fix bug

app/core/opportunity_lifecycle.py

@@ -168,6 +168,24 @@ def detect_static_count(signals: Iterable[Any]) -> int:
     return max_count
 
 
+def has_current_entry_trigger(signals: Iterable[Any], entry_plan: Dict[str, Any]) -> bool:
+    if entry_plan.get("entry_trigger_confirmed") is True:
+        return True
+    summary = str(entry_plan.get("pa_15min_summary") or "")
+    if "即刻入场" in summary and "无动K突破" not in summary:
+        return True
+    for sig in signals or []:
+        text = str(sig)
+        if "15min即刻入场" in text or "当前15min" in text or "当前 15min" in text:
+            return True
+    return False
+
+
+def has_bearish_flow_risk(signals: Iterable[Any]) -> bool:
+    risk_keywords = ("空头加速", "放量阴线", "多头出货", "量价背离")
+    return any(any(keyword in str(sig) for keyword in risk_keywords) for sig in signals or [])
+
+
 def _calc_position_pct(current_price: float, entry_plan: Dict[str, Any]) -> float:
     support = to_float(entry_plan.get("support") or entry_plan.get("support_price") or entry_plan.get("range_low"))
     resistance = to_float(entry_plan.get("resistance") or entry_plan.get("resistance_price") or entry_plan.get("range_high"))
@@ -302,6 +320,10 @@ def apply_entry_quality_gate(
             reasons.append(f"rr1={rr1} < {_cfg_value(cfg, 'min_rr_buy_now')}，禁止现价买入")
 
     if action_status == "可即刻买入":
+        if not has_current_entry_trigger(signals, entry_plan):
+            reasons.append("缺少当前15min触发，禁止现价买入")
+        if has_bearish_flow_risk(signals):
+            reasons.append("出现空头加速/放量阴线风险，禁止现价买入")
         if current_price > 0:
             plan_entry_price = to_float(entry_plan.get("entry_price"))
             # 价格已经回到/跌破计划参考价，且实时 RR 已达标时，应转为入场窗口，不能继续显示“等回踩”。

app/db/altcoin_db.py

@@ -1363,7 +1363,15 @@ def _is_executed_trade(item):
     status = (item.get("status") or "").strip()
     action_status = normalize_action_status(item.get("action_status"), status)
     execution_status = item.get("execution_status") or ""
-    if action_status == "可即刻买入" or execution_status == "buy_now":
+    try:
+        entry_triggered = int(item.get("entry_triggered") or 0) == 1
+    except Exception:
+        entry_triggered = False
+    if entry_triggered:
+        return True
+    if status in ("hit_tp1", "hit_tp2", "stopped_out"):
+        return True
+    if item.get("display_bucket") == "position" or execution_status in ("holding", "completed"):
         return True
     return is_executed_lifecycle(status, action_status, execution_status)
 

app/db/analytics.py

@@ -52,6 +52,42 @@ def _safe_float(value, default=0.0):
         return default
 
 
+EXECUTED_TRADE_WHERE = """(
+    COALESCE(entry_triggered, 0) = 1
+    OR COALESCE(display_bucket, '') = 'position'
+    OR COALESCE(execution_status, '') IN ('holding', 'completed')
+    OR status IN ('hit_tp1', 'hit_tp2', 'stopped_out')
+)"""
+
+
+SUCCESS_CASE = f"""(
+    ({EXECUTED_TRADE_WHERE})
+    AND (
+        status IN ('hit_tp1', 'hit_tp2')
+        OR (
+            status NOT IN ('stopped_out', 'expired', 'invalid', 'archived')
+            AND COALESCE(max_pnl_pct, 0) >= 5
+        )
+    )
+)"""
+
+
+FAILURE_CASE = f"""(
+    ({EXECUTED_TRADE_WHERE})
+    AND (status='stopped_out' OR COALESCE(pnl_pct, 0) <= -3 OR COALESCE(max_drawdown_pct, 0) <= -5)
+)"""
+
+
+def _executed_trade_where(alias=""):
+    prefix = f"{alias}." if alias else ""
+    return f"""(
+    COALESCE({prefix}entry_triggered, 0) = 1
+    OR COALESCE({prefix}display_bucket, '') = 'position'
+    OR COALESCE({prefix}execution_status, '') IN ('holding', 'completed')
+    OR {prefix}status IN ('hit_tp1', 'hit_tp2', 'stopped_out')
+)"""
+
+
 def _parse_dt(value):
     if isinstance(value, datetime):
         return value
@@ -162,20 +198,16 @@ def get_all_recommendations(limit=50, decision_only=False, version="", offset=0,
     except Exception:
         offset = 0
 
-    result_where = """(status IN ('hit_tp1', 'hit_tp2', 'stopped_out')
+    result_where = EXECUTED_TRADE_WHERE
-               OR (COALESCE(max_pnl_pct, 0) >= 5)
-               OR (COALESCE(pnl_pct, 0) <= -3 OR COALESCE(max_drawdown_pct, 0) <= -5))"""
     version_where = " AND strategy_version=?" if version else ""
     params = [version] if version else []
 
     total = None
     summary = None
     version_counts = []
-    success_case = "status IN ('hit_tp1','hit_tp2') OR (status NOT IN ('stopped_out','expired','invalid','archived') AND COALESCE(max_pnl_pct,0) >= 5)"
-    failure_case = "status='stopped_out' OR COALESCE(pnl_pct,0) <= -3 OR COALESCE(max_drawdown_pct,0) <= -5"
     realized_pnl_case = (
-        f"CASE WHEN {failure_case} THEN COALESCE(pnl_pct,0) "
+        f"CASE WHEN {FAILURE_CASE} THEN COALESCE(pnl_pct,0) "
-        f"WHEN {success_case} THEN COALESCE(NULLIF(max_pnl_pct,0), pnl_pct, 0) "
+        f"WHEN {SUCCESS_CASE} THEN COALESCE(NULLIF(max_pnl_pct,0), pnl_pct, 0) "
         "ELSE 0 END"
     )
 
@@ -201,10 +233,10 @@ def get_all_recommendations(limit=50, decision_only=False, version="", offset=0,
                 SELECT
                     COUNT(*) AS total,
                     SUM(CASE WHEN """
-                + success_case
+                + SUCCESS_CASE
                 + """ THEN 1 ELSE 0 END) AS success_count,
                     SUM(CASE WHEN """
-                + failure_case
+                + FAILURE_CASE
                 + """ THEN 1 ELSE 0 END) AS failure_count,
                     SUM("""
                 + realized_pnl_case
@@ -213,7 +245,7 @@ def get_all_recommendations(limit=50, decision_only=False, version="", offset=0,
                 + realized_pnl_case
                 + """) AS best_pnl,
                     AVG(CASE WHEN """
-                + failure_case
+                + FAILURE_CASE
                 + """ THEN COALESCE(pnl_pct,0) END) AS avg_failure_pnl
                 FROM (
                     SELECT r.*
@@ -232,6 +264,9 @@ def get_all_recommendations(limit=50, decision_only=False, version="", offset=0,
                 tuple(params),
             ).fetchone()
             summary = dict(summary_row) if summary_row else {}
+            for key in ("total", "success_count", "failure_count", "total_pnl", "best_pnl", "avg_failure_pnl"):
+                if summary.get(key) is None:
+                    summary[key] = 0
 
             vc_rows = conn.execute(
                 """
@@ -493,13 +528,20 @@ def get_stats():
     decay_watch = decay_candidates[0] if decay_candidates else None
 
     points_24h = []
-    rows_24h = conn.execute("""
+    rows_24h = conn.execute(
-    SELECT substr(track_time, 1, 13) || ':00:00' AS bucket, AVG(pnl_pct) AS avg_pnl, COUNT(*) AS sample_count
+        """
-    FROM price_tracking
+    SELECT substr(pt.track_time, 1, 13) || ':00:00' AS bucket, AVG(pt.pnl_pct) AS avg_pnl, COUNT(*) AS sample_count
-    WHERE julianday(?) - julianday(track_time) <= 1.0
+    FROM price_tracking pt
+    JOIN recommendation r ON r.id = pt.rec_id
+    WHERE julianday(?) - julianday(pt.track_time) <= 1.0
+      AND """
+        + _executed_trade_where("r")
+        + """
     GROUP BY bucket
     ORDER BY bucket ASC
-    """, (now.isoformat(),)).fetchall()
+    """,
+        (now.isoformat(),),
+    ).fetchall()
     for row in rows_24h:
         points_24h.append({
             "time": row["bucket"],
@@ -508,13 +550,20 @@ def get_stats():
         })
 
     points_7d = []
-    rows_7d = conn.execute("""
+    rows_7d = conn.execute(
-    SELECT substr(track_time, 1, 10) AS bucket, AVG(pnl_pct) AS avg_pnl, COUNT(*) AS sample_count
+        """
-    FROM price_tracking
+    SELECT substr(pt.track_time, 1, 10) AS bucket, AVG(pt.pnl_pct) AS avg_pnl, COUNT(*) AS sample_count
-    WHERE julianday(?) - julianday(track_time) <= 7.0
+    FROM price_tracking pt
+    JOIN recommendation r ON r.id = pt.rec_id
+    WHERE julianday(?) - julianday(pt.track_time) <= 7.0
+      AND """
+        + _executed_trade_where("r")
+        + """
     GROUP BY bucket
     ORDER BY bucket ASC
-    """, (now.isoformat(),)).fetchall()
+    """,
+        (now.isoformat(),),
+    ).fetchall()
     for row in rows_7d:
         points_7d.append({
             "time": row["bucket"],

rules.yaml

@@ -407,11 +407,11 @@ event_driven:
         note: Solana meme主题扩散
 meta:
   version: 1
-  last_review: '2026-05-15T11:16:43.982118'
+  last_review: '2026-05-15T11:52:18.602057'
-  last_reverse_analysis: '2026-05-15T11:17:20.540656'
+  last_reverse_analysis: '2026-05-15T11:52:58.300578'
-  total_reviews: 44
+  total_reviews: 45
   total_rules_learned: 37
-  iteration_count: 49
+  iteration_count: 50
   strategy_version: v1.7.11
   strategy_revision_started_at: '2026-05-09T01:20:00'
   strategy_revision_note: 'v1.7.11: 触发时效治理，旧形态只作背景，消息触发显式标记'

tests/test_actionable_active_recommendations.py

@@ -35,7 +35,7 @@ def _insert_recommendation(db_path, **kwargs):
         tp1=110.0,
         tp2=118.0,
         sector='AI',
-        signals='[]',
+        signals='["🟢 15min即刻入场信号"]',
         is_meme=0,
         status='active',
         current_price=100.0,
@@ -49,7 +49,7 @@ def _insert_recommendation(db_path, **kwargs):
         stopped_out_time='',
         expired_time='',
         last_track_time='2026-04-30T10:05:00',
-        entry_plan_json='{}',
+        entry_plan_json='{"entry_trigger_confirmed": true}',
         action_status='持有',
         direction='多头启动',
         strategy_version='v1.2',
@@ -151,9 +151,9 @@ def test_stats_only_count_actionable_active_recommendations(temp_db):
     stats = altcoin_db.get_stats()
     assert stats['active_count'] == 2
     assert stats['raw_active_count'] == 4
-    assert stats['active_pnl_sum'] == 5.0
+    assert stats['active_pnl_sum'] == 0
-    assert stats['active_avg_pnl'] == 5.0
+    assert stats['active_avg_pnl'] == 0
-    assert stats['active_success_count'] == 1
+    assert stats['active_success_count'] == 0
     assert stats['active_failed_count'] == 0
     assert stats['active_pending_count'] == 0
 
@@ -198,12 +198,12 @@ def test_stats_api_exposes_separate_live_and_history_sections(temp_db):
 
     live = stats['live_overview']
     assert live['actionable_count'] == 2
-    assert live['executed_trade_count'] == 1
+    assert live['executed_trade_count'] == 0
-    assert live['executed_pnl_sum'] == 5.0
+    assert live['executed_pnl_sum'] == 0
-    assert live['executed_avg_pnl'] == 5.0
+    assert live['executed_avg_pnl'] == 0
-    assert live['actionable_pnl_sum'] == 5.0
+    assert live['actionable_pnl_sum'] == 0
-    assert live['actionable_avg_pnl'] == 5.0
+    assert live['actionable_avg_pnl'] == 0
-    assert live['actionable_success_count'] == 1
+    assert live['actionable_success_count'] == 0
     assert live['actionable_failed_count'] == 0
     assert live['actionable_pending_count'] == 0
     assert live['raw_active_count'] == 4
@@ -307,6 +307,44 @@ def test_history_avg_pnl_only_uses_real_tp_and_stopout_samples(temp_db):
 
     assert stats['history_overview']['avg_pnl_pct'] == pytest.approx(1.0)
 
+
+def test_history_api_excludes_untriggered_observe_wait_and_invalid_losses(temp_db):
+    _insert_recommendation(
+        temp_db,
+        symbol='OBSLOSS/USDT',
+        action_status='持有',
+        status='active',
+        entry_plan_json='{"entry_action": "继续观察"}',
+        pnl_pct=-4.0,
+        max_drawdown_pct=-6.0,
+    )
+    _insert_recommendation(
+        temp_db,
+        symbol='WAITLOSS/USDT',
+        action_status='等回踩',
+        status='active',
+        entry_plan_json='{"entry_action": "等回踩", "entry_price": 95}',
+        pnl_pct=-5.0,
+        max_drawdown_pct=-7.0,
+    )
+    _insert_recommendation(
+        temp_db,
+        symbol='INVLOSS/USDT',
+        action_status='衰减',
+        status='active',
+        entry_plan_json='{"entry_action": "继续观察"}',
+        pnl_pct=-6.0,
+        max_drawdown_pct=-8.0,
+    )
+
+    page = altcoin_db.get_all_recommendations(limit=20, decision_only=True, with_meta=True)
+
+    assert page['items'] == []
+    assert page['total'] == 0
+    assert page['summary']['total'] == 0
+    assert page['summary']['failure_count'] == 0
+    assert page['summary']['total_pnl'] == 0
+
 def test_version_filter_labels_use_plan_not_executable_to_avoid_wait_pullback_confusion(temp_db):
     _insert_recommendation(
         temp_db,

tests/test_executed_trade_pnl_semantics.py

@@ -25,7 +25,7 @@ def temp_db(monkeypatch, tmp_path):
     return db_path
 
 
-def test_wait_pullback_plan_is_actionable_but_not_counted_as_executed_pnl(temp_db):
+def test_actionable_plans_are_not_counted_as_executed_pnl_until_entry_triggers(temp_db):
     _insert_recommendation(
         temp_db,
         symbol='BUY/USDT',
@@ -59,14 +59,34 @@ def test_wait_pullback_plan_is_actionable_but_not_counted_as_executed_pnl(temp_d
     assert live['buy_now_count'] == 1
     assert live['wait_pullback_count'] == 1
 
-    # 但收益只算已经执行/触发入场的 BUY，不把 WAIT/OBS 的发现后涨幅算收益
+    # 但 buy_now 只是入场窗口，不等于已成交；未触发入场前不计算收益。
+    assert live['executed_trade_count'] == 0
+    assert live['executed_pnl_sum'] == pytest.approx(0.0)
+    assert live['executed_avg_pnl'] == pytest.approx(0.0)
+    assert stats['active_pnl_sum'] == pytest.approx(0.0)
+    assert stats['active_avg_pnl'] == pytest.approx(0.0)
+    assert stats['active_success_count'] == 0
+    assert stats['active_pending_count'] == 0
+
+
+def test_entry_triggered_buy_now_counts_as_executed_pnl(temp_db):
+    _insert_recommendation(
+        temp_db,
+        symbol='BUY/USDT',
+        action_status='可即刻买入',
+        entry_plan_json='{"entry_action": "可即刻买入"}',
+        pnl_pct=5.0,
+        max_pnl_pct=5.0,
+    )
+    conn = altcoin_db.sqlite3.connect(str(temp_db))
+    conn.execute("UPDATE recommendation SET entry_triggered=1 WHERE symbol='BUY/USDT'")
+    conn.commit()
+    conn.close()
+
+    stats = altcoin_db.get_stats()
+    live = stats['live_overview']
     assert live['executed_trade_count'] == 1
     assert live['executed_pnl_sum'] == pytest.approx(5.0)
-    assert live['executed_avg_pnl'] == pytest.approx(5.0)
-    assert stats['active_pnl_sum'] == pytest.approx(5.0)
-    assert stats['active_avg_pnl'] == pytest.approx(5.0)
-    assert stats['active_success_count'] == 1
-    assert stats['active_pending_count'] == 0
 
 
 def test_active_api_marks_wait_plan_as_unexecuted_not_success(temp_db):

tests/test_history_grouping.py

@@ -36,7 +36,7 @@ class RecommendationHistoryBase(unittest.TestCase):
             tp1=110.0,
             tp2=118.0,
             sector='AI',
-            signals='[]',
+            signals=json.dumps(['🟢 15min即刻入场信号'], ensure_ascii=False),
             is_meme=0,
             status='active',
             current_price=100.0,
@@ -60,6 +60,7 @@ class RecommendationHistoryBase(unittest.TestCase):
                 'tp2': 118.0,
                 'rr1': 2.0,
                 'rr2': 3.6,
+                'entry_trigger_confirmed': True,
             }, ensure_ascii=False),
             action_status='可即刻买入',
             direction='多头启动',

tests/test_llm_insights.py

@@ -52,7 +52,7 @@ def _insert_recommendation(db_path, **kwargs):
         stopped_out_time="",
         expired_time="",
         last_track_time="2026-05-01T10:10:00",
-        entry_plan_json=json.dumps({"entry_price": 100.0, "entry_action": "可即刻买入"}, ensure_ascii=False),
+        entry_plan_json=json.dumps({"entry_price": 100.0, "entry_action": "可即刻买入", "entry_trigger_confirmed": True}, ensure_ascii=False),
         action_status="可即刻买入",
         direction="多头启动",
         execution_status="buy_now",

tests/test_opportunity_lifecycle.py

@@ -53,6 +53,28 @@ def test_buy_now_with_bad_rr_sets_real_pullback_price():
     assert any('现价不买' in r for r in reasons)
 
 
+def test_buy_now_requires_current_trigger_and_no_bearish_flow_risk():
+    action, plan, reasons = apply_entry_quality_gate(
+        action_status='可即刻买入',
+        entry_plan={
+            'entry_action': '即刻买入',
+            'entry_price': 1.0,
+            'current_price': 1.0,
+            'stop_loss': 0.95,
+            'tp1': 1.12,
+            'risk_reward_ok': True,
+            'rr1': 2.4,
+        },
+        signals=['1H历史起爆点已过期(12根前)', '⚠️ 1H连续3K空头加速'],
+        current_price=1.0,
+        market_context={'change_24h': 2.0},
+    )
+
+    assert action != '可即刻买入'
+    assert any('缺少当前15min触发' in r for r in reasons)
+    assert any('空头加速' in r for r in reasons)
+
+
 def test_tracker_gate_downgrade_removes_provisional_buy_signal():
     signals = reconcile_buy_signals_after_gate(
         [

tests/test_recommendation_execution_status.py

@@ -31,7 +31,7 @@ class RecommendationExecutionStatusTests(unittest.TestCase):
             tp1=110.0,
             tp2=118.0,
             sector='AI',
-            signals='[]',
+            signals=json.dumps(['🟢 15min即刻入场信号'], ensure_ascii=False),
             is_meme=0,
             status='active',
             current_price=100.0,
@@ -55,6 +55,7 @@ class RecommendationExecutionStatusTests(unittest.TestCase):
                 'tp2': 118.0,
                 'rr1': 2.0,
                 'rr2': 3.6,
+                'entry_trigger_confirmed': True,
             }, ensure_ascii=False),
             action_status='可即刻买入',
             direction='多头启动',

tests/test_signal_trust_stage1.py

@@ -35,7 +35,7 @@ class RecommendationSignalTrustTests(unittest.TestCase):
             tp1=10.8,
             tp2=11.4,
             sector='',
-            signals=json.dumps(['15m 入场窗口信号'], ensure_ascii=False),
+            signals=json.dumps(['🟢 15min即刻入场信号'], ensure_ascii=False),
             is_meme=0,
             status='active',
             current_price=10.0,
@@ -53,6 +53,7 @@ class RecommendationSignalTrustTests(unittest.TestCase):
                 'entry_price': 10.0,
                 'entry_action': '可即刻买入',
                 'risk_reward_ok': True,
+                'entry_trigger_confirmed': True,
                 'rr1': 2.0,
                 'stop_loss': 9.6,
                 'tp1': 10.8,