diff --git a/src/easy_tdx/web/backtest_schemas.py b/src/easy_tdx/web/backtest_schemas.py
index ebcf853..2f17978 100644
--- a/src/easy_tdx/web/backtest_schemas.py
+++ b/src/easy_tdx/web/backtest_schemas.py
@@ -25,6 +25,10 @@ __all__ = [
     "SavedStrategyListResponse",
     "MultiStrategyItem",
     "MultiStrategyBacktestRequest",
+    "SignalScanRequest",
+    "SignalScanRecentSignal",
+    "SignalScanRow",
+    "SignalScanResult",
     "serialize_result",
 ]
 
@@ -372,6 +376,59 @@ class MultiStrategyBacktestRequest(BaseModel):
     execution: Literal["next_open", "next_close"] = Field(default="next_open")
 
 
+# ── 信号雷达（一键扫描已保存策略的最近买卖信号）────────────────────────────────
+
+
+class SignalScanRequest(BaseModel):
+    """信号扫描请求：扫描策略库全部已保存策略，只看最近 N 根 K 线内的信号。"""
+
+    window_bars: int = Field(
+        default=5, ge=1, le=30, description="检查最近 N 根 K 线内的信号（日线即 N 个交易日）"
+    )
+
+
+class SignalScanRecentSignal(BaseModel):
+    """窗口内单根 K 线的信号。"""
+
+    date: str
+    direction: Literal["BUY", "SELL"]
+
+
+class SignalScanRow(BaseModel):
+    """扫描结果单行：一个"策略×标的"子任务的信号摘要。
+
+    single 策略 1 行；portfolio 每只标的 1 行；multi 每个子策略 1 行
+    （行内 ``strategy_name`` 是所属已保存策略的名字）。
+    """
+
+    strategy_id: str
+    strategy_name: str
+    kind: Literal["single", "portfolio", "multi"]
+    strategy: str
+    strategy_label: str = ""
+    params: dict[str, Any] = {}
+    symbol: str
+    category: str = "DAY"
+    latest_signal: Literal["BUY", "SELL"] | None = None  # 窗口内最后一根有信号的 K 线
+    signal_date: str | None = None  # 该信号所在 K 线日期
+    recent_signals: list[SignalScanRecentSignal] = []  # 窗口内全部信号（按时间正序）
+    position: Literal["holding", "flat"] | None = None  # 扫描结束时策略仓位
+    last_close: float | None = None
+    last_bar_date: str | None = None
+    error: str | None = None
+
+
+class SignalScanResult(BaseModel):
+    """信号扫描结果：全部子任务行 + 汇总计数。"""
+
+    rows: list[SignalScanRow]
+    total: int = 0
+    buy_count: int = 0  # 窗口内有买入信号的行数
+    sell_count: int = 0  # 窗口内有卖出信号的行数
+    error_count: int = 0
+    elapsed: float = 0.0
+
+
 # ── 结果序列化 ─────────────────────────────────────────────────────────────────
 
 
diff --git a/src/easy_tdx/web/routers/backtest.py b/src/easy_tdx/web/routers/backtest.py
index 345812b..8d6cfbd 100644
--- a/src/easy_tdx/web/routers/backtest.py
+++ b/src/easy_tdx/web/routers/backtest.py
@@ -25,6 +25,7 @@ from easy_tdx.web.backtest_schemas import (
     OptimizeAllResult,
     OptimizeBacktestRequest,
     PortfolioBacktestRequest,
+    SignalScanRequest,
     StrategySchemaResponse,
     TaskListResponse,
     TaskStateResponse,
@@ -297,6 +298,44 @@ async def run_optimize_all_async(
     return TaskSubmitResponse(task_id=task_id, status=status)
 
 
+# ── 信号雷达（一键扫描已保存策略）────────────────────────────────────────────
+
+
+@router.post("/backtest/signal-scan/run/async", response_model=TaskSubmitResponse, status_code=202)
+async def run_signal_scan_async(
+    req: SignalScanRequest,
+    client: Any = Depends(get_client),
+) -> TaskSubmitResponse:
+    """提交「信号雷达」后台任务：扫描策略库全部已保存策略的最近买卖信号。
+
+    single/portfolio/multi 统一展开成"策略×标的"子任务，按 (symbol, category)
+    去重取最近 800 根 K 线（async 上下文内完成），后台线程内逐条跑信号流程
+    （与回测引擎同口径，含仓位跟踪）。只扫信号、不重跑回测、不改业绩快照。
+    结果为 SignalScanResult，通过 GET /backtest/tasks/{task_id} 轮询。
+    """
+    from easy_tdx.web.signal_scan import expand_targets, fetch_scan_bars, run_scan
+    from easy_tdx.web.strategy_store import get_store
+
+    records = get_store().list_all()
+    if not records:
+        raise ValueError("策略库为空，请先在回测页保存策略")
+
+    targets = expand_targets(records)
+    bars = await fetch_scan_bars(client, targets)
+    description = (
+        f"信号扫描 | {len(records)}条策略 · {len(targets)}个子任务 · 窗口{req.window_bars}根"
+    )
+
+    runner = get_runner()
+    task_id = runner.submit(
+        lambda: run_scan(bars, targets, req.window_bars),
+        description=description,
+    )
+    state = runner.get(task_id)
+    status: Any = state.status if state.status in ("pending", "running") else "running"
+    return TaskSubmitResponse(task_id=task_id, status=status)
+
+
 # ── 内部实现 ───────────────────────────────────────────────────────────────────
 
 
diff --git a/src/easy_tdx/web/signal_scan.py b/src/easy_tdx/web/signal_scan.py
new file mode 100644
index 0000000..dbb4203
--- /dev/null
+++ b/src/easy_tdx/web/signal_scan.py
@@ -0,0 +1,325 @@
+"""信号雷达：一键扫描策略库全部已保存策略的最近买卖信号。
+
+流程（与「策略库 → 重跑到今天」同一套信号口径）：
+1. ``expand_targets``: 把已保存策略（single/portfolio/multi 三种 kind）统一展开成
+   "策略×标的" 子任务列表；数据损坏的条目展开为带 error 的行，不中断整批。
+2. ``fetch_scan_bars``: 按 (symbol, category) 去重取最近 K 线（async，event loop 内
+   调用；单页 800 根足够覆盖内置策略全部参数的指标预热）。
+3. ``run_scan``: 后台线程内逐 target 构建策略实例，跑一遍 bar-by-bar 信号流程
+   （复用 combo._update_position 跟踪仓位，与 BacktestEngine 同口径），
+   汇总最近 ``window`` 根内的买卖信号、结束仓位与最新收盘价。
+
+只扫信号、不重跑完整回测，也不改写策略库保存的业绩快照。
+"""
+
+from __future__ import annotations
+
+import logging
+import re
+import time
+from dataclasses import dataclass, field
+from typing import Any
+
+import pandas as pd
+
+from easy_tdx.backtest.combo import _update_position
+from easy_tdx.backtest.strategy import Strategy
+from easy_tdx.web.strategy_store import SavedStrategy
+
+logger = logging.getLogger(__name__)
+
+# 每标的取的 K 线根数：标准协议单次上限 800 根，足够内置策略最慢参数（如慢线 250）预热。
+SCAN_BARS = 800
+
+# 仓位跟踪用的佣金率（与 combo.extract_factor_signals 默认一致，只影响全仓股数估算）
+_COMMISSION = 0.0003
+
+# 市场前缀纠错规则（与前端 web-ui/src/market.ts detectMarket 保持一致）：
+# 北交所 43/83/87/92/93/4xx/8xx；沪市 6xx/9xx/5xx（含沪市基金）；其余深市。
+_BJ_PREFIX = re.compile(r"^(43|83|87|92|93|4|8)")
+_SH_PREFIX = re.compile(r"^[695]")
+
+
+def _detect_market(code: str) -> str:
+    """按 6 位代码推断市场（SH/SZ/BJ），规则与前端 detectMarket 一致。"""
+    if not re.fullmatch(r"\d{6}", code):
+        return "SZ"
+    if _BJ_PREFIX.match(code):
+        return "BJ"
+    if _SH_PREFIX.match(code):
+        return "SH"
+    return "SZ"
+
+
+def normalize_symbol(raw: str) -> str:
+    """纠正历史保存策略的市场前缀（如 SZ:515080 → SH:515080）。
+
+    早期前端曾按市场前缀漏判沪市基金，导致部分历史保存的 symbol 错标，
+    后端按错配市场取到 0 根 K 线被静默跳过。这里按代码段重判市场兜底。
+    """
+    code = raw.split(":", 1)[-1].strip() if raw else ""
+    if not code:
+        return raw
+    return f"{_detect_market(code)}:{code}"
+
+
+# ── 展开子任务 ────────────────────────────────────────────────────────────────
+
+
+@dataclass
+class ScanTarget:
+    """一个待扫描的"策略×标的"子任务（由已保存策略展开而来）。
+
+    ``error`` 非空表示展开阶段就发现问题（缺 symbol / 组合数据损坏），
+    run_scan 会把它原样写进结果行，不参与取数与信号计算。
+    """
+
+    strategy_id: str  # 所属已保存策略 id
+    strategy_name: str  # 所属已保存策略名（展示用）
+    kind: str  # single | portfolio | multi
+    strategy: str  # 策略注册表 key（如 ma_cross）
+    strategy_label: str = ""
+    params: dict[str, Any] = field(default_factory=dict)
+    symbol: str = ""  # 归一化后的 "市场:代码"
+    category: str = "DAY"
+    error: str | None = None
+
+
+def expand_targets(records: list[SavedStrategy]) -> list[ScanTarget]:
+    """把全部已保存策略展开成"策略×标的"子任务列表。
+
+    - single: 1 条（context.symbol）
+    - portfolio: context.stocks 每只一条（同 strategy + params）
+    - multi: context.items 每条一 target（各自带 strategy/params/symbol）
+    - 缺关键字段的条目展开为 error 行（保证结果表能看到"这条策略有问题"）
+    """
+    targets: list[ScanTarget] = []
+    for rec in records:
+        ctx = rec.context or {}
+        if rec.kind == "multi":
+            items = ctx.get("items")
+            if not isinstance(items, list) or not items:
+                targets.append(
+                    ScanTarget(
+                        strategy_id=rec.id,
+                        strategy_name=rec.name,
+                        kind=rec.kind,
+                        strategy=rec.strategy,
+                        error="组合缺少策略明细（items），可能数据损坏",
+                    )
+                )
+                continue
+            for item in items:
+                if not isinstance(item, dict):
+                    targets.append(_error_target(rec, "组合条目数据损坏"))
+                    continue
+                symbol = item.get("symbol")
+                if not item.get("strategy") or not symbol:
+                    targets.append(_error_target(rec, "组合条目缺少 strategy/symbol"))
+                    continue
+                targets.append(
+                    ScanTarget(
+                        strategy_id=rec.id,
+                        strategy_name=rec.name,
+                        kind=rec.kind,
+                        strategy=str(item["strategy"]),
+                        strategy_label=str(item.get("strategy_label") or ""),
+                        params=item.get("params") or {},
+                        symbol=normalize_symbol(str(symbol)),
+                        category=str(item.get("category") or "DAY"),
+                    )
+                )
+        else:
+            # single 与 portfolio 同构：portfolio 把同策略铺到多只标的
+            stocks = ctx.get("stocks") if rec.kind == "portfolio" else None
+            symbols = [str(s) for s in stocks] if isinstance(stocks, list) and stocks else None
+            if symbols is None:
+                symbol = ctx.get("symbol")
+                if not symbol:
+                    targets.append(_error_target(rec, "缺少标的上下文（symbol）"))
+                    continue
+                symbols = [str(symbol)]
+            for sym in symbols:
+                targets.append(
+                    ScanTarget(
+                        strategy_id=rec.id,
+                        strategy_name=rec.name,
+                        kind=rec.kind,
+                        strategy=rec.strategy,
+                        strategy_label=rec.strategy_label,
+                        params=rec.params or {},
+                        symbol=normalize_symbol(sym),
+                        category=str(ctx.get("category") or "DAY"),
+                    )
+                )
+    return targets
+
+
+def _error_target(rec: SavedStrategy, message: str) -> ScanTarget:
+    """构造一条展开失败的 error 行（保留策略身份，便于在结果表定位）。"""
+    return ScanTarget(
+        strategy_id=rec.id,
+        strategy_name=rec.name,
+        kind=rec.kind,
+        strategy=rec.strategy,
+        error=message,
+    )
+
+
+# ── 取行情 ────────────────────────────────────────────────────────────────────
+
+
+async def fetch_scan_bars(
+    client: Any,
+    targets: list[ScanTarget],
+) -> dict[tuple[str, str], pd.DataFrame | None]:
+    """按 (symbol, category) 去重取最近 ``SCAN_BARS`` 根 K 线（async，event loop 内调用）。
+
+    同一标的被多个策略引用时只取一次。单个标的取数失败/数据无效记 None
+    （不中断整批），run_scan 会给相关行统一标 error。
+    """
+    from easy_tdx.web.convert import category_from_str, market_from_str
+
+    bars: dict[tuple[str, str], pd.DataFrame | None] = {}
+    for t in targets:
+        key = (t.symbol, t.category)
+        if key in bars or t.error:
+            continue
+        try:
+            market_str, code = t.symbol.split(":", 1)
+            df = await client.get_security_bars(
+                market_from_str(market_str),
+                code,
+                category_from_str(t.category),
+                0,
+                SCAN_BARS,
+            )
+        except Exception as exc:  # noqa: BLE001 — 单标的失败不中断整批
+            logger.warning("信号扫描取数失败 %s: %s", t.symbol, exc)
+            bars[key] = None
+            continue
+        if not isinstance(df, pd.DataFrame) or len(df) < 2 or "close" not in df.columns:
+            bars[key] = None
+            continue
+        # 列归一化：日线返回 date 列，_bind_data 需要 datetime；页内已正序但保险再排一次
+        if "datetime" not in df.columns and "date" in df.columns:
+            df = df.copy()
+            df["datetime"] = df["date"]
+        if "datetime" not in df.columns:
+            bars[key] = None
+            continue
+        bars[key] = df.sort_values("datetime").reset_index(drop=True)
+    return bars
+
+
+# ── 信号评估 ──────────────────────────────────────────────────────────────────
+
+
+def evaluate_signals(
+    strategy: Strategy,
+    df: pd.DataFrame,
+    window: int,
+) -> dict[str, Any]:
+    """在 df 上单遍跑策略的 bar-by-bar 信号流程，返回最近 window 根内的信号摘要。
+
+    复现 BacktestEngine._generate_signals / combo.extract_factor_signals 的
+    信号收集 + 仓位跟踪（``_update_position``），保证扫描结果与真实回测一致。
+    """
+    n = len(df)
+    strat = strategy
+    strat._bind_data(df)
+    strat._cash = 100_000.0
+    strat._position_size = 0.0
+    strat._call_init()
+
+    close_arr = df["close"].to_numpy()
+    dt_col = df["datetime"]
+    start = max(0, n - window)
+    recent: list[dict[str, Any]] = []
+
+    for i in range(n):
+        strat._set_bar_index(i)
+        strat._call_next()
+        signals = strat._clear_signals()
+        if signals and i >= start:
+            date = str(dt_col.iloc[i])[:16]
+            for sig in signals:
+                recent.append({"date": date, "direction": sig.direction})
+        _update_position(strat, signals, close_arr[i], _COMMISSION)
+
+    return {
+        "recent_signals": recent,
+        "latest_signal": recent[-1]["direction"] if recent else None,
+        "signal_date": recent[-1]["date"] if recent else None,
+        # 结束仓位（容忍浮点误差）：>0 视为策略当前持仓
+        "position": "holding" if strat._position_size > 0.5 else "flat",
+        "last_close": float(close_arr[-1]),
+        "last_bar_date": str(dt_col.iloc[-1])[:16],
+    }
+
+
+# ── 汇总扫描 ──────────────────────────────────────────────────────────────────
+
+
+def run_scan(
+    bars: dict[tuple[str, str], pd.DataFrame | None],
+    targets: list[ScanTarget],
+    window: int,
+) -> dict[str, Any]:
+    """后台线程内执行：逐 target 构建策略实例并评估信号，汇总成扫描结果。
+
+    单个 target 失败（未知策略/参数非法/取数为空/计算异常）记为该行的
+    error，不影响其余行。返回结构对应 SignalScanResult schema。
+    """
+    from easy_tdx.backtest.strategies import get_registry
+
+    registry = get_registry()
+    rows: list[dict[str, Any]] = []
+    t0 = time.time()
+
+    for t in targets:
+        row: dict[str, Any] = {
+            "strategy_id": t.strategy_id,
+            "strategy_name": t.strategy_name,
+            "kind": t.kind,
+            "strategy": t.strategy,
+            "strategy_label": t.strategy_label,
+            "params": t.params,
+            "symbol": t.symbol,
+            "category": t.category,
+            "latest_signal": None,
+            "signal_date": None,
+            "recent_signals": [],
+            "position": None,
+            "last_close": None,
+            "last_bar_date": None,
+            "error": None,
+        }
+        try:
+            if t.error:
+                raise ValueError(t.error)
+            df = bars.get((t.symbol, t.category))
+            if df is None:
+                raise ValueError("未取到有效 K 线（停牌/代码失效/取数失败）")
+            try:
+                entry = registry.get(t.strategy)
+            except KeyError as exc:
+                raise ValueError(f"未知策略 '{t.strategy}'（可能为旧版本保存）") from exc
+            strategy = entry.build(t.params)
+            row.update(evaluate_signals(strategy, df, window))
+        except Exception as exc:  # noqa: BLE001 — 单行失败不中断整批
+            row["error"] = str(exc) or type(exc).__name__
+            logger.warning("信号扫描失败 %s@%s: %s", t.strategy, t.symbol, exc)
+        rows.append(row)
+
+    buy_count = sum(1 for r in rows if any(s["direction"] == "BUY" for s in r["recent_signals"]))
+    sell_count = sum(1 for r in rows if any(s["direction"] == "SELL" for s in r["recent_signals"]))
+    error_count = sum(1 for r in rows if r["error"])
+    return {
+        "rows": rows,
+        "total": len(rows),
+        "buy_count": buy_count,
+        "sell_count": sell_count,
+        "error_count": error_count,
+        "elapsed": round(time.time() - t0, 2),
+    }
diff --git a/tests/unit/test_signal_scan.py b/tests/unit/test_signal_scan.py
new file mode 100644
index 0000000..918b544
--- /dev/null
+++ b/tests/unit/test_signal_scan.py
@@ -0,0 +1,386 @@
+"""信号雷达（signal_scan）单元 + 端到端测试（离线，无网络）。
+
+覆盖：
+- normalize_symbol 市场前缀纠错
+- expand_targets 三种 kind 展开 + 数据损坏容错
+- fetch_scan_bars 去重取数 / 失败容错 / date→datetime 列归一化
+- evaluate_signals 金叉买入、死叉卖出、仓位跟踪、窗口过滤（与回测引擎同口径）
+- run_scan 单行失败不中断 + 汇总计数
+- POST /backtest/signal-scan/run/async 端到端（fake store + fake 行情）
+"""
+
+from __future__ import annotations
+
+import asyncio
+import time
+
+import numpy as np
+import pandas as pd
+import pytest
+
+pytest.importorskip("fastapi")
+
+from easy_tdx.web.signal_scan import (  # noqa: E402
+    evaluate_signals,
+    expand_targets,
+    fetch_scan_bars,
+    normalize_symbol,
+    run_scan,
+)
+from easy_tdx.web.strategy_store import SavedStrategy  # noqa: E402
+
+# ── 测试数据 ───────────────────────────────────────────────────────────────────
+
+
+def v_shape_df(n_fall: int = 40, n_rise: int = 80, n_drop: int = 0) -> pd.DataFrame:
+    """V 型走势合成日线：下跌 → 上涨（→ 可选急跌），保证出现金叉（→ 死叉）。
+
+    返回的 df 带标准 OHLCV + datetime 列（日线接口返回 date，归一化后是 datetime）。
+    """
+    closes = np.concatenate(
+        [
+            10.0 - np.arange(n_fall) * 0.02,  # 缓跌：MA5 持续低于 MA20
+            9.2 + np.arange(n_rise) * 0.12,  # 稳定上涨：金叉出现
+            (10.0 + n_rise * 0.12 - np.arange(1, n_drop + 1) * 0.5) if n_drop else [],  # 急跌：死叉
+        ]
+    )
+    n = len(closes)
+    dates = pd.date_range("2025-01-01", periods=n, freq="B")
+    return pd.DataFrame(
+        {
+            "datetime": dates,
+            "open": closes - 0.05,
+            "high": closes + 0.10,
+            "low": closes - 0.10,
+            "close": closes,
+            "vol": np.full(n, 5000.0),
+            "amount": closes * 5000,
+        }
+    )
+
+
+def _single(**ctx_overrides: object) -> SavedStrategy:
+    ctx: dict = {"symbol": "SH:601088", "category": "DAY"}
+    ctx.update(ctx_overrides)
+    return SavedStrategy(
+        id="s1",
+        name="神华·双均线",
+        kind="single",
+        strategy="ma_cross",
+        strategy_label="双均线交叉",
+        params={"fast": 5, "slow": 20},
+        context=ctx,
+    )
+
+
+class FakeClient:
+    """假行情客户端：按 (market, code) 返回预置 df，未预置的抛错。"""
+
+    def __init__(self, data: dict[str, pd.DataFrame]) -> None:
+        self.data = data
+        self.calls: list[tuple[str, str]] = []
+
+    async def get_security_bars(self, market, code, category, start, count):  # noqa: ANN001
+        market_str = str(getattr(market, "name", market))
+        key = f"{market_str}:{code}"
+        self.calls.append((key, str(getattr(category, "name", category))))
+        if key not in self.data:
+            raise ConnectionError(f"no data for {key}")
+        return self.data[key]
+
+
+# ── normalize_symbol ──────────────────────────────────────────────────────────
+
+
+@pytest.mark.parametrize(
+    ("raw", "expected"),
+    [
+        ("SH:601088", "SH:601088"),  # 正确的沪市主板
+        ("SZ:515080", "SH:515080"),  # 历史错标的沪市基金 → 纠正
+        ("510300", "SH:510300"),  # 无前缀 → 补全
+        ("SZ:000001", "SZ:000001"),  # 正确的深市主板
+        ("430047", "BJ:430047"),  # 北交所
+        ("830799", "BJ:830799"),  # 北交所 8xx
+        ("SZ:300347", "SZ:300347"),  # 创业板
+    ],
+)
+def test_normalize_symbol(raw: str, expected: str) -> None:
+    assert normalize_symbol(raw) == expected
+
+
+# ── expand_targets ────────────────────────────────────────────────────────────
+
+
+def test_expand_single() -> None:
+    targets = expand_targets([_single()])
+    assert len(targets) == 1
+    t = targets[0]
+    assert (t.strategy, t.params, t.symbol, t.category) == (
+        "ma_cross",
+        {"fast": 5, "slow": 20},
+        "SH:601088",
+        "DAY",
+    )
+    assert t.error is None
+
+
+def test_expand_portfolio_multi_symbols() -> None:
+    rec = SavedStrategy(
+        id="p1",
+        name="银行组合",
+        kind="portfolio",
+        strategy="macd",
+        params={"short": 10, "long": 20},
+        context={"stocks": ["SZ:000001", "515080", "SH:601088"], "category": "DAY"},
+    )
+    targets = expand_targets([rec])
+    assert len(targets) == 3
+    assert [t.symbol for t in targets] == ["SZ:000001", "SH:515080", "SH:601088"]
+    assert all(t.strategy == "macd" for t in targets)
+
+
+def test_expand_multi_items() -> None:
+    rec = SavedStrategy(
+        id="m1",
+        name="老登+小登组合",
+        kind="multi",
+        strategy="multi",
+        context={
+            "items": [
+                {"strategy": "trix", "params": {"m1": 18, "m2": 20}, "symbol": "SZ:300347"},
+                {
+                    "strategy": "ema_cross",
+                    "params": {"fast": 12},
+                    "symbol": "SZ:301308",
+                    "category": "DAY",
+                },
+                {"strategy": "macd", "symbol": "SH:601088"},  # 缺 params → 默认空
+                {"strategy": "", "symbol": "SZ:000001"},  # 缺 strategy → error 行
+            ]
+        },
+    )
+    targets = expand_targets([rec])
+    assert len(targets) == 4
+    ok = [t for t in targets if t.error is None]
+    assert [t.strategy for t in ok] == ["trix", "ema_cross", "macd"]
+    assert ok[1].params == {"fast": 12}
+    assert [t.error is None for t in targets] == [True, True, True, False]
+
+
+def test_expand_error_rows() -> None:
+    # single 缺 symbol / multi 缺 items → 各展开为一条 error 行（不丢策略身份）
+    no_symbol = _single()
+    no_symbol.context = {"category": "DAY"}
+    broken_multi = SavedStrategy(id="m2", name="坏组合", kind="multi", strategy="multi")
+    targets = expand_targets([no_symbol, broken_multi])
+    assert len(targets) == 2
+    assert all(t.error for t in targets)
+    assert [t.strategy_name for t in targets] == ["神华·双均线", "坏组合"]
+
+
+# ── fetch_scan_bars ───────────────────────────────────────────────────────────
+
+
+def test_fetch_scan_bars_dedupe_and_normalize() -> None:
+    df = v_shape_df()
+    # 日线接口风格：date 列而非 datetime
+    daily = df.rename(columns={"datetime": "date"})
+    client = FakeClient({"SH:601088": daily, "SZ:000001": daily})
+    rec1 = _single()
+    rec2 = _single(id="s2", name="另一个神华", strategy="macd", params={})
+    targets = expand_targets([rec1, rec2])  # 同 symbol 只取一次
+    targets.append(expand_targets([_single(symbol="SZ:000001")])[0])
+
+    bars = asyncio.run(fetch_scan_bars(client, targets))
+    assert set(bars) == {("SH:601088", "DAY"), ("SZ:000001", "DAY")}
+    # SH:601088 只取了一次（去重生效）
+    assert len([c for c in client.calls if c[0] == "SH:601088"]) == 1
+    # date 列已归一化为 datetime 且按时间正序
+    out = bars[("SH:601088", "DAY")]
+    assert "datetime" in out.columns
+    assert out["datetime"].is_monotonic_increasing
+
+
+def test_fetch_scan_bars_failure_tolerant() -> None:
+    client = FakeClient({})  # 全部抛错
+    targets = expand_targets([_single()])
+    bars = asyncio.run(fetch_scan_bars(client, targets))
+    assert bars == {("SH:601088", "DAY"): None}
+
+
+# ── evaluate_signals ──────────────────────────────────────────────────────────
+
+
+def _ma_cross_instance():  # noqa: ANN202
+    from easy_tdx.backtest.strategies import get_registry
+
+    return get_registry().get("ma_cross").build({"fast": 5, "slow": 20})
+
+
+def _expected_cross_dates(df: pd.DataFrame, direction: str) -> list[str]:
+    """用 MyTT 独立算出金叉/死叉所在日期（作为期望值，与被测代码解耦）。"""
+    from easy_tdx.MyTT import CROSS, MA
+
+    close = df["close"].to_numpy()
+    fast, slow = MA(close, 5), MA(close, 20)
+    mask = CROSS(fast, slow) if direction == "BUY" else CROSS(slow, fast)
+    return [str(df["datetime"].iloc[i])[:16] for i in range(len(df)) if mask[i]]
+
+
+def test_evaluate_signals_golden_cross_buy() -> None:
+    df = v_shape_df(n_rise=30)  # 只涨不跌：恰好一个金叉、之后无死叉
+    buy_dates = _expected_cross_dates(df, "BUY")
+    assert len(buy_dates) == 1, "V 型数据应恰好产生一个金叉"
+    cross_date = buy_dates[0]
+    cross_idx = [i for i in range(len(df)) if str(df["datetime"].iloc[i])[:16] == cross_date][0]
+
+    # 窗口恰好从金叉那根开始 → 窗口内能捕获 BUY
+    result = evaluate_signals(_ma_cross_instance(), df, window=len(df) - cross_idx)
+    buys = [s for s in result["recent_signals"] if s["direction"] == "BUY"]
+    assert [s["date"] for s in buys] == [cross_date]
+    assert result["latest_signal"] == "BUY"
+    assert result["signal_date"] == cross_date
+    assert result["position"] == "holding"  # 买入后一直持有
+    assert result["last_close"] == pytest.approx(float(df["close"].iloc[-1]))
+    assert result["last_bar_date"] == str(df["datetime"].iloc[-1])[:16]
+
+    # 窗口再收窄一根（金叉在窗口外）→ 不上报旧信号，但仓位跟踪不受窗口影响
+    result2 = evaluate_signals(_ma_cross_instance(), df, window=len(df) - cross_idx - 1)
+    assert result2["recent_signals"] == []
+    assert result2["latest_signal"] is None
+    assert result2["position"] == "holding"
+
+
+def test_evaluate_signals_death_cross_sell() -> None:
+    df = v_shape_df(n_drop=15)  # 涨完急跌：金叉买入 → 死叉卖出
+    result = evaluate_signals(_ma_cross_instance(), df, window=len(df))
+    dirs = [s["direction"] for s in result["recent_signals"]]
+    assert dirs[0] == "BUY"
+    assert dirs[-1] == "SELL"
+    assert result["latest_signal"] == "SELL"
+    assert result["position"] == "flat"  # 清仓
+
+
+def test_evaluate_signals_matches_engine_trades() -> None:
+    """与真实回测引擎成交方向序列一致性抽查（同 df、同策略）。"""
+    from easy_tdx.backtest.engine import BacktestEngine
+
+    df = v_shape_df(n_drop=15)
+    strat = _ma_cross_instance()
+    result = evaluate_signals(strat, df, window=len(df))
+    engine = BacktestEngine(strategy=_ma_cross_instance())
+    trades = engine.run(df).trades
+    engine_dirs = list(trades["direction"])
+    scan_dirs = [s["direction"] for s in result["recent_signals"]]
+    assert scan_dirs == engine_dirs[: len(scan_dirs)]
+
+
+# ── run_scan ──────────────────────────────────────────────────────────────────
+
+
+def test_run_scan_summary_and_errors() -> None:
+    df = v_shape_df()
+    targets = [
+        expand_targets([_single()])[0],  # 正常行（有行情）
+        expand_targets([_single(id="s2", name="同标的第二策略")])[0],  # 同标的复用行情
+    ]
+    # 制造三类失败：未知策略 / 无行情 / 展开错误
+    bad_strategy = expand_targets([_single()])[0]
+    bad_strategy.strategy = "nope_strategy"
+    targets.append(bad_strategy)
+    no_bars = expand_targets([_single()])[0]
+    no_bars.symbol = "SZ:999999"
+    targets.append(no_bars)
+    broken = expand_targets([SavedStrategy(id="x", name="坏", kind="single", strategy="ma_cross")])[
+        0
+    ]
+    targets.append(broken)
+
+    bars = {("SH:601088", "DAY"): df}
+    out = run_scan(bars, targets, window=len(df))
+    assert out["total"] == 5
+    assert out["buy_count"] == 2  # 前两行各有一个金叉买入
+    assert out["sell_count"] == 0
+    assert out["error_count"] == 3  # 未知策略 / 无行情 / 展开错误
+    rows = out["rows"]
+    assert rows[0]["error"] is None
+    assert rows[0]["latest_signal"] == "BUY"
+    assert "未知策略" in rows[2]["error"]
+    assert "未取到有效 K 线" in rows[3]["error"]
+    assert "缺少标的上下文" in rows[4]["error"]
+    assert out["elapsed"] >= 0
+
+
+# ── API 端到端 ────────────────────────────────────────────────────────────────
+
+
+@pytest.fixture()
+def api_client():
+    from fastapi.testclient import TestClient
+
+    from easy_tdx.web import create_app
+
+    app = create_app()
+    with TestClient(app) as c:
+        yield c
+
+
+def test_signal_scan_endpoint_e2e(api_client, monkeypatch) -> None:
+    """POST 提交 → 轮询 done → 结果结构完整（fake store + fake 取数）。"""
+    import easy_tdx.web.signal_scan as sigscan
+    import easy_tdx.web.strategy_store as store_mod
+
+    # 缓跌 59 根 + 末根跳涨：金叉恰好发生在最后一根 K 线（窗口=1 也能捕获）
+    df = v_shape_df(n_fall=59, n_rise=0)
+    df.loc[df.index[-1], ["open", "high", "low", "close"]] = [14.95, 15.2, 14.8, 15.0]
+
+    class FakeStore:
+        def list_all(self) -> list[SavedStrategy]:
+            return [_single()]
+
+    async def fake_fetch(client, targets):  # noqa: ANN001
+        return {("SH:601088", "DAY"): df}
+
+    monkeypatch.setattr(store_mod, "get_store", lambda: FakeStore())
+    monkeypatch.setattr(sigscan, "fetch_scan_bars", fake_fetch)
+
+    resp = api_client.post("/api/v1/backtest/signal-scan/run/async", json={"window_bars": 1})
+    assert resp.status_code == 202, resp.text
+    task_id = resp.json()["task_id"]
+
+    final = None
+    for _ in range(200):
+        poll = api_client.get(f"/api/v1/backtest/tasks/{task_id}")
+        assert poll.status_code == 200
+        final = poll.json()
+        if final["status"] in ("done", "failed"):
+            break
+        time.sleep(0.05)
+    assert final is not None and final["status"] == "done", final
+
+    result = final["result"]
+    assert result["total"] == 1
+    assert result["buy_count"] == 1
+    row = result["rows"][0]
+    assert row["strategy"] == "ma_cross"
+    assert row["symbol"] == "SH:601088"
+    assert row["error"] is None
+    assert row["position"] in ("holding", "flat")
+
+
+def test_signal_scan_endpoint_empty_store(api_client, monkeypatch) -> None:
+    import easy_tdx.web.strategy_store as store_mod
+
+    class EmptyStore:
+        def list_all(self) -> list[SavedStrategy]:
+            return []
+
+    monkeypatch.setattr(store_mod, "get_store", lambda: EmptyStore())
+    resp = api_client.post("/api/v1/backtest/signal-scan/run/async", json={})
+    assert resp.status_code == 400
+    assert "策略库为空" in resp.json()["detail"]
+
+
+def test_signal_scan_endpoint_window_validation(api_client) -> None:
+    resp = api_client.post("/api/v1/backtest/signal-scan/run/async", json={"window_bars": 0})
+    assert resp.status_code == 422
diff --git a/web-ui/src/App.vue b/web-ui/src/App.vue
index 8ab88a2..64cd7de 100644
--- a/web-ui/src/App.vue
+++ b/web-ui/src/App.vue
@@ -12,6 +12,7 @@
         <RouterLink to="/optimize" active-class="active">参数寻优</RouterLink>
         <RouterLink to="/compare" active-class="active">结果对比</RouterLink>
         <RouterLink to="/strategies" active-class="active">策略库</RouterLink>
+        <RouterLink to="/signals" active-class="active">信号雷达</RouterLink>
         <RouterLink to="/settings" active-class="active">服务器设置</RouterLink>
       </nav>
     </header>
diff --git a/web-ui/src/api.ts b/web-ui/src/api.ts
index 08ba6ea..d1fecd2 100644
--- a/web-ui/src/api.ts
+++ b/web-ui/src/api.ts
@@ -17,6 +17,8 @@ import type {
   ServerHostInfo,
   ServerHostListResponse,
   ServerSwitchResult,
+  SignalScanRequest,
+  SignalScanResult,
   StrategiesResponse,
   TaskListResponse,
   TaskState,
@@ -237,6 +239,55 @@ export async function runBacktestWithPolling(
 
 // ── 策略库（已保存策略）──────────────────────────────────────────────────────
 
+/** 提交「信号雷达」一键扫描后台任务，返回 task_id。 */
+export async function submitSignalScanTask(
+  req: SignalScanRequest = {},
+): Promise<TaskSubmitResponse> {
+  const resp = await fetch(`${BASE}/backtest/signal-scan/run/async`, {
+    method: 'POST',
+    headers: { 'Content-Type': 'application/json' },
+    body: JSON.stringify(req),
+  })
+  if (!resp.ok) await throwError(resp)
+  return (await resp.json()) as TaskSubmitResponse
+}
+
+/**
+ * 提交信号扫描并轮询直到 done/failed。
+ *
+ * 与 runBacktestWithPolling 的区别：扫描要在请求内逐标的取行情（提交本身
+ * 就可能耗时数十秒），且标的较多时总时长可能超过 2 分钟，故默认 300s 超时。
+ */
+export async function runSignalScanWithPolling(
+  req: SignalScanRequest = {},
+  onPoll?: (state: TaskState) => void,
+  intervalMs = 500,
+  timeoutMs = 300_000,
+): Promise<TaskState> {
+  const { task_id } = await submitSignalScanTask(req)
+  const start = Date.now()
+  // eslint-disable-next-line no-constant-condition
+  while (true) {
+    const state = await fetchTask(task_id)
+    onPoll?.(state)
+    if (state.status === 'done' || state.status === 'failed') return state
+    if (Date.now() - start > timeoutMs) {
+      throw new Error(`信号扫描超时（${timeoutMs / 1000}s），可稍后重试或减小窗口`)
+    }
+    await new Promise((r) => setTimeout(r, intervalMs))
+  }
+}
+
+/** 断言任务结果为信号扫描结果（类型收窄用）。 */
+export function asSignalScanResult(state: TaskState): SignalScanResult {
+  if (state.status === 'failed') throw new Error(state.error || '信号扫描失败')
+  const result = state.result as SignalScanResult | null
+  if (!result || !Array.isArray(result.rows)) {
+    throw new Error('信号扫描结果格式异常（缺少 rows）')
+  }
+  return result
+}
+
 /** 列出全部已保存策略（按创建时间倒序）。 */
 export async function fetchSavedStrategies(): Promise<SavedStrategyListResponse> {
   const resp = await fetch(`${BASE}/strategies`)
diff --git a/web-ui/src/router.ts b/web-ui/src/router.ts
index c2a1575..4a12be5 100644
--- a/web-ui/src/router.ts
+++ b/web-ui/src/router.ts
@@ -5,15 +5,18 @@ import CompareView from './views/CompareView.vue'
 import OptimizeView from './views/OptimizeView.vue'
 import PortfolioView from './views/PortfolioView.vue'
 import ServerSettingsView from './views/ServerSettingsView.vue'
+import SignalRadarView from './views/SignalRadarView.vue'
 import StrategiesView from './views/StrategiesView.vue'
 
-// 单标的回测（/）+ 组合回测（/portfolio）+ 参数寻优（/optimize）+ 结果对比（/compare）+ 策略库（/strategies）+ 服务器设置（/settings）。
+// 单标的回测（/）+ 组合回测（/portfolio）+ 参数寻优（/optimize）+ 结果对比（/compare）
+// + 策略库（/strategies）+ 信号雷达（/signals）+ 服务器设置（/settings）。
 const routes = [
   { path: '/', name: 'backtest', component: BacktestView },
   { path: '/portfolio', name: 'portfolio', component: PortfolioView },
   { path: '/optimize', name: 'optimize', component: OptimizeView },
   { path: '/compare', name: 'compare', component: CompareView },
   { path: '/strategies', name: 'strategies', component: StrategiesView },
+  { path: '/signals', name: 'signals', component: SignalRadarView },
   { path: '/settings', name: 'settings', component: ServerSettingsView },
 ]
 
diff --git a/web-ui/src/types.ts b/web-ui/src/types.ts
index f1a5ea2..4d5b7e8 100644
--- a/web-ui/src/types.ts
+++ b/web-ui/src/types.ts
@@ -131,7 +131,13 @@ export type TaskStatus = 'pending' | 'running' | 'done' | 'failed'
 export interface TaskState {
   task_id: string
   status: TaskStatus
-  result: BacktestResult | PortfolioResult | OptimizeResult | OptimizeAllResult | null
+  result:
+    | BacktestResult
+    | PortfolioResult
+    | OptimizeResult
+    | OptimizeAllResult
+    | SignalScanResult
+    | null
   error: string | null
   description: string
   elapsed: number
@@ -307,6 +313,48 @@ export interface SavedStrategyListResponse {
   count: number
 }
 
+// ── 信号雷达（POST /api/v1/backtest/signal-scan/run/async） ──────────────────
+
+/** 信号扫描请求：window_bars = 检查最近 N 根 K 线内的信号。 */
+export interface SignalScanRequest {
+  window_bars?: number
+}
+
+/** 窗口内单根 K 线的信号。 */
+export interface SignalScanRecentSignal {
+  date: string
+  direction: 'BUY' | 'SELL'
+}
+
+/** 扫描结果单行：一个"策略×标的"子任务的信号摘要。 */
+export interface SignalScanRow {
+  strategy_id: string
+  strategy_name: string
+  kind: 'single' | 'portfolio' | 'multi'
+  strategy: string
+  strategy_label: string
+  params: Record<string, number | string | boolean>
+  symbol: string
+  category: string
+  latest_signal: 'BUY' | 'SELL' | null
+  signal_date: string | null
+  recent_signals: SignalScanRecentSignal[]
+  position: 'holding' | 'flat' | null
+  last_close: number | null
+  last_bar_date: string | null
+  error: string | null
+}
+
+/** 信号扫描结果：全部子任务行 + 汇总计数。 */
+export interface SignalScanResult {
+  rows: SignalScanRow[]
+  total: number
+  buy_count: number
+  sell_count: number
+  error_count: number
+  elapsed: number
+}
+
 // ── 多策略组合回测（资金分仓，POST /api/v1/backtest/multi-strategy/run/async） ──
 
 /** 多策略组合的单个策略槽位（一个策略 + 参数 + 它要跑的原标的 + 日期）。 */
diff --git a/web-ui/src/views/SignalRadarView.vue b/web-ui/src/views/SignalRadarView.vue
new file mode 100644
index 0000000..1f94b30
--- /dev/null
+++ b/web-ui/src/views/SignalRadarView.vue
@@ -0,0 +1,587 @@
+<script setup lang="ts">
+// 信号雷达页：一键扫描策略库全部已保存策略（单标的/多标的/多策略组合），
+// 把每种策略展开成"策略×标的"子任务，用最近 N 根 K 线（窗口可选，默认 5）
+// 判断买/卖信号并汇总列出——方便每天跟踪"今天哪些策略有信号"。
+// 后端 POST /backtest/signal-scan/run/async；取行情在提交请求内完成（标的多时
+// 提交本身就要等一会儿），结果轮询拿 SignalScanResult。上次扫描结果缓存在
+// localStorage，进页面先展示，避免每次都要重扫。
+
+import { computed, onMounted, ref } from 'vue'
+import { useRouter } from 'vue-router'
+
+import { asSignalScanResult, formatError, runSignalScanWithPolling } from '../api'
+import type { SignalScanResult, SignalScanRow } from '../types'
+
+const router = useRouter()
+
+const WINDOW_OPTIONS = [1, 3, 5, 10]
+const STORAGE_KEY = 'easy-tdx.signal-radar.last'
+
+const windowBars = ref(5)
+const scanning = ref(false)
+const error = ref('')
+const result = ref<SignalScanResult | null>(null)
+const scannedAt = ref('') // 本地时间戳（上次扫描完成时刻）
+const elapsedSec = ref('') // 上次扫描总耗时（提交+计算）
+
+interface CachedScan {
+  result: SignalScanResult
+  scannedAt: string
+  windowBars: number
+}
+
+onMounted(() => {
+  try {
+    const raw = localStorage.getItem(STORAGE_KEY)
+    if (!raw) return
+    const cached = JSON.parse(raw) as CachedScan
+    if (cached?.result?.rows) {
+      result.value = cached.result
+      scannedAt.value = cached.scannedAt || ''
+      if (WINDOW_OPTIONS.includes(cached.windowBars)) windowBars.value = cached.windowBars
+    }
+  } catch {
+    // 缓存损坏则忽略，直接空态
+  }
+})
+
+async function onScan() {
+  if (scanning.value) return
+  scanning.value = true
+  error.value = ''
+  const t0 = Date.now()
+  try {
+    const state = await runSignalScanWithPolling({ window_bars: windowBars.value })
+    result.value = asSignalScanResult(state)
+    scannedAt.value = new Date().toLocaleString('zh-CN', { hour12: false })
+    elapsedSec.value = ((Date.now() - t0) / 1000).toFixed(1)
+    const cached: CachedScan = {
+      result: result.value,
+      scannedAt: scannedAt.value,
+      windowBars: windowBars.value,
+    }
+    localStorage.setItem(STORAGE_KEY, JSON.stringify(cached))
+  } catch (e) {
+    error.value = formatError(e)
+  } finally {
+    scanning.value = false
+  }
+}
+
+// ── 筛选 ─────────────────────────────────────────────────────────────────────
+
+type FilterKey = 'signal' | 'buy' | 'sell' | 'error' | 'all'
+
+const activeFilter = ref<FilterKey>('signal') // 默认只看有信号的
+
+function hasBuy(r: SignalScanRow): boolean {
+  return r.recent_signals.some((s) => s.direction === 'BUY')
+}
+function hasSell(r: SignalScanRow): boolean {
+  return r.recent_signals.some((s) => s.direction === 'SELL')
+}
+
+const filterDefs = computed(() => {
+  const rows = result.value?.rows || []
+  const defs: { key: FilterKey; label: string; count: number }[] = [
+    { key: 'signal', label: '有信号', count: rows.filter((r) => !r.error && r.recent_signals.length > 0).length },
+    { key: 'buy', label: '买入', count: rows.filter((r) => !r.error && hasBuy(r)).length },
+    { key: 'sell', label: '卖出', count: rows.filter((r) => !r.error && hasSell(r)).length },
+    { key: 'error', label: '失败', count: rows.filter((r) => r.error).length },
+    { key: 'all', label: '全部', count: rows.length },
+  ]
+  return defs
+})
+
+const visibleRows = computed(() => {
+  const rows = result.value?.rows || []
+  switch (activeFilter.value) {
+    case 'signal':
+      return rows.filter((r) => !r.error && r.recent_signals.length > 0)
+    case 'buy':
+      return rows.filter((r) => !r.error && hasBuy(r))
+    case 'sell':
+      return rows.filter((r) => !r.error && hasSell(r))
+    case 'error':
+      return rows.filter((r) => r.error)
+    default:
+      return rows
+  }
+})
+
+// ── 展示辅助 ─────────────────────────────────────────────────────────────────
+
+function kindLabel(kind: SignalScanRow['kind']): string {
+  return kind === 'multi' ? '多策略' : kind === 'portfolio' ? '多标的' : '单标的'
+}
+
+/** 窗口内信号序列，如 "B 08-19 · S 08-20"（B=买 S=卖）。 */
+function signalSeq(r: SignalScanRow): string {
+  return r.recent_signals
+    .map((s) => `${s.direction === 'BUY' ? 'B' : 'S'} ${s.date.slice(5, 10)}`)
+    .join(' · ')
+}
+
+/** 跳转单标的回测页回填该子策略（query 模式与策略库「载入」一致）。 */
+function onLoad(r: SignalScanRow) {
+  const codeOnly = r.symbol.includes(':') ? r.symbol.split(':').pop()! : r.symbol
+  router.push({
+    path: '/',
+    query: {
+      strategy: r.strategy,
+      params: JSON.stringify(r.params),
+      symbol: codeOnly || undefined,
+      category: r.category || undefined,
+      endDate: new Date().toISOString().slice(0, 10),
+    },
+  })
+}
+</script>
+
+<template>
+  <div class="radar-view">
+    <header class="page-header">
+      <div>
+        <h2>信号雷达</h2>
+        <p class="subtitle">
+          一键扫描策略库全部已保存策略，列出最近 K 线内出现买入/卖出信号的策略。
+          <template v-if="scannedAt">
+            上次扫描 {{ scannedAt }}<template v-if="elapsedSec">（{{ elapsedSec }}s）</template>。
+          </template>
+        </p>
+      </div>
+      <div class="header-actions">
+        <label class="window-picker">
+          窗口
+          <select v-model="windowBars" :disabled="scanning">
+            <option v-for="w in WINDOW_OPTIONS" :key="w" :value="w">{{ w }} 根</option>
+          </select>
+        </label>
+        <button class="primary" :disabled="scanning" @click="onScan">
+          {{ scanning ? '扫描中…' : '⚡ 一键扫描' }}
+        </button>
+      </div>
+    </header>
+
+    <div v-if="error" class="error-banner">⚠ {{ error }}</div>
+
+    <!-- 扫描中：提交请求内要逐标的取行情，需要等待 -->
+    <div v-if="scanning" class="scanning-box">
+      <span class="spinner"></span>
+      正在扫描：逐标的取最近 800 根 K 线并计算信号（标的较多时约需几十秒，请稍候）…
+    </div>
+
+    <template v-if="result && !scanning">
+      <!-- 汇总卡片 -->
+      <div class="stat-cards">
+        <div class="stat">
+          <span class="k">子任务</span>
+          <span class="v">{{ result.total }}</span>
+        </div>
+        <div class="stat">
+          <span class="k">买入信号</span>
+          <span class="v buy">{{ result.buy_count }}</span>
+        </div>
+        <div class="stat">
+          <span class="k">卖出信号</span>
+          <span class="v sell">{{ result.sell_count }}</span>
+        </div>
+        <div class="stat">
+          <span class="k">失败</span>
+          <span class="v dim">{{ result.error_count }}</span>
+        </div>
+      </div>
+
+      <p class="hint">
+        窗口 = 最近 {{ windowBars }} 根 {{ result.rows[0]?.category === 'DAY' ? '交易日' : 'K 线' }}；
+        盘中最后一根 K 线未收盘，信号为盘中即时值，收盘后为准。
+      </p>
+
+      <!-- 筛选 tab -->
+      <nav class="tabs">
+        <button
+          v-for="f in filterDefs"
+          :key="f.key"
+          :class="['tab', { active: activeFilter === f.key }]"
+          @click="activeFilter = f.key"
+        >
+          {{ f.label }}<span class="tab-count">{{ f.count }}</span>
+        </button>
+      </nav>
+
+      <div v-if="visibleRows.length === 0" class="placeholder">
+        <p>{{ activeFilter === 'signal' ? '窗口内没有任何买卖信号。' : '该筛选下没有子任务。' }}</p>
+        <p class="hint">可切换更大的窗口（如 10 根）或点「一键扫描」重新检查。</p>
+      </div>
+
+      <table v-else class="radar-table">
+        <thead>
+          <tr>
+            <th>策略</th>
+            <th>类型</th>
+            <th>子策略 / 参数</th>
+            <th>标的</th>
+            <th>最新信号</th>
+            <th>窗口内信号</th>
+            <th class="num">最新收盘</th>
+            <th>仓位</th>
+            <th></th>
+          </tr>
+        </thead>
+        <tbody>
+          <tr v-for="(r, i) in visibleRows" :key="`${r.strategy_id}-${i}`" :class="{ errored: r.error }">
+            <td class="name" :title="r.strategy_name">{{ r.strategy_name }}</td>
+            <td><span class="kind-badge" :class="r.kind">{{ kindLabel(r.kind) }}</span></td>
+            <td class="sub-strat">
+              {{ r.strategy_label || r.strategy }}
+              <span class="params">{{ JSON.stringify(r.params) }}</span>
+            </td>
+            <td class="sym">{{ r.symbol }}</td>
+            <td v-if="r.error" class="err" colspan="4">⚠ {{ r.error }}</td>
+            <template v-else>
+              <td>
+                <span v-if="r.latest_signal" class="signal-tag" :class="r.latest_signal">
+                  {{ r.latest_signal === 'BUY' ? '买入' : '卖出' }}
+                </span>
+                <span v-else class="none-tag">—</span>
+              </td>
+              <td class="seq">{{ signalSeq(r) || '—' }}</td>
+              <td class="num">{{ r.last_close != null ? r.last_close.toFixed(2) : '-' }}</td>
+              <td>
+                <span v-if="r.position" class="pos-tag" :class="r.position">
+                  {{ r.position === 'holding' ? '持仓' : '空仓' }}
+                </span>
+              </td>
+            </template>
+            <td>
+              <button v-if="!r.error" class="ghost sm" @click="onLoad(r)">载入</button>
+            </td>
+          </tr>
+        </tbody>
+      </table>
+    </template>
+
+    <div v-if="!result && !scanning && !error" class="placeholder">
+      <p>还没有扫描结果。</p>
+      <p class="hint">
+        点右上角「⚡ 一键扫描」，把策略库里保存的单策略与组合策略全部检查一遍，
+        列出最近 {{ windowBars }} 根 K 线内出现买卖信号的策略。每天收盘后扫一次即可跟踪。
+      </p>
+    </div>
+  </div>
+</template>
+
+<style scoped>
+.radar-view {
+  height: 100%;
+  overflow-y: auto;
+  padding: 16px 20px 32px;
+}
+.page-header {
+  display: flex;
+  align-items: center;
+  justify-content: space-between;
+  margin-bottom: 16px;
+}
+.page-header h2 {
+  font-size: 16px;
+  font-weight: 600;
+}
+.subtitle {
+  font-size: 12px;
+  color: var(--text-dim);
+  margin-top: 4px;
+}
+.header-actions {
+  display: flex;
+  align-items: center;
+  gap: 10px;
+}
+.window-picker {
+  display: flex;
+  align-items: center;
+  gap: 6px;
+  font-size: 12px;
+  color: var(--text-muted);
+}
+.window-picker select {
+  background: var(--bg-panel);
+  color: var(--text);
+  border: 1px solid var(--border);
+  border-radius: var(--radius);
+  padding: 5px 8px;
+  font-size: 12px;
+  cursor: pointer;
+}
+.primary {
+  font-size: 13px;
+  padding: 7px 18px;
+  background: var(--accent);
+  border: 1px solid var(--accent);
+  color: #fff;
+  font-weight: 600;
+  border-radius: var(--radius);
+  cursor: pointer;
+}
+.primary:hover:not(:disabled) {
+  filter: brightness(1.1);
+}
+.primary:disabled {
+  opacity: 0.6;
+  cursor: default;
+}
+.error-banner {
+  background: rgba(239, 65, 70, 0.12);
+  border: 1px solid var(--up);
+  color: var(--up);
+  padding: 10px 14px;
+  border-radius: var(--radius);
+  margin-bottom: 16px;
+  font-size: 13px;
+}
+.scanning-box {
+  display: flex;
+  align-items: center;
+  gap: 10px;
+  padding: 18px 16px;
+  background: var(--bg-panel);
+  border: 1px solid var(--border);
+  border-radius: var(--radius);
+  color: var(--text-muted);
+  font-size: 13px;
+}
+.spinner {
+  width: 14px;
+  height: 14px;
+  border: 2px solid var(--border);
+  border-top-color: var(--accent);
+  border-radius: 50%;
+  animation: spin 0.8s linear infinite;
+  flex-shrink: 0;
+}
+@keyframes spin {
+  to {
+    transform: rotate(360deg);
+  }
+}
+.placeholder {
+  display: flex;
+  flex-direction: column;
+  align-items: center;
+  justify-content: center;
+  text-align: center;
+  height: 50%;
+  color: var(--text-dim);
+  gap: 8px;
+}
+.placeholder .hint,
+.hint {
+  font-size: 12px;
+  color: var(--text-dim);
+  max-width: 560px;
+  line-height: 1.6;
+}
+
+/* 汇总卡片 */
+.stat-cards {
+  display: flex;
+  gap: 14px;
+  margin-bottom: 10px;
+}
+.stat {
+  flex: 1;
+  display: flex;
+  flex-direction: column;
+  gap: 3px;
+  background: var(--bg-panel);
+  border: 1px solid var(--border);
+  border-radius: var(--radius);
+  padding: 10px 14px;
+}
+.stat .k {
+  font-size: 12px;
+  color: var(--text-dim);
+}
+.stat .v {
+  font-size: 22px;
+  font-weight: 700;
+  font-family: var(--font-mono);
+}
+.stat .v.buy {
+  color: var(--up);
+}
+.stat .v.sell {
+  color: var(--down);
+}
+.stat .v.dim {
+  color: var(--text-dim);
+}
+
+/* 筛选 tab（与策略库页同风格） */
+.tabs {
+  display: flex;
+  gap: 4px;
+  border-bottom: 1px solid var(--border);
+  margin: 14px 0 12px;
+}
+.tab {
+  background: transparent;
+  border: none;
+  border-bottom: 2px solid transparent;
+  color: var(--text-muted);
+  padding: 8px 14px;
+  font-size: 13px;
+  font-weight: 500;
+  cursor: pointer;
+  display: flex;
+  align-items: center;
+  gap: 6px;
+}
+.tab:hover {
+  color: var(--text);
+}
+.tab.active {
+  color: var(--text);
+  border-bottom-color: var(--accent);
+}
+.tab-count {
+  font-size: 11px;
+  padding: 1px 6px;
+  border-radius: 8px;
+  background: var(--border);
+  color: var(--text-dim);
+  font-weight: 400;
+}
+.tab.active .tab-count {
+  background: rgba(74, 158, 255, 0.18);
+  color: var(--accent);
+}
+
+/* 结果表 */
+.radar-table {
+  width: 100%;
+  border-collapse: collapse;
+  font-size: 13px;
+}
+.radar-table th,
+.radar-table td {
+  padding: 8px 10px;
+  text-align: left;
+  border-bottom: 1px solid var(--border);
+  vertical-align: middle;
+}
+.radar-table th {
+  color: var(--text-dim);
+  font-size: 12px;
+  font-weight: 600;
+}
+.radar-table .num {
+  text-align: right;
+  font-family: var(--font-mono);
+}
+.radar-table .name {
+  max-width: 180px;
+  overflow: hidden;
+  text-overflow: ellipsis;
+  white-space: nowrap;
+  font-weight: 500;
+}
+.radar-table .sym {
+  font-family: var(--font-mono);
+  font-weight: 600;
+  white-space: nowrap;
+}
+.radar-table .sub-strat {
+  max-width: 220px;
+  overflow: hidden;
+  text-overflow: ellipsis;
+  white-space: nowrap;
+}
+.sub-strat .params {
+  font-family: var(--font-mono);
+  font-size: 11px;
+  color: var(--text-dim);
+  margin-left: 6px;
+}
+.radar-table .seq {
+  font-family: var(--font-mono);
+  font-size: 12px;
+  color: var(--text-muted);
+  white-space: nowrap;
+}
+.radar-table .err {
+  color: var(--up);
+  font-size: 12px;
+}
+.radar-table tr.errored {
+  opacity: 0.75;
+}
+
+/* 徽章 */
+.kind-badge {
+  font-size: 11px;
+  padding: 2px 7px;
+  border-radius: 4px;
+  background: rgba(74, 158, 255, 0.15);
+  color: var(--accent);
+  white-space: nowrap;
+}
+.kind-badge.portfolio {
+  background: rgba(140, 110, 220, 0.18);
+  color: #b39ddb;
+}
+.kind-badge.multi {
+  background: rgba(245, 158, 11, 0.18);
+  color: #f59e0b;
+}
+.signal-tag {
+  font-size: 12px;
+  padding: 2px 10px;
+  border-radius: 4px;
+  font-weight: 600;
+  white-space: nowrap;
+}
+/* A股习惯：买入红、卖出绿 */
+.signal-tag.BUY {
+  background: rgba(239, 65, 70, 0.14);
+  color: var(--up);
+}
+.signal-tag.SELL {
+  background: rgba(24, 160, 88, 0.16);
+  color: var(--down);
+}
+.none-tag {
+  color: var(--text-dim);
+}
+.pos-tag {
+  font-size: 11px;
+  padding: 2px 8px;
+  border-radius: 4px;
+  white-space: nowrap;
+}
+.pos-tag.holding {
+  background: rgba(239, 65, 70, 0.12);
+  color: var(--up);
+}
+.pos-tag.flat {
+  background: var(--border);
+  color: var(--text-dim);
+}
+.ghost {
+  font-size: 12px;
+  padding: 4px 12px;
+  background: transparent;
+  border: 1px solid var(--border);
+  border-radius: var(--radius);
+  color: var(--text-muted);
+  cursor: pointer;
+}
+.ghost:hover:not(:disabled) {
+  border-color: var(--accent);
+  color: var(--accent);
+}
+.sm {
+  font-size: 12px;
+  padding: 4px 12px;
+}
+</style>