feat(analytics): 看板管理化补强——员工活跃排行表+预警行动入口卡片

管理者反馈「纯汇总数字看不到有用信息」:overview 载荷扩
staff_ranking(全员行:msg_total rollup 优先/空表回退 msg_daily_stats
聚合,active_* 两路径统一走 msg_daily_stats 窗内 distinct peer——
stat_daily_staff 的 active_* 是当日快照,跨日 SUM/MAX 语义皆错;
call_cnt 按 user_id 落窗直查;环比同期对齐)+ actions(该回未回 2h/
真流失 30d/敏感词 pending,复用已测试查询路径各取 total)。

前端看板:toolbar 下三张可点行动卡(0 灰显仍可点,直达处置页,
随 channel 切换刷新)+ 趋势卡下员工排行表(max-height 420 滚动,
未映射小 tag,环比色同卡片惯例 None 显 '-')。

测试 574→577 全绿(rollup 聚合/回退/行动计数三新);build 过。

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

yunke-server/app/analytics/metrics.py

@@ -19,6 +19,7 @@ from app.db.models import (
     Message,
     MsgDailyStats,
     PhoneCall,
+    SensitiveHit,
     Staff,
     StatDailyStaff,
 )
@@ -264,6 +265,189 @@ async def anomaly(session: AsyncSession, channel: str) -> dict | None:
     return None
 
 
+async def staff_ranking(
+    session: AsyncSession, *, channel: str, scope: str,
+) -> list[dict]:
+    """员工活跃排行(A2 核心子集,2026-09-07 管理者反馈补强)。
+
+    口径:msg_total=stat_daily_staff 聚合(空表回退 msg_daily_stats+映射,
+    同 _active_staff 模式);call_cnt=phone_call 按 user_id 落窗直查(3k 行
+    小表);环比=与 _prev_scope_days 同期对比(None=前窗无数据);名字取
+    staff.name,无 staff 行/未映射账号回退 user_id 原值标 unmapped。
+    排序 msg_total desc + user_id asc 决胜。返回全部行(员工 ~41)。
+
+    active_friends/active_rooms 两路径统一从 msg_daily_stats 算窗内
+    COUNT(DISTINCT peer)(映射合并到员工后,同 recompute_days 模式):
+    stat_daily_staff 的 active_* 是**当日快照**,跨日 SUM 会重复计数、
+    MAX 只是峰值,皆非「窗内活跃去重数」——rollup 只供 msg_total,
+    避免两路径语义分叉。
+    """
+    days = scope_day_keys(scope, today_key())
+    amap = await account_map(session, channel)
+
+    # 活跃客户/群 + 回退 msg_total:落窗拉行,Python 侧映射后按 user 去重
+    # (COUNT(DISTINCT peer) 必须在「账号合并到员工」之后——同人多账号
+    # 跨账号去重,写 SQL 反而绕且踩 only_full_group_by)
+    rows = (
+        await session.execute(
+            sa.select(
+                MsgDailyStats.owner_account_id,
+                MsgDailyStats.peer_kind,
+                MsgDailyStats.peer_id,
+                MsgDailyStats.send_cnt,
+                MsgDailyStats.recv_cnt,
+            ).where(
+                MsgDailyStats.channel == channel, MsgDailyStats.day.in_(days)
+            )
+        )
+    ).all()
+    act: dict[str, dict[str, set]] = {}
+    msg_fallback: dict[str, int] = {}
+    for owner, kind, peer, s, r in rows:
+        uid = amap.get(owner, owner)
+        a = act.setdefault(uid, {"friends": set(), "rooms": set()})
+        if kind == "friend":  # 显式分支:未来新 kind 跳过,不误入 rooms
+            a["friends"].add(peer)
+        elif kind == "room":
+            a["rooms"].add(peer)
+        msg_fallback[uid] = msg_fallback.get(uid, 0) + int(s or 0) + int(r or 0)
+
+    use_rollup = await _staff_rows(session)
+    if use_rollup:
+        rollup = (
+            await session.execute(
+                sa.select(
+                    StatDailyStaff.user_id,
+                    sa.func.coalesce(
+                        sa.func.sum(
+                            StatDailyStaff.msg_sent + StatDailyStaff.msg_recv
+                        ),
+                        0,
+                    ),
+                )
+                .where(
+                    StatDailyStaff.channel == channel,
+                    StatDailyStaff.day.in_(days),
+                )
+                .group_by(StatDailyStaff.user_id)
+            )
+        ).all()
+        msg_total = {uid: int(v) for uid, v in rollup}
+    else:
+        msg_total = msg_fallback
+
+    # 通话:按 user_id 落窗直查(窗口换算同 _call_count 写法)
+    calls: dict[str, int] = {}
+    if days:
+        lo, _ = day_bounds_ms(days[0])
+        hi_start, _ = day_bounds_ms(days[-1])
+        call_rows = (
+            await session.execute(
+                sa.select(PhoneCall.user_id, sa.func.count())
+                .where(
+                    PhoneCall.user_id.is_not(None),
+                    PhoneCall.start_call_time.is_not(None),
+                    PhoneCall.start_call_time >= lo,
+                    PhoneCall.start_call_time < hi_start + 86_400_000,
+                )
+                .group_by(PhoneCall.user_id)
+            )
+        ).all()
+        calls = {uid: int(v) for uid, v in call_rows}
+
+    # 环比:同期对齐前窗(仅周/月;今日 vs 昨日全天会误导,与 overview 同口径)
+    prev_total: dict[str, int] = {}
+    if scope in ("week", "month"):
+        prev_days = _prev_scope_days(scope, days)
+        if use_rollup:
+            prev_rows = (
+                await session.execute(
+                    sa.select(
+                        StatDailyStaff.user_id,
+                        sa.func.coalesce(
+                            sa.func.sum(
+                                StatDailyStaff.msg_sent + StatDailyStaff.msg_recv
+                            ),
+                            0,
+                        ),
+                    )
+                    .where(
+                        StatDailyStaff.channel == channel,
+                        StatDailyStaff.day.in_(prev_days),
+                    )
+                    .group_by(StatDailyStaff.user_id)
+                )
+            ).all()
+            prev_total = {uid: int(v) for uid, v in prev_rows}
+        else:
+            prev_rows = (
+                await session.execute(
+                    sa.select(
+                        MsgDailyStats.owner_account_id,
+                        sa.func.coalesce(
+                            sa.func.sum(
+                                MsgDailyStats.send_cnt + MsgDailyStats.recv_cnt
+                            ),
+                            0,
+                        ),
+                    )
+                    .where(
+                        MsgDailyStats.channel == channel,
+                        MsgDailyStats.day.in_(prev_days),
+                    )
+                    .group_by(MsgDailyStats.owner_account_id)
+                )
+            ).all()
+            for owner, v in prev_rows:
+                uid = amap.get(owner, owner)  # 同人多账号累加,不覆盖
+                prev_total[uid] = prev_total.get(uid, 0) + int(v)
+
+    # 名字/未映射:staff 几十行全拉;映射值集=在册员工 user_id 全集
+    staff_names = {
+        uid: name
+        for uid, name in (
+            await session.execute(sa.select(Staff.user_id, Staff.name))
+        ).all()
+    }
+    mapped_uids = set(amap.values())
+
+    out = []
+    for uid in sorted(set(msg_total) | set(act) | set(calls),
+                      key=lambda u: (-msg_total.get(u, 0), u)):
+        cur, prev = msg_total.get(uid, 0), prev_total.get(uid, 0)
+        out.append({
+            "user_id": uid,
+            "name": staff_names.get(uid) or uid,
+            "unmapped": uid not in staff_names and uid not in mapped_uids,
+            "msg_total": cur,
+            "active_friends": len(act[uid]["friends"]) if uid in act else 0,
+            "active_rooms": len(act[uid]["rooms"]) if uid in act else 0,
+            "call_cnt": calls.get(uid, 0),
+            "msg_delta": round((cur - prev) / prev, 3) if cur and prev else None,
+        })
+    return out
+
+
+async def action_counts(session: AsyncSession, *, channel: str) -> dict:
+    """预警行动入口计数(看板顶部卡片):复用已测试的查询路径,各取 total。"""
+    un = await unreplied(session, channel=channel, hours=2, page=1, page_size=1)
+    ch = await churn(session, channel=channel, kind="real", tier=30, min_msgs=5,
+                     page=1, page_size=1)
+    pending = (
+        await session.execute(
+            sa.select(sa.func.count()).select_from(SensitiveHit).where(
+                SensitiveHit.channel == channel,
+                SensitiveHit.disposition == "pending",
+            )
+        )
+    ).scalar_one()
+    return {
+        "unreplied_2h": int(un["total"]),
+        "churn_real_30d": int(ch["total"]),
+        "sensitive_pending": int(pending),
+    }
+
+
 async def overview(
     session: AsyncSession, *, channel: str, scope: str, trend_days: int = 30
 ) -> dict[str, Any]:
@@ -341,6 +525,8 @@ async def overview(
         "cards": cards,
         "trend": trend,
         "anomaly": await anomaly(session, channel),
+        "staff_ranking": await staff_ranking(session, channel=channel, scope=scope),
+        "actions": await action_counts(session, channel=channel),
     }
 
 

yunke-server/tests/test_analytics_overview.py

@@ -1,12 +1,19 @@
 """A1 总览指标:卡片/首沟通口径/环比同期对齐(仅周月)/异常警示。"""
 from __future__ import annotations
 
+import datetime as dt
+
 import pytest
 
 from app.analytics import metrics
 from app.db.models import (
+    Customer,
+    Message,
     MsgDailyStats,
     PhoneCall,
+    SensitiveHit,
+    SensitiveWord,
+    Staff,
     StatDailyStaff,
     WechatAccount,
 )
@@ -204,3 +211,136 @@ async def test_anomaly_new_staff_detail_and_sort(make_client, monkeypatch):
         assert "new" not in staff["u1"]  # 老员工不带标记
 
     await make_client(seed)
+
+
+async def test_staff_ranking(make_client, monkeypatch):
+    """员工活跃排行:rollup 供 msg_total;active_* 统一走 msg_daily_stats 去重。
+
+    _TODAY=20260904 周五 → 本周 [0831..0904],上周 [0824..0828]。
+    rollup 的 active_friends 故意 seed 999——若实现误用 rollup 聚合(跨日
+    SUM/MAX 皆错)会立刻暴露;正确值=窗内 distinct peer(u1: f1+f2)。
+    """
+    monkeypatch.setattr(metrics, "today_key", lambda: _TODAY)
+    week = [20260831, 20260901, 20260902, 20260903, 20260904]
+    prev_week = [20260824, 20260825, 20260826, 20260827, 20260828]
+    async def seed(session):
+        session.add(WechatAccount(wx_id="wx1", user_id="u1", user_name="张三"))
+        session.add(WechatAccount(wx_id="wx2", user_id="u2", user_name="李四"))
+        session.add(Staff(user_id="u1", name="张三"))
+        session.add(Staff(user_id="u2", name="李四"))
+        # rollup:u1 本周 100(5×20),u2 50(5×10);active_* 999=诱饵(不得被采用)
+        for d in week:
+            session.add(StatDailyStaff(day=d, channel="wechat", user_id="u1",
+                                       msg_sent=20, msg_recv=0,
+                                       active_friends=999, active_rooms=999))
+            session.add(StatDailyStaff(day=d, channel="wechat", user_id="u2",
+                                       msg_sent=10, msg_recv=0,
+                                       active_friends=1, active_rooms=0))
+        # u3 仅存在于 rollup(无账号映射/无 staff 行)→ 未映射,名字回退 user_id
+        session.add(StatDailyStaff(day=20260904, channel="wechat", user_id="u3",
+                                   msg_sent=10, msg_recv=0,
+                                   active_friends=0, active_rooms=0))
+        # 上周 rollup:u1 80(5×16) → msg_delta=(100-80)/80=0.25;u2 无前窗→None
+        for d in prev_week:
+            session.add(StatDailyStaff(day=d, channel="wechat", user_id="u1",
+                                       msg_sent=16, msg_recv=0,
+                                       active_friends=1, active_rooms=0))
+        # 活跃指标真源:wx1→u1 两 friend(f1/f2 不同日)+一 room;wx2→u2 一 friend
+        for day, kind, peer, owner in [
+            (20260831, "friend", "f1", "wx1"), (20260904, "friend", "f2", "wx1"),
+            (20260902, "room", "r1", "wx1"), (20260903, "friend", "f1", "wx2"),
+        ]:
+            session.add(MsgDailyStats(channel="wechat", owner_account_id=owner,
+                                      peer_kind=kind, peer_id=peer, day=day,
+                                      send_cnt=1, recv_cnt=0,
+                                      last_ts=1788500000000, last_is_send=True))
+        # 通话:u1 一通落窗(1788500000000=2026-09-04 当日);u2 的在 2025 年不计
+        session.add(PhoneCall(call_id="cr1", channel="voice_call", user_id="u1",
+                              start_call_time=1788500000000, call_duration=60))
+        session.add(PhoneCall(call_id="cr2", channel="voice_call", user_id="u2",
+                              start_call_time=1756950000000, call_duration=60))
+        await session.commit()
+
+        out = await metrics.staff_ranking(session, channel="wechat", scope="week")
+        assert [r["user_id"] for r in out] == ["u1", "u2", "u3"]  # msg_total 降序
+        r1, r2, r3 = out
+        assert r1["name"] == "张三" and r1["unmapped"] is False
+        assert r1["msg_total"] == 100  # rollup 聚合
+        assert r1["active_friends"] == 2  # distinct peer,非 rollup 的 999
+        assert r1["active_rooms"] == 1
+        assert r1["call_cnt"] == 1
+        assert r1["msg_delta"] == 0.25  # (100-80)/80
+        assert r2["msg_total"] == 50 and r2["active_friends"] == 1
+        assert r2["active_rooms"] == 0 and r2["call_cnt"] == 0  # 窗外通话不计
+        assert r2["msg_delta"] is None  # 前窗无数据
+        assert r3["name"] == "u3" and r3["unmapped"] is True
+        assert r3["msg_total"] == 10 and r3["active_friends"] == 0
+
+    await make_client(seed)
+
+
+async def test_staff_ranking_fallback_when_rollup_empty(make_client, monkeypatch):
+    """stat_daily_staff 空表 → msg_total 回退 msg_daily_stats 聚合(部署即用)。"""
+    monkeypatch.setattr(metrics, "today_key", lambda: _TODAY)
+    async def seed(session):
+        session.add(WechatAccount(wx_id="wx1", user_id="u1", user_name="张三"))
+        session.add(MsgDailyStats(channel="wechat", owner_account_id="wx1",
+                                  peer_kind="friend", peer_id="t1", day=20260904,
+                                  send_cnt=10, recv_cnt=5, last_ts=1788500000000,
+                                  last_is_send=True))
+        # wx9 无账号行 → 映射不上按 owner 原值计入并标未映射
+        session.add(MsgDailyStats(channel="wechat", owner_account_id="wx9",
+                                  peer_kind="friend", peer_id="t2", day=20260904,
+                                  send_cnt=2, recv_cnt=0, last_ts=1788500000000,
+                                  last_is_send=True))
+        await session.commit()
+        out = await metrics.staff_ranking(session, channel="wechat", scope="today")
+        assert [r["user_id"] for r in out] == ["u1", "wx9"]
+        assert out[0]["msg_total"] == 15 and out[0]["active_friends"] == 1
+        assert out[0]["unmapped"] is False
+        assert out[0]["msg_delta"] is None  # 今日 scope 无环比
+        assert out[1]["msg_total"] == 2 and out[1]["unmapped"] is True
+        assert out[1]["name"] == "wx9"
+
+    await make_client(seed)
+
+
+async def test_action_counts(make_client, monkeypatch):
+    """预警行动入口:unreplied 走真实路径,churn/sensitive 各计 pending/真流失。"""
+    monkeypatch.setattr(metrics, "_now_ms", lambda: 1756950000000)
+    async def seed(session):
+        now = 1756950000000
+        h3 = 3 * 3600 * 1000
+        # 该回未回 1 条:客户尾向 3h 前 + 有效 text 消息
+        session.add(MsgDailyStats(channel="wechat", owner_account_id="wx1",
+                                  peer_kind="friend", peer_id="t1", day=20260904,
+                                  send_cnt=5, recv_cnt=3, last_ts=now - h3,
+                                  last_is_send=False))
+        session.add(Message(msg_id="t1m", channel="wechat", owner_account_id="wx1",
+                            talker_id="t1", timestamp=now - h3, is_send=False,
+                            type="text", text="在吗,方案发我一下",
+                            fetched_at=dt.datetime(2026, 9, 4, 12, 0)))
+        # 真流失 1 条:沉默 45 天 + 历史 ≥5
+        day_ms = 86_400_000
+        session.add(Customer(friend_id="c_real", channel="wechat",
+                             owner_account_id="wx1", user_id="u1",
+                             last_chat_time=now - 45 * day_ms, delete_flag=0))
+        session.add(MsgDailyStats(channel="wechat", owner_account_id="wx1",
+                                  peer_kind="friend", peer_id="c_real", day=20260601,
+                                  send_cnt=6, recv_cnt=0, last_ts=now - 50 * day_ms,
+                                  last_is_send=True))
+        # 敏感词:1 pending + 1 confirmed(只计 pending)
+        w = SensitiveWord(word="测试词")
+        session.add(w)
+        await session.flush()
+        session.add(SensitiveHit(word_id=w.id, msg_id="m1", channel="wechat",
+                                 disposition="pending"))
+        session.add(SensitiveHit(word_id=w.id, msg_id="m2", channel="wechat",
+                                 disposition="confirmed"))
+        await session.commit()
+
+        out = await metrics.action_counts(session, channel="wechat")
+        assert out == {"unreplied_2h": 1, "churn_real_30d": 1,
+                       "sensitive_pending": 1}
+
+    await make_client(seed)

yunkes/src/api/analytics.ts

@@ -19,6 +19,14 @@ export interface OverviewCards {
 export interface TrendPoint { day: number; msg: number; active_customers: number; call_cnt: number }
 export interface AnomalyStaff { user_id: string; yesterday: number; prev7_mean: number; new?: boolean }
 export interface Anomaly { total_delta_pct: number; yesterday_total: number; prev7_mean: number; staff: AnomalyStaff[] }
+// 员工活跃排行(2026-09-07 管理者反馈补强):active_*=窗内 distinct peer,
+// msg_delta 仅周/月且当前/前窗均非 0 才有值
+export interface StaffRankingRow {
+  user_id: string; name: string; unmapped: boolean
+  msg_total: number; active_friends: number; active_rooms: number
+  call_cnt: number; msg_delta: number | null
+}
+export interface ActionCounts { unreplied_2h: number; churn_real_30d: number; sensitive_pending: number }
 export interface OverviewResp {
   scope: Scope
   channel: Channel
@@ -26,6 +34,8 @@ export interface OverviewResp {
   cards: OverviewCards
   trend: TrendPoint[]
   anomaly: Anomaly | null
+  staff_ranking: StaffRankingRow[]
+  actions: ActionCounts
 }
 export interface HealthResp { data_as_of: number | null; entities: { table: string; last_seen: string | null }[] }
 export interface ChurnRow {

yunkes/src/views/analytics/DashboardView.vue

@@ -13,6 +13,20 @@
       <span v-if="asOfText" class="as-of">数据截至 {{ asOfText }}</span>
     </div>
 
+    <!-- 预警行动入口:三卡直达处置页(2026-09-07 管理者反馈「纯汇总数字看不到
+         行动入口」);计数随 channel 切换自然跟随 overview 载荷,0 灰显仍可点 -->
+    <div class="action-row">
+      <el-card
+        v-for="a in actionCards" :key="a.to" shadow="never"
+        class="action-card" :class="{ zero: a.count === 0 }"
+        @click="router.push(a.to)"
+      >
+        <span class="action-icon">{{ a.icon }}</span>
+        <span class="action-label">{{ a.label }}</span>
+        <span class="action-count">{{ a.count }}</span>
+      </el-card>
+    </div>
+
     <el-alert v-if="error" type="error" :title="error" :closable="false" class="anomaly" />
 
     <el-alert v-if="anomalyView" type="warning" :closable="false" class="anomaly">
@@ -49,19 +63,62 @@
       </template>
       <div ref="chartEl" class="trend-chart"></div>
     </el-card>
+
+    <!-- 员工活跃排行:全行展示(~41 人,420px 内滚),按消息量降序(后端排好) -->
+    <el-card v-loading="loading" shadow="never" class="rank-card">
+      <template #header>
+        <span>员工活跃排行</span>
+        <span class="rank-scope">按所选时间范围</span>
+      </template>
+      <el-table :data="data?.staff_ranking ?? []" max-height="420" size="small">
+        <el-table-column type="index" label="#" width="48" />
+        <el-table-column label="员工" min-width="160">
+          <template #default="{ row }">
+            {{ row.name }}
+            <el-tag v-if="row.unmapped" size="small" type="info" class="unmapped-tag">未映射</el-tag>
+          </template>
+        </el-table-column>
+        <el-table-column label="消息量" align="right">
+          <template #default="{ row }">{{ fmt(row.msg_total) }}</template>
+        </el-table-column>
+        <el-table-column label="活跃客户" align="right">
+          <template #default="{ row }">{{ fmt(row.active_friends) }}</template>
+        </el-table-column>
+        <el-table-column label="活跃群" align="right">
+          <template #default="{ row }">{{ fmt(row.active_rooms) }}</template>
+        </el-table-column>
+        <el-table-column label="通话量" align="right">
+          <template #default="{ row }">{{ fmt(row.call_cnt) }}</template>
+        </el-table-column>
+        <el-table-column label="环比" align="right" width="90">
+          <template #default="{ row }">
+            <span
+              v-if="row.msg_delta !== null"
+              class="rank-delta"
+              :class="{ down: row.msg_delta < 0 }"
+            >{{ (row.msg_delta * 100).toFixed(1) }}%</span>
+            <span v-else>-</span>
+          </template>
+        </el-table-column>
+      </el-table>
+    </el-card>
   </div>
 </template>
 
 <script setup lang="ts">
-// A1 数据看板:筛选栏(渠道×时间范围) → 异常警示条 → 五卡片 → 30 日趋势折线。
+// A1 数据看板:筛选栏(渠道×时间范围) → 预警行动入口 → 异常警示条 → 五卡片
+// → 30 日趋势折线 → 员工活跃排行表。
 // 数据来自 /analytics/overview + /analytics/health(数据截至角标)。
 import { computed, onMounted, ref, watch } from 'vue'
+import { useRouter } from 'vue-router'
 import {
   getAnalyticsHealth, getOverview, type AnomalyStaff, type Channel, type OverviewResp, type Scope,
 } from '@/api/analytics'
 import { useChart } from '@/composables/useChart'
 import { formatTimeShort } from '@/utils/format'
 
+const router = useRouter()
+
 interface CardItem {
   label: string
   value: string
@@ -151,6 +208,16 @@ const anomalyView = computed<AnomalyView | null>(() => {
 
 const fmt = (n: number | undefined | null) => (n ?? 0).toLocaleString()
 
+// 预警行动入口:计数来自 overview 载荷 actions(0 灰显仍可点,直达处置页)
+const actionCards = computed(() => {
+  const a = data.value?.actions
+  return [
+    { icon: '🔴', label: '该回未回 2h', count: a?.unreplied_2h ?? 0, to: '/analytics/unreplied' },
+    { icon: '🟡', label: '流失预警 30天+', count: a?.churn_real_30d ?? 0, to: '/analytics/churn' },
+    { icon: '⚠', label: '敏感词待处置', count: a?.sensitive_pending ?? 0, to: '/analytics/sensitive' },
+  ]
+})
+
 const cardList = computed<CardItem[]>(() => {
   const c = data.value?.cards
   if (!c) return []
@@ -260,4 +327,48 @@ onMounted(() => {
 .trend-chart {
   height: 320px;
 }
+.action-row {
+  display: grid;
+  grid-template-columns: repeat(auto-fit, minmax(200px, 1fr));
+  gap: 12px;
+  margin-bottom: 16px;
+}
+.action-card {
+  cursor: pointer;
+}
+.action-card.zero {
+  opacity: 0.55;
+}
+.action-card :deep(.el-card__body) {
+  display: flex;
+  align-items: center;
+  gap: 8px;
+  padding: 10px 14px;
+}
+.action-label {
+  font-size: 13px;
+  color: var(--el-text-color-primary);
+}
+.action-count {
+  margin-left: auto;
+  font-size: 22px;
+  font-weight: 600;
+}
+.rank-card {
+  margin-top: 16px;
+}
+.rank-scope {
+  margin-left: 8px;
+  font-size: 12px;
+  color: var(--el-text-color-secondary);
+}
+.unmapped-tag {
+  margin-left: 6px;
+}
+.rank-delta {
+  color: var(--el-color-success);
+}
+.rank-delta.down {
+  color: var(--el-color-danger);
+}
 </style>