feat: 2026-04-15~05-02 累积变更基线 — AI 重构 + Runtime Context + DWS 修复

涵盖（每条对应已存的审计记录）：
- AI 模块拆分：apps/backend/app/ai/apps -> prompts/（8 个 APP + app2a 派生）
  audit: 2026-04-20__ai-module-complete.md
- admin-web AI 管理套件：AIDashboard / AIOperations / AIRunLogs / AITriggers / TriggerManager
  audit: 2026-04-21__admin-web-ai-management-suite.md
- App2 财务洞察 prompt v3 -> v5.1 + 小程序 AI 接入（chat / board-finance）
  audit: 2026-04-22__app2_prompt_v5_1_and_miniprogram_ai_insight.md
- App2 prewarm 全过滤器 + AI 触发器 cron reschedule
  audit: 2026-04-21__app2-finance-prewarm-all-filters.md
  migration: 20260420_ai_trigger_jobs_and_app2_prewarm.sql / 20260421_app2_prewarm_cron_reschedule.sql
- AppType 联合类型对齐 + adminAiAppTypes.test.ts
  audit: 2026-04-30__admin_web_ai_app_type_alignment.md
- DashScope tokens_used 提取修复
  audit: 2026-04-30__backend_dashscope_tokens_used_extraction.md
- App3 线索完整详情 prompt
  audit: 2026-05-01__backend_app3_full_detail_prompt.md
- Runtime Context 沙箱（5-1~5-2 主线）：
  - 后端 schema/service + admin_runtime_context / xcx_runtime_clock 两个 router
  - admin-web RuntimeContext.tsx + miniprogram runtime-clock.ts
  - migration: 20260501__runtime_context_sandbox.sql
  - tools/db/verify_admin_web_sandbox.py + verify_sandbox_end_to_end.py
  - database/changes: 7 份 sandbox_* 验证报告
- 飞球 DWS 修复：finance_area_daily 区域汇总 + task_engine 调整
  + RLS 视图业务日上界（migration 20260502 + scripts/ops/gen_rls_business_date_migration.py）

合规：
- .gitignore 启用 tmp/ 排除
- 不入仓：apps/etl/connectors/feiqiu/.env（API_TOKEN secret，本地修改保留）

待验证清单：
- docs/audit/changes/2026-05-04__cumulative_baseline_pending_verification.md
  每个主题的功能完整性 / 上线验证几乎都未收口，按优先级 P0~P3 逐一处理

apps/backend/app/services/board_service.py

@@ -195,6 +195,7 @@ from typing import Any
 from fastapi import HTTPException
 
 from app.services import fdw_queries
+from app.services.runtime_context import get_runtime_context, task_runtime_filter
 
 logger = logging.getLogger(__name__)
 
@@ -260,7 +261,8 @@ async def get_coach_board(
             detail="最近6个月不支持客源储值排序",
         )
 
-    start_date, end_date = _calc_date_range(time)
+    runtime_ctx = get_runtime_context(site_id)
+    start_date, end_date = _calc_date_range(time, ref_date=runtime_ctx.business_date)
     start_str = str(start_date)
     end_str = str(end_date)
 
@@ -415,20 +417,22 @@ def _query_coach_tasks(
 
     result: dict[int, dict] = {}
     try:
+        runtime_clause, runtime_params = task_runtime_filter(site_id, conn=conn)
         with conn.cursor() as cur:
             # 狭义召回+回访完成数：均从 coach_tasks 统计，status='completed' 表示助教亲自完成
             cur.execute(
-                """
+                f"""
                 SELECT assistant_id, task_type, COUNT(*) AS cnt
                 FROM biz.coach_tasks
                 WHERE assistant_id = ANY(%s)
                   AND site_id = %s
+                  {runtime_clause}
                   AND completed_at >= %s::date
                   AND completed_at < (%s::date + INTERVAL '1 day')::timestamptz
                   AND status = 'completed'
                 GROUP BY assistant_id, task_type
                 """,
-                (assistant_ids, site_id, start_date, end_date),
+                [assistant_ids, site_id, *runtime_params, start_date, end_date],
             )
             for row in cur.fetchall():
                 aid, task_type, cnt = row[0], row[1], row[2] or 0
@@ -470,13 +474,27 @@ def _batch_ideal_days(conn: Any, site_id: int, member_ids: list[int]) -> dict[in
     return result
 
 
-def _batch_coach_details(conn: Any, site_id: int, member_ids: list[int]) -> dict[int, list[dict]]:
-    """批量查询客户-助教服务明细（loyal 维度 coachDetails 用）。每个客户前 5 个。"""
+def _batch_coach_details(
+    conn: Any,
+    site_id: int,
+    member_ids: list[int],
+    *,
+    ref_date: date | None = None,
+) -> dict[int, list[dict]]:
+    """批量查询客户-助教服务明细（loyal 维度 coachDetails 用）。每个客户前 5 个。
+
+    ref_date 默认从 RuntimeContext 取业务日，用于把 60 天消费窗口的上界落到 ``ref_date`` 上，
+    避免 sandbox 模式下读到 sandbox_date 之后的真实消费。
+    """
     from app.services.fdw_queries import _fdw_context
+    from app.services.runtime_context import as_runtime_today_param
+
+    ref = ref_date or as_runtime_today_param(site_id, conn=conn)
     result: dict[int, list[dict]] = {mid: [] for mid in member_ids}
     try:
         with _fdw_context(conn, site_id) as cur:
             # CHANGE 2026-03-29 | coach_spend 改为从 dwd_assistant_service_log 聚合 60 天消费
+            # CHANGE 2026-05-02 | 用 ref_date（业务日）替代 CURRENT_DATE，沙箱不读「未来」
             cur.execute(
                 """
                 SELECT ri.member_id,
@@ -493,7 +511,8 @@ def _batch_coach_details(conn: Any, site_id: int, member_ids: list[int]) -> dict
                            SUM(ledger_amount) AS spend_60d
                     FROM app.v_dwd_assistant_service_log
                     WHERE is_delete = 0
-                      AND create_time >= CURRENT_DATE - INTERVAL '60 days'
+                      AND create_time >= (%s::date - INTERVAL '60 days')
+                      AND create_time <  (%s::date + INTERVAL '1 day')
                       AND tenant_member_id = ANY(%s)
                     GROUP BY tenant_member_id, site_assistant_id
                 ) s60 ON ri.member_id = s60.tenant_member_id
@@ -502,7 +521,7 @@ def _batch_coach_details(conn: Any, site_id: int, member_ids: list[int]) -> dict
                   AND (da.leave_status IS NULL OR da.leave_status = 0)
                 ORDER BY ri.member_id, ri.rs_display DESC
                 """,
-                (member_ids, member_ids),
+                (ref, ref, member_ids, member_ids),
             )
             for row in cur.fetchall():
                 mid = row[0]
@@ -690,7 +709,8 @@ async def get_finance_board(
     - area≠all 时 overview 覆盖逻辑保留
     - compare=1 时对上期执行同样缓存/日粒度逻辑
     """
-    start_date, end_date = _calc_date_range(time)
+    runtime_ctx = get_runtime_context(site_id)
+    start_date, end_date = _calc_date_range(time, ref_date=runtime_ctx.business_date)
     start_str = str(start_date)
     end_str = str(end_date)