feat(analytics): 首响时长+回复率数据管道——消息串算法/日汇总扩展列/员工聚合

批1(A1+A2):管理层要看「每个人的响应质量」。

- 迁移 d9e0f1a2b3c4:msg_daily_stats/stat_daily_staff 各加
  cust_threads/threads_answered/fr_sum_ms(NOT NULL server_default 0,
  幂等守卫照 9b0d0c133035 惯例;models.py 双声明同步)
- summary.py _thread_stats:串=客户连续消息不被员工消息打断的段,
  is_send=None 不参与串判定;fr=员工首条回复−串末条客户消息;
  日切近似 v1(日末未闭合串计 threads 不计 answered,口径写进 docstring)
- recompute_days/recompute_all 都先按 ts 排序再算串(乱序防护)
- staff_summary 聚合三列按账号→员工累加(fr_cnt≡threads_answered 不单列)
- 测试 +10:串算法矩阵 9 例+staff 聚合传递;全量 589 绿
- 本地 86 万行回填验证:daily-stats 60s/staff 10s,rollup 总和与
  明细完全一致,随机 5 行 SQL 独立复算全对

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

yunke-server/migrations/versions/d9e0f1a2b3c4_fr_reply_rate_columns.py

@@ -0,0 +1,62 @@
+"""首响时长+回复率聚合列(msg_daily_stats / stat_daily_staff 各 3 列)
+
+Revision ID: d9e0f1a2b3c4
+Revises: c3d4e5f6a7b8
+Create Date: 2026-09-07
+
+数据分析板块批1(A1+A2,2026-09-07):管理层要看「每个人的响应质量」。
+两表各加 cust_threads / threads_answered / fr_sum_ms——消息串算法见
+app/storage/summary.py(口径与 8-24 spec 对齐,日切近似 v1)。
+fr_cnt ≡ threads_answered(被回串数=样本数),不单列。
+
+幂等:sa.inspect 先查列存在则跳过(照 9b0d0c133035 惯例,SQLite/MySQL
+通用);downgrade 对称删列。模型侧 models.py 同步双声明,防 alembic
+autogenerate 反 DROP。NOT NULL + server_default 0:旧行/旧构造不传也不炸。
+"""
+from collections.abc import Sequence
+
+import sqlalchemy as sa
+from alembic import op
+
+
+# revision identifiers, used by Alembic.
+revision: str = "d9e0f1a2b3c4"
+down_revision: str | Sequence[str] | None = "c3d4e5f6a7b8"
+branch_labels: str | Sequence[str] | None = None
+depends_on: str | Sequence[str] | None = None
+
+_COLUMNS: tuple[tuple[str, str, sa.types.TypeEngine], ...] = (
+    ("msg_daily_stats", "cust_threads", sa.Integer()),
+    ("msg_daily_stats", "threads_answered", sa.Integer()),
+    ("msg_daily_stats", "fr_sum_ms", sa.BigInteger()),
+    ("stat_daily_staff", "cust_threads", sa.Integer()),
+    ("stat_daily_staff", "threads_answered", sa.Integer()),
+    ("stat_daily_staff", "fr_sum_ms", sa.BigInteger()),
+)
+
+
+def _has_column(bind, table: str, column: str) -> bool:
+    insp = sa.inspect(bind)
+    if not insp.has_table(table):
+        return False
+    return column in {c["name"] for c in insp.get_columns(table)}
+
+
+def upgrade() -> None:
+    """Upgrade schema."""
+    bind = op.get_bind()
+    for table, column, type_ in _COLUMNS:
+        if _has_column(bind, table, column):
+            continue  # 幂等:已加过则跳过
+        op.add_column(
+            table,
+            sa.Column(column, type_, nullable=False, server_default=sa.text("0")),
+        )
+
+
+def downgrade() -> None:
+    """Downgrade schema."""
+    bind = op.get_bind()
+    for table, column, _ in _COLUMNS:
+        if _has_column(bind, table, column):
+            op.drop_column(table, column)