="entry", quantity=5, price=70000.0, market="KR",
-        exchange_code="KRX", decision_id="d1",
-    )
-    log_trade(
-        conn=conn, stock_code="005930", action="SELL", confidence=95,
-        rationale="partial exit", quantity=2, price=71000.0, market="KR",
-        exchange_code="KRX", decision_id="d2",
-    )
-
-    result = get_open_positions_by_market(conn, "KR")
-    assert "005930" in result
-
-
-def test_get_open_positions_by_market_is_market_scoped() -> None:
-    """Only stocks from the specified market are returned."""
-    conn = init_db(":memory:")
-    log_trade(
-        conn=conn, stock_code="005930", action="BUY", confidence=90,
-        rationale="entry", quantity=3, price=70000.0, market="KR",
-        exchange_code="KRX", decision_id="d1",
-    )
-    log_trade(
-        conn=conn, stock_code="AAPL", action="BUY", confidence=85,
-        rationale="entry", quantity=2, price=200.0, market="NASD",
-        exchange_code="NAS", decision_id="d2",
-    )
-
-    kr_result = get_open_positions_by_market(conn, "KR")
-    nasd_result = get_open_positions_by_market(conn, "NASD")
-
-    assert kr_result == ["005930"]
-    assert nasd_result == ["AAPL"]
-
-
-def test_get_open_positions_by_market_returns_empty_when_no_trades() -> None:
-    """Empty list returned when no trades exist for the market."""
-    conn = init_db(":memory:")
-    assert get_open_positions_by_market(conn, "KR") == []

tests/test_main.py

@@ -14,6 +14,9 @@ from src.evolution.scorecard import DailyScorecard
 from src.logging.decision_logger import DecisionLogger
 from src.main import (
     _apply_dashboard_flag,
+    _determine_order_quantity,
+    _extract_held_codes_from_balance,
+    _extract_held_qty_from_balance,
     _handle_market_close,
     _run_context_scheduler,
     _run_evolution_loop,
@@ -68,6 +71,141 @@ def _make_sell_match(stock_code: str = "005930") -> ScenarioMatch:
     )
 
 
+class TestExtractHeldQtyFromBalance:
+    """Tests for _extract_held_qty_from_balance()."""
+
+    def _domestic_balance(self, stock_code: str, ord_psbl_qty: int) -> dict:
+        return {
+            "output1": [{"pdno": stock_code, "ord_psbl_qty": str(ord_psbl_qty)}],
+            "output2": [{"dnca_tot_amt": "1000000"}],
+        }
+
+    def test_domestic_returns_ord_psbl_qty(self) -> None:
+        balance = self._domestic_balance("005930", 7)
+        assert _extract_held_qty_from_balance(balance, "005930", is_domestic=True) == 7
+
+    def test_domestic_fallback_to_hldg_qty(self) -> None:
+        balance = {"output1": [{"pdno": "005930", "hldg_qty": "3"}]}
+        assert _extract_held_qty_from_balance(balance, "005930", is_domestic=True) == 3
+
+    def test_domestic_returns_zero_when_not_found(self) -> None:
+        balance = self._domestic_balance("005930", 5)
+        assert _extract_held_qty_from_balance(balance, "000660", is_domestic=True) == 0
+
+    def test_domestic_returns_zero_when_output1_empty(self) -> None:
+        balance = {"output1": [], "output2": [{}]}
+        assert _extract_held_qty_from_balance(balance, "005930", is_domestic=True) == 0
+
+    def test_overseas_returns_ovrs_cblc_qty(self) -> None:
+        balance = {"output1": [{"ovrs_pdno": "AAPL", "ovrs_cblc_qty": "10"}]}
+        assert _extract_held_qty_from_balance(balance, "AAPL", is_domestic=False) == 10
+
+    def test_overseas_fallback_to_hldg_qty(self) -> None:
+        balance = {"output1": [{"ovrs_pdno": "AAPL", "hldg_qty": "4"}]}
+        assert _extract_held_qty_from_balance(balance, "AAPL", is_domestic=False) == 4
+
+    def test_case_insensitive_match(self) -> None:
+        balance = {"output1": [{"pdno": "005930", "ord_psbl_qty": "2"}]}
+        assert _extract_held_qty_from_balance(balance, "005930", is_domestic=True) == 2
+
+
+class TestExtractHeldCodesFromBalance:
+    """Tests for _extract_held_codes_from_balance()."""
+
+    def test_returns_codes_with_positive_qty(self) -> None:
+        balance = {
+            "output1": [
+                {"pdno": "005930", "ord_psbl_qty": "5"},
+                {"pdno": "000660", "ord_psbl_qty": "3"},
+            ]
+        }
+        result = _extract_held_codes_from_balance(balance, is_domestic=True)
+        assert set(result) == {"005930", "000660"}
+
+    def test_excludes_zero_qty_holdings(self) -> None:
+        balance = {
+            "output1": [
+                {"pdno": "005930", "ord_psbl_qty": "0"},
+                {"pdno": "000660", "ord_psbl_qty": "2"},
+            ]
+        }
+        result = _extract_held_codes_from_balance(balance, is_domestic=True)
+        assert "005930" not in result
+        assert "000660" in result
+
+    def test_returns_empty_when_output1_missing(self) -> None:
+        balance: dict = {}
+        assert _extract_held_codes_from_balance(balance, is_domestic=True) == []
+
+    def test_overseas_uses_ovrs_pdno(self) -> None:
+        balance = {"output1": [{"ovrs_pdno": "AAPL", "ovrs_cblc_qty": "3"}]}
+        result = _extract_held_codes_from_balance(balance, is_domestic=False)
+        assert result == ["AAPL"]
+
+
+class TestDetermineOrderQuantity:
+    """Test _determine_order_quantity() — SELL uses broker_held_qty."""
+
+    def test_sell_returns_broker_held_qty(self) -> None:
+        result = _determine_order_quantity(
+            action="SELL",
+            current_price=105.0,
+            total_cash=50000.0,
+            candidate=None,
+            settings=None,
+            broker_held_qty=7,
+        )
+        assert result == 7
+
+    def test_sell_returns_zero_when_broker_qty_zero(self) -> None:
+        result = _determine_order_quantity(
+            action="SELL",
+            current_price=105.0,
+            total_cash=50000.0,
+            candidate=None,
+            settings=None,
+            broker_held_qty=0,
+        )
+        assert result == 0
+
+    def test_buy_without_position_sizing_returns_one(self) -> None:
+        result = _determine_order_quantity(
+            action="BUY",
+            current_price=50000.0,
+            total_cash=1000000.0,
+            candidate=None,
+            settings=None,
+        )
+        assert result == 1
+
+    def test_buy_with_zero_cash_returns_zero(self) -> None:
+        result = _determine_order_quantity(
+            action="BUY",
+            current_price=50000.0,
+            total_cash=0.0,
+            candidate=None,
+            settings=None,
+        )
+        assert result == 0
+
+    def test_buy_with_position_sizing_calculates_correctly(self) -> None:
+        settings = MagicMock(spec=Settings)
+        settings.POSITION_SIZING_ENABLED = True
+        settings.POSITION_VOLATILITY_TARGET_SCORE = 50.0
+        settings.POSITION_BASE_ALLOCATION_PCT = 10.0
+        settings.POSITION_MAX_ALLOCATION_PCT = 30.0
+        settings.POSITION_MIN_ALLOCATION_PCT = 1.0
+        # 1,000,000 * 10% = 100,000 budget // 50,000 price = 2 shares
+        result = _determine_order_quantity(
+            action="BUY",
+            current_price=50000.0,
+            total_cash=1000000.0,
+            candidate=None,
+            settings=settings,
+        )
+        assert result == 2
+
+
 class TestSafeFloat:
     """Test safe_float() helper function."""
 
@@ -1240,13 +1378,14 @@ async def test_sell_updates_original_buy_decision_outcome() -> None:
     broker.get_current_price = AsyncMock(return_value=(120.0, 0.0, 0.0))
     broker.get_balance = AsyncMock(
         return_value={
+            "output1": [{"pdno": "005930", "ord_psbl_qty": "1"}],
             "output2": [
                 {
                     "tot_evlu_amt": "100000",
                     "dnca_tot_amt": "10000",
                     "pchs_amt_smtl_amt": "90000",
                 }
-            ]
+            ],
         }
     )
     broker.send_order = AsyncMock(return_value={"msg1": "OK"})
@@ -1330,13 +1469,14 @@ async def test_hold_overridden_to_sell_when_stop_loss_triggered() -> None:
     broker.get_current_price = AsyncMock(return_value=(95.0, -5.0, 0.0))
     broker.get_balance = AsyncMock(
         return_value={
+            "output1": [{"pdno": "005930", "ord_psbl_qty": "1"}],
             "output2": [
                 {
                     "tot_evlu_amt": "100000",
                     "dnca_tot_amt": "10000",
                     "pchs_amt_smtl_amt": "90000",
                 }
-            ]
+            ],
         }
     )
     broker.send_order = AsyncMock(return_value={"msg1": "OK"})
@@ -1396,6 +1536,318 @@ async def test_hold_overridden_to_sell_when_stop_loss_triggered() -> None:
     assert broker.send_order.call_args.kwargs["order_type"] == "SELL"
 
 
+@pytest.mark.asyncio
+async def test_hold_overridden_to_sell_when_take_profit_triggered() -> None:
+    """HOLD decision should be overridden to SELL when take-profit threshold is reached."""
+    db_conn = init_db(":memory:")
+    decision_logger = DecisionLogger(db_conn)
+
+    buy_decision_id = decision_logger.log_decision(
+        stock_code="005930",
+        market="KR",
+        exchange_code="KRX",
+        action="BUY",
+        confidence=90,
+        rationale="entry",
+        context_snapshot={},
+        input_data={},
+    )
+    log_trade(
+        conn=db_conn,
+        stock_code="005930",
+        action="BUY",
+        confidence=90,
+        rationale="entry",
+        quantity=1,
+        price=100.0,
+        market="KR",
+        exchange_code="KRX",
+        decision_id=buy_decision_id,
+    )
+
+    broker = MagicMock()
+    # Current price 106.0 → +6% gain, above take_profit_pct=3.0
+    broker.get_current_price = AsyncMock(return_value=(106.0, 6.0, 0.0))
+    broker.get_balance = AsyncMock(
+        return_value={
+            "output1": [{"pdno": "005930", "ord_psbl_qty": "1"}],
+            "output2": [
+                {
+                    "tot_evlu_amt": "100000",
+                    "dnca_tot_amt": "10000",
+                    "pchs_amt_smtl_amt": "90000",
+                }
+            ],
+        }
+    )
+    broker.send_order = AsyncMock(return_value={"msg1": "OK"})
+
+    scenario = StockScenario(
+        condition=StockCondition(rsi_below=30),
+        action=ScenarioAction.BUY,
+        confidence=88,
+        stop_loss_pct=-2.0,
+        take_profit_pct=3.0,
+        rationale="take profit policy",
+    )
+    playbook = DayPlaybook(
+        date=date(2026, 2, 8),
+        market="KR",
+        stock_playbooks=[
+            {"stock_code": "005930", "stock_name": "Samsung", "scenarios": [scenario]}
+        ],
+    )
+    engine = MagicMock(spec=ScenarioEngine)
+    engine.evaluate = MagicMock(return_value=_make_hold_match())
+
+    market = MagicMock()
+    market.name = "Korea"
+    market.code = "KR"
+    market.exchange_code = "KRX"
+    market.is_domestic = True
+
+    telegram = MagicMock()
+    telegram.notify_trade_execution = AsyncMock()
+    telegram.notify_fat_finger = AsyncMock()
+    telegram.notify_circuit_breaker = AsyncMock()
+    telegram.notify_scenario_matched = AsyncMock()
+
+    await trading_cycle(
+        broker=broker,
+        overseas_broker=MagicMock(),
+        scenario_engine=engine,
+        playbook=playbook,
+        risk=MagicMock(),
+        db_conn=db_conn,
+        decision_logger=decision_logger,
+        context_store=MagicMock(
+            get_latest_timeframe=MagicMock(return_value=None),
+            set_context=MagicMock(),
+        ),
+        criticality_assessor=MagicMock(
+            assess_market_conditions=MagicMock(return_value=MagicMock(value="NORMAL")),
+            get_timeout=MagicMock(return_value=5.0),
+        ),
+        telegram=telegram,
+        market=market,
+        stock_code="005930",
+        scan_candidates={},
+    )
+
+    broker.send_order.assert_called_once()
+    assert broker.send_order.call_args.kwargs["order_type"] == "SELL"
+
+
+@pytest.mark.asyncio
+async def test_hold_not_overridden_when_between_stop_loss_and_take_profit() -> None:
+    """HOLD should remain HOLD when P&L is within stop-loss and take-profit bounds."""
+    db_conn = init_db(":memory:")
+    decision_logger = DecisionLogger(db_conn)
+
+    buy_decision_id = decision_logger.log_decision(
+        stock_code="005930",
+        market="KR",
+        exchange_code="KRX",
+        action="BUY",
+        confidence=90,
+        rationale="entry",
+        context_snapshot={},
+        input_data={},
+    )
+    log_trade(
+        conn=db_conn,
+        stock_code="005930",
+        action="BUY",
+        confidence=90,
+        rationale="entry",
+        quantity=1,
+        price=100.0,
+        market="KR",
+        exchange_code="KRX",
+        decision_id=buy_decision_id,
+    )
+
+    broker = MagicMock()
+    # Current price 101.0 → +1% gain, within [-2%, +3%] range
+    broker.get_current_price = AsyncMock(return_value=(101.0, 1.0, 0.0))
+    broker.get_balance = AsyncMock(
+        return_value={
+            "output2": [
+                {
+                    "tot_evlu_amt": "100000",
+                    "dnca_tot_amt": "10000",
+                    "pchs_amt_smtl_amt": "90000",
+                }
+            ]
+        }
+    )
+    broker.send_order = AsyncMock(return_value={"msg1": "OK"})
+
+    scenario = StockScenario(
+        condition=StockCondition(rsi_below=30),
+        action=ScenarioAction.BUY,
+        confidence=88,
+        stop_loss_pct=-2.0,
+        take_profit_pct=3.0,
+        rationale="within range policy",
+    )
+    playbook = DayPlaybook(
+        date=date(2026, 2, 8),
+        market="KR",
+        stock_playbooks=[
+            {"stock_code": "005930", "stock_name": "Samsung", "scenarios": [scenario]}
+        ],
+    )
+    engine = MagicMock(spec=ScenarioEngine)
+    engine.evaluate = MagicMock(return_value=_make_hold_match())
+
+    market = MagicMock()
+    market.name = "Korea"
+    market.code = "KR"
+    market.exchange_code = "KRX"
+    market.is_domestic = True
+
+    telegram = MagicMock()
+    telegram.notify_trade_execution = AsyncMock()
+    telegram.notify_fat_finger = AsyncMock()
+    telegram.notify_circuit_breaker = AsyncMock()
+    telegram.notify_scenario_matched = AsyncMock()
+
+    await trading_cycle(
+        broker=broker,
+        overseas_broker=MagicMock(),
+        scenario_engine=engine,
+        playbook=playbook,
+        risk=MagicMock(),
+        db_conn=db_conn,
+        decision_logger=decision_logger,
+        context_store=MagicMock(
+            get_latest_timeframe=MagicMock(return_value=None),
+            set_context=MagicMock(),
+        ),
+        criticality_assessor=MagicMock(
+            assess_market_conditions=MagicMock(return_value=MagicMock(value="NORMAL")),
+            get_timeout=MagicMock(return_value=5.0),
+        ),
+        telegram=telegram,
+        market=market,
+        stock_code="005930",
+        scan_candidates={},
+    )
+
+    broker.send_order.assert_not_called()
+
+
+@pytest.mark.asyncio
+async def test_sell_order_uses_broker_balance_qty_not_db() -> None:
+    """SELL quantity must come from broker balance output1, not DB.
+
+    The DB records order quantity which may differ from actual fill quantity.
+    This test verifies that we use the broker-confirmed orderable quantity.
+    """
+    db_conn = init_db(":memory:")
+    decision_logger = DecisionLogger(db_conn)
+
+    buy_decision_id = decision_logger.log_decision(
+        stock_code="005930",
+        market="KR",
+        exchange_code="KRX",
+        action="BUY",
+        confidence=90,
+        rationale="entry",
+        context_snapshot={},
+        input_data={},
+    )
+    # DB records 10 shares ordered — but only 5 actually filled (partial fill scenario)
+    log_trade(
+        conn=db_conn,
+        stock_code="005930",
+        action="BUY",
+        confidence=90,
+        rationale="entry",
+        quantity=10,  # ordered quantity (may differ from fill)
+        price=100.0,
+        market="KR",
+        exchange_code="KRX",
+        decision_id=buy_decision_id,
+    )
+
+    broker = MagicMock()
+    # Stop-loss triggers (price dropped below -2%)
+    broker.get_current_price = AsyncMock(return_value=(95.0, -5.0, 0.0))
+    broker.get_balance = AsyncMock(
+        return_value={
+            # Broker confirms only 5 shares are actually orderable (partial fill)
+            "output1": [{"pdno": "005930", "ord_psbl_qty": "5"}],
+            "output2": [
+                {
+                    "tot_evlu_amt": "100000",
+                    "dnca_tot_amt": "10000",
+                    "pchs_amt_smtl_amt": "90000",
+                }
+            ],
+        }
+    )
+    broker.send_order = AsyncMock(return_value={"msg1": "OK"})
+
+    scenario = StockScenario(
+        condition=StockCondition(rsi_below=30),
+        action=ScenarioAction.BUY,
+        confidence=88,
+        stop_loss_pct=-2.0,
+        rationale="stop loss policy",
+    )
+    playbook = DayPlaybook(
+        date=date(2026, 2, 8),
+        market="KR",
+        stock_playbooks=[
+            {"stock_code": "005930", "stock_name": "Samsung", "scenarios": [scenario]}
+        ],
+    )
+    engine = MagicMock(spec=ScenarioEngine)
+    engine.evaluate = MagicMock(return_value=_make_hold_match())
+
+    market = MagicMock()
+    market.name = "Korea"
+    market.code = "KR"
+    market.exchange_code = "KRX"
+    market.is_domestic = True
+
+    telegram = MagicMock()
+    telegram.notify_trade_execution = AsyncMock()
+    telegram.notify_fat_finger = AsyncMock()
+    telegram.notify_circuit_breaker = AsyncMock()
+    telegram.notify_scenario_matched = AsyncMock()
+
+    await trading_cycle(
+        broker=broker,
+        overseas_broker=MagicMock(),
+        scenario_engine=engine,
+        playbook=playbook,
+        risk=MagicMock(),
+        db_conn=db_conn,
+        decision_logger=decision_logger,
+        context_store=MagicMock(
+            get_latest_timeframe=MagicMock(return_value=None),
+            set_context=MagicMock(),
+        ),
+        criticality_assessor=MagicMock(
+            assess_market_conditions=MagicMock(return_value=MagicMock(value="NORMAL")),
+            get_timeout=MagicMock(return_value=5.0),
+        ),
+        telegram=telegram,
+        market=market,
+        stock_code="005930",
+        scan_candidates={},
+    )
+
+    broker.send_order.assert_called_once()
+    call_kwargs = broker.send_order.call_args.kwargs
+    assert call_kwargs["order_type"] == "SELL"
+    # Must use broker-confirmed qty (5), NOT DB-recorded ordered qty (10)
+    assert call_kwargs["quantity"] == 5
+
+
 @pytest.mark.asyncio
 async def test_handle_market_close_runs_daily_review_flow() -> None:
     """Market close should aggregate, create scorecard, lessons, and notify."""

tests/test_pre_market_planner.py

@@ -830,3 +830,171 @@ class TestSmartFallbackPlaybook:
         ]
         assert len(buy_scenarios) == 1
         assert buy_scenarios[0].condition.volume_ratio_above == 2.0  # VOL_MULTIPLIER default
+
+
+# ---------------------------------------------------------------------------
+# Holdings in prompt (#170)
+# ---------------------------------------------------------------------------
+
+
+class TestHoldingsInPrompt:
+    """Tests for current_holdings parameter in generate_playbook / _build_prompt."""
+
+    def _make_holdings(self) -> list[dict]:
+        return [
+            {
+                "stock_code": "005930",
+                "name": "Samsung",
+                "qty": 10,
+                "entry_price": 71000.0,
+                "unrealized_pnl_pct": 2.3,
+                "holding_days": 3,
+            }
+        ]
+
+    def test_build_prompt_includes_holdings_section(self) -> None:
+        """Prompt should contain a Current Holdings section when holdings are given."""
+        planner = _make_planner()
+        candidates = [_candidate()]
+        holdings = self._make_holdings()
+
+        prompt = planner._build_prompt(
+            "KR",
+            candidates,
+            context_data={},
+            self_market_scorecard=None,
+            cross_market=None,
+            current_holdings=holdings,
+        )
+
+        assert "## Current Holdings" in prompt
+        assert "005930" in prompt
+        assert "+2.30%" in prompt
+        assert "보유 3일" in prompt
+
+    def test_build_prompt_no_holdings_omits_section(self) -> None:
+        """Prompt should NOT contain a Current Holdings section when holdings=None."""
+        planner = _make_planner()
+        candidates = [_candidate()]
+
+        prompt = planner._build_prompt(
+            "KR",
+            candidates,
+            context_data={},
+            self_market_scorecard=None,
+            cross_market=None,
+            current_holdings=None,
+        )
+
+        assert "## Current Holdings" not in prompt
+
+    def test_build_prompt_empty_holdings_omits_section(self) -> None:
+        """Empty list should also omit the holdings section."""
+        planner = _make_planner()
+        candidates = [_candidate()]
+
+        prompt = planner._build_prompt(
+            "KR",
+            candidates,
+            context_data={},
+            self_market_scorecard=None,
+            cross_market=None,
+            current_holdings=[],
+        )
+
+        assert "## Current Holdings" not in prompt
+
+    def test_build_prompt_holdings_instruction_included(self) -> None:
+        """Prompt should include instruction to generate scenarios for held stocks."""
+        planner = _make_planner()
+        candidates = [_candidate()]
+        holdings = self._make_holdings()
+
+        prompt = planner._build_prompt(
+            "KR",
+            candidates,
+            context_data={},
+            self_market_scorecard=None,
+            cross_market=None,
+            current_holdings=holdings,
+        )
+
+        assert "005930" in prompt
+        assert "SELL/HOLD" in prompt
+
+    @pytest.mark.asyncio
+    async def test_generate_playbook_passes_holdings_to_prompt(self) -> None:
+        """generate_playbook should pass current_holdings through to the prompt."""
+        planner = _make_planner()
+        candidates = [_candidate()]
+        holdings = self._make_holdings()
+
+        # Capture the actual prompt sent to Gemini
+        captured_prompts: list[str] = []
+        original_decide = planner._gemini.decide
+
+        async def capture_and_call(data: dict) -> TradeDecision:
+            captured_prompts.append(data.get("prompt_override", ""))
+            return await original_decide(data)
+
+        planner._gemini.decide = capture_and_call  # type: ignore[method-assign]
+
+        await planner.generate_playbook(
+            "KR", candidates, today=date(2026, 2, 8), current_holdings=holdings
+        )
+
+        assert len(captured_prompts) == 1
+        assert "## Current Holdings" in captured_prompts[0]
+        assert "005930" in captured_prompts[0]
+
+    @pytest.mark.asyncio
+    async def test_holdings_stock_allowed_in_parse_response(self) -> None:
+        """Holdings stocks not in candidates list should be accepted in the response."""
+        holding_code = "000660"  # Not in candidates
+        stocks = [
+            {
+                "stock_code": "005930",  # candidate
+                "scenarios": [
+                    {
+                        "condition": {"rsi_below": 30},
+                        "action": "BUY",
+                        "confidence": 85,
+                        "rationale": "oversold",
+                    }
+                ],
+            },
+            {
+                "stock_code": holding_code,  # holding only
+                "scenarios": [
+                    {
+                        "condition": {"price_change_pct_below": -2.0},
+                        "action": "SELL",
+                        "confidence": 90,
+                        "rationale": "stop-loss",
+                    }
+                ],
+            },
+        ]
+        planner = _make_planner(gemini_response=_gemini_response_json(stocks=stocks))
+        candidates = [_candidate()]  # only 005930
+        holdings = [
+            {
+                "stock_code": holding_code,
+                "name": "SK Hynix",
+                "qty": 5,
+                "entry_price": 180000.0,
+                "unrealized_pnl_pct": -1.5,
+                "holding_days": 7,
+            }
+        ]
+
+        pb = await planner.generate_playbook(
+            "KR",
+            candidates,
+            today=date(2026, 2, 8),
+            current_holdings=holdings,
+        )
+
+        codes = [sp.stock_code for sp in pb.stock_playbooks]
+        assert "005930" in codes
+        assert holding_code in codes