diff --git a/deploy/profile-scripts/mofin_db.py b/deploy/profile-scripts/mofin_db.py
index ce7722bf..b3a80af2 100644
--- a/deploy/profile-scripts/mofin_db.py
+++ b/deploy/profile-scripts/mofin_db.py
@@ -2430,3 +2430,59 @@ def sync_strategy_def(conn, d: dict):
         print(f"  [SYNC_DEF] {name} 新注册（needs_review=1）")
     conn.commit()
     return changed
+
+
+# ── 版本化写入函数（包装原有 write_holding_strategy）──
+def write_holding_strategy_versioned(conn, code, name, data, source_trigger="batch_12d"):
+    """版本化写入策略卡：
+    1. 对比关键字段，有变化 → supersede旧版 + 新增active行(version+1)
+    2. 无变化 → 跳过写入
+    3. 首次创建 → version=1.1
+    """
+    from datetime import datetime
+    now = datetime.now().isoformat()
+
+    # 读当前 active 记录
+    old = conn.execute(
+        "SELECT id, version, entry_low, entry_high, stop_loss, take_profit, timing_signal "
+        "FROM holding_strategies WHERE code=? AND status='active'", (code,)).fetchone()
+
+    key_fields = ['entry_low', 'entry_high', 'stop_loss', 'take_profit', 'timing_signal']
+    changed = False
+    if old:
+        for i, f in enumerate(key_fields):
+            old_v = old[i+2]
+            new_v = data.get(f)
+            if new_v is not None and str(old_v or '') != str(new_v):
+                changed = True
+                break
+
+    if old and not changed:
+        print(f"  [NOCHANGE] {code} 关键字段无变化, 跳过写入", flush=True)
+        return (True, "no_change")
+
+    # 版本号处理
+    if old and changed:
+        old_id = old[0]
+        old_ver = old[1] or '1.1'
+        conn.execute(
+            "UPDATE holding_strategies SET status='superseded', superseded_at=? WHERE id=?",
+            (now, old_id))
+        try:
+            major, minor = old_ver.split('.')
+            new_ver = f"{major}.{int(minor)+1}"
+        except:
+            new_ver = "1.2"
+        print(f"  [VERSION] {code} v{old_ver}->superseded, 新v{new_ver}", flush=True)
+    elif not old:
+        new_ver = '1.1'
+        data['cycle_start'] = now[:10]
+        print(f"  [NEW] {code} v1.1 新建策略卡", flush=True)
+    else:
+        new_ver = old[1] if old else '1.1'
+
+    if not data.get('strategy_source'):
+        data['strategy_source'] = data.get('strategy_name', '')
+    data['version'] = new_ver
+
+    return write_holding_strategy(conn, code, name, data, source_trigger)
diff --git a/deploy/profile-scripts/strategy_effectiveness.py b/deploy/profile-scripts/strategy_effectiveness.py
new file mode 100644
index 00000000..3c605b9b
--- /dev/null
+++ b/deploy/profile-scripts/strategy_effectiveness.py
@@ -0,0 +1,243 @@
+#!/usr/bin/env python3
+"""策略到期评估模块：用完整K线数据评估每个区间的职责履行"""
+
+import os, sys, sqlite3, json
+from datetime import datetime, timedelta
+
+DB = "/home/hmo/MoFin/data/mofin.db"
+
+def get_expired_strategies(conn):
+    """获取已到期且未评估的策略"""
+    now = datetime.now().strftime("%Y-%m-%d")
+    return conn.execute("""
+        SELECT id, code, version, strategy_source, entry_low, entry_high,
+               stop_loss, take_profit, buy_zone_expected_days, take_profit_expected_days,
+               created_at, superseded_at
+        FROM holding_strategies
+        WHERE status IN ('active', 'superseded')
+          AND superseded_at IS NOT NULL
+          AND id NOT IN (SELECT strategy_id FROM strategy_effectiveness)
+        ORDER BY superseded_at
+    """).fetchall()
+
+def get_kline(conn, code, start_date, end_date):
+    """获取K线数据"""
+    return conn.execute("""
+        SELECT date, open, close, high, low
+        FROM stock_daily
+        WHERE code=? AND date BETWEEN ? AND ?
+        ORDER BY date
+    """, (code, start_date, end_date)).fetchall()
+
+def evaluate_zone(klines, zone_type, zone_low, zone_high, expected_days):
+    """评估单个区间的职责履行"""
+    if not klines or zone_low is None or zone_high is None:
+        return {"accuracy": "no_data", "detail": "无K线数据或区间未设定"}
+
+    first_date = klines[0][0]
+    last_date = klines[-1][0]
+
+    # 统计每日形态
+    days_in_zone = 0  # 收盘在区间内
+    days_penetrated_above = 0  # 收盘突破上沿
+    days_penetrated_below = 0  # 收盘突破下沿
+    v_shape_days = 0  # V型（进入后离开）
+    first_trigger_day = None  # 首次触发日
+    prev_close = None
+
+    for date, open_p, close, high, low in klines:
+        if close is None:
+            continue
+        # 收盘价相对于区间
+        if zone_low <= close <= zone_high:
+            days_in_zone += 1
+            if first_trigger_day is None:
+                first_trigger_day = date
+        elif close > zone_high:
+            days_penetrated_above += 1
+        elif close < zone_low:
+            days_penetrated_below += 1
+
+        # V型检测：前一天在区间内，今天离开
+        if prev_close is not None:
+            if (zone_low <= prev_close <= zone_high) and (close < zone_low or close > zone_high):
+                v_shape_days += 1
+        prev_close = close
+
+    total_days = len(klines)
+    actual_days_to_trigger = None
+    if first_trigger_day:
+        fd = datetime.strptime(first_trigger_day, "%Y-%m-%d")
+        sd = datetime.strptime(first_date, "%Y-%m-%d")
+        actual_days_to_trigger = (fd - sd).days
+
+    # 区间职责评估
+    if zone_type == "buy_zone":
+        # 买入区职责：触发后是否上涨
+        if first_trigger_day:
+            trigger_idx = next(i for i, k in enumerate(klines) if k[0] == first_trigger_day)
+            after_klines = klines[trigger_idx:]
+            if after_klines:
+                trigger_close = after_klines[0][2]
+                max_after = max(k[2] for k in after_klines if k[2])
+                profit_pct = (max_after - trigger_close) / trigger_close * 100 if trigger_close else 0
+                if profit_pct > 5:
+                    accuracy = "effective"
+                elif profit_pct > 0:
+                    accuracy = "partially_effective"
+                else:
+                    accuracy = "ineffective"
+            else:
+                accuracy = "no_data"
+        else:
+            accuracy = "not_triggered"
+
+    elif zone_type == "stop_loss":
+        # 止损职责：触发后是否继续跌（避免更大损失）
+        if first_trigger_day:
+            trigger_idx = next(i for i, k in enumerate(klines) if k[0] == first_trigger_day)
+            after_klines = klines[trigger_idx:]
+            if len(after_klines) >= 2:
+                trigger_close = after_klines[0][2]
+                # 之后1-2天是否继续跌
+                next_2d_low = min(k[4] for k in after_klines[1:3] if k[4])
+                if next_2d_low and next_2d_low < trigger_close * 0.97:
+                    accuracy = "effective"  # 止损后继续跌，止损正确
+                elif next_2d_low and next_2d_low > trigger_close * 1.03:
+                    accuracy = "ineffective"  # 止损后反弹，被洗盘
+                else:
+                    accuracy = "neutral"
+            else:
+                accuracy = "no_data"
+        else:
+            accuracy = "not_triggered"
+
+    elif zone_type == "take_profit":
+        # 止盈职责：触发后是否回落（锁定正确）
+        if first_trigger_day:
+            trigger_idx = next(i for i, k in enumerate(klines) if k[0] == first_trigger_day)
+            after_klines = klines[trigger_idx:]
+            if len(after_klines) >= 2:
+                trigger_close = after_klines[0][2]
+                # 之后3天最高价
+                max_3d = max(k[3] for k in after_klines[1:4] if k[3])
+                if max_3d and max_3d > trigger_close * 1.05:
+                    accuracy = "ineffective"  # 止盈后继续涨，偏保守
+                elif max_3d and max_3d < trigger_close:
+                    accuracy = "effective"  # 止盈后回落，锁定正确
+                else:
+                    accuracy = "neutral"
+            else:
+                accuracy = "no_data"
+        else:
+            accuracy = "not_triggered"
+
+    # 时间准确性
+    if actual_days_to_trigger and expected_days:
+        ratio = actual_days_to_trigger / expected_days
+        if ratio <= 1:
+            time_accuracy = "on_time"
+        elif ratio <= 1.5:
+            time_accuracy = "slightly_late"
+        else:
+            time_accuracy = "late"
+    else:
+        time_accuracy = "no_data"
+
+    return {
+        "accuracy": accuracy,
+        "time_accuracy": time_accuracy,
+        "actual_days": actual_days_to_trigger,
+        "expected_days": expected_days,
+        "days_in_zone": days_in_zone,
+        "v_shape_days": v_shape_days,
+        "total_days": total_days,
+    }
+
+def evaluate_strategy(conn, strategy):
+    """评估单个策略"""
+    sid, code, ver, source, el, eh, sl, tp, buy_exp, tp_exp, created, superseded = strategy
+
+    # 获取K线数据（从创建到被替代）
+    klines = get_kline(conn, code, created[:10], superseded[:10])
+    if not klines:
+        return None
+
+    buy_eval = evaluate_zone(klines, "buy_zone", el, eh, buy_exp)
+    tp_eval = evaluate_zone(klines, "take_profit", tp, tp*1.05 if tp else None, tp_exp) if tp else None
+    sl_eval = evaluate_zone(klines, "stop_loss", sl*0.95 if sl else None, sl, None) if sl else None
+
+    # 综合评价
+    assessment = []
+    if buy_eval["accuracy"] == "ineffective":
+        assessment.append("买入区预判有误（触发后下跌）")
+    elif buy_eval["accuracy"] == "effective":
+        assessment.append("买入区预判准确")
+    if sl_eval and sl_eval["accuracy"] == "ineffective":
+        assessment.append("止损被洗盘（触发后反弹）")
+    elif sl_eval and sl_eval["accuracy"] == "effective":
+        assessment.append("止损有效（避免更大损失）")
+    if tp_eval and tp_eval["accuracy"] == "ineffective":
+        assessment.append("止盈偏保守（触发后继续涨）")
+    elif tp_eval and tp_eval["accuracy"] == "effective":
+        assessment.append("止盈锁定正确")
+    if buy_eval["time_accuracy"] == "late":
+        assessment.append("入场时机偏晚")
+    elif buy_eval["time_accuracy"] == "on_time":
+        assessment.append("入场时机准确")
+
+    # 改进建议
+    suggestions = []
+    if buy_eval["accuracy"] == "ineffective":
+        suggestions.append("买入区需要下调（当前价位偏高）")
+    if buy_eval["time_accuracy"] == "late":
+        suggestions.append("买入区预期天数需要延长")
+    if sl_eval and sl_eval["accuracy"] == "ineffective":
+        suggestions.append("止损位设置过于激进，考虑放宽")
+    if tp_eval and tp_eval["accuracy"] == "ineffective":
+        suggestions.append("止盈位偏保守，可适当提高")
+
+    return {
+        "strategy_id": sid,
+        "code": code,
+        "strategy_source": source,
+        "version": ver,
+        "period_start": created[:10],
+        "period_end": superseded[:10],
+        "buy_zone_accuracy": buy_eval["accuracy"],
+        "take_profit_accuracy": tp_eval["accuracy"] if tp_eval else "no_zone",
+        "stop_loss_accuracy": sl_eval["accuracy"] if sl_eval else "no_zone",
+        "time_accuracy": buy_eval["time_accuracy"],
+        "overall_assessment": "; ".join(assessment) if assessment else "数据不足",
+        "improvement_suggestion": "; ".join(suggestions) if suggestions else "暂无改进建议",
+    }
+
+def main():
+    conn = sqlite3.connect(DB, timeout=30)
+    expired = get_expired_strategies(conn)
+    print(f"待评估策略: {len(expired)} 个")
+
+    ok = 0
+    for strategy in expired:
+        result = evaluate_strategy(conn, strategy)
+        if result:
+            conn.execute("""
+                INSERT INTO strategy_effectiveness
+                (strategy_id, code, strategy_source, version, period_start, period_end,
+                 buy_zone_accuracy, take_profit_accuracy, stop_loss_accuracy,
+                 time_accuracy, overall_assessment, improvement_suggestion)
+                VALUES (?,?,?,?,?,?,?,?,?,?,?,?)
+            """, (result["strategy_id"], result["code"], result["strategy_source"],
+                  result["version"], result["period_start"], result["period_end"],
+                  result["buy_zone_accuracy"], result["take_profit_accuracy"],
+                  result["stop_loss_accuracy"], result["time_accuracy"],
+                  result["overall_assessment"], result["improvement_suggestion"]))
+            ok += 1
+            print(f"  {result['code']} v{result['version']}: {result['overall_assessment'][:50]}")
+
+    conn.commit()
+    conn.close()
+    print(f"\n评估完成: {ok} 个策略已评估")
+
+if __name__ == "__main__":
+    main()