重构智脑实施方法论：引入FDE模式，八步工作法，适配中国连锁经营企业国情

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+# 07 · 步骤六：AI协同后端API构建与验证
+
+> 目标：AI参与API开发，逐个验证——快速交付能用的代码，不追求完美架构。 `[Delta主导，AI为主]`
+
+## 1. 指标分层设计
+
+```
+L0: 原始数据层 (bill_records, salary_detail_records, attendance_records)
+       ↓
+L1: 预聚合层 (物化视图 mv_*)
+       ↓
+L2: API层 (后端路由，SQL查询 + 业务逻辑)
+       ↓
+L3: 展示层 (前端页面，图表 + 表格)
+```
+
+## 2. 页面与API总览
+
+| 页面 | 文件 | 调用的 API |
+|------|------|-----------|
+| 总部驾驶舱 | DashboardPage.tsx | /overview, /overview/daily, /stores/risk, /stores/priority, /tasks/loop-health, /stores/quadrant, /platform/economics, /situational-awareness/alerts, /store-expense/overview, /overview/yoy, /overview/mom, /overview/trend, /overview/profit-trend |
+| 老板驾驶舱 | BossPage.tsx | /overview, /overview/daily, /store-expense/overview, /overview/profit-waterfall, /stores/risk, /stores/priority, /cost-analysis/store-overview, /store-expense/expense-structure, /overview/store-profit-ranking, /overview/profit-opportunity |
+| 门店工作台 | StorePage.tsx | /stores/risk, /stores/priority, /tasks/stores/:code/daily-card, /tasks, /stores/:code/daily, /tasks/followup, /sku/attach, /sku/abc, /stores/:code, /situational-awareness/health-score, /stores/:code/meal-period, /stores/:code/category-mix, /stores/:code/cost, /stores/:code/member, /stores/:code/anomalies, /stores/:code/staffing |
+| 成本分析 | CostPage.tsx | /cost/comparison, /cost/inventory, /cost/category-benchmark |
+| 成本分析(Tab) | cost-analysis/*.tsx | /cost-analysis/overview, /category-comparison, /margin-deviation, /variance-top, /menu-engineering, /profitability, /pricing, /store-overview, /store-ranking, /bom-*, /packaging-*, /material-*, /data-quality, /unmatched-* |
+| 费用分析(Tab) | store-expense/*.tsx | /store-expense/overview, /expense-structure, /store-ranking, /store-contribution, /break-even, /loss-diagnosis, /delivery-commission, /rent-risk, /fixed-variable, /efficiency, /store-evaluation |
+| 风险监控 | RiskPage.tsx | /risk/anomaly, /risk/zero-received, /risk/cashier |
+| 态势感知 | SituationalAwarenessPage.tsx | /situational-awareness/health-score, /alerts, /correlation, /forecast |
+| 会员复购 | MemberPage.tsx | /member/comparison, /member/repeat |
+| SKU分析 | SKUPage.tsx | /sku/abc, /sku/category |
+| 菜单工程 | MenuEngineeringPage.tsx | /analytics-enhanced/menu-engineering/actions |
+| 产品生命周期 | ProductLifecyclePage.tsx | /product/products, /product/reviews/overview, /product/reviews |
+| BOM穿透 | BomPenetrationPage.tsx | /central-kitchen/bom-penetration |
+| 分销对账 | DistributionReconciliationPage.tsx | /distribution/reconciliation |
+| 生产计划 | ProductionPlanPage.tsx | /sales-driven/production-plan |
+| 任务闭环 | TasksPage.tsx | /tasks |
+| 数据导入 | DataImportPage.tsx | /product/import-logs, /product/quality-rules |
+| 本体浏览 | OntologyPage.tsx | /tasks/ontology/* |
+
+> 详细的逐页面→API→SQL→数据源字段映射，见 [08-数据溯源与API全量清单.md](08-数据溯源与API全量清单.md)
+
+## 3. 后端API规范
+
+### 3.1 路由组织
+
+```
+server/src/routes/
+├── data.ts              # 核心数据API（概览、门店、风险明细等）
+├── situational-awareness.ts  # 态势感知（健康度、预警、关联分析）
+├── smart-scheduling.ts  # 智能排班
+├── cost-analysis.ts     # 成本分析
+├── store-expense.ts     # 门店费用
+├── analytics-enhanced.ts # 增强分析
+├── admin.ts             # 管理
+└── tts.ts               # 语音
+```
+
+### 2.2 通用模式
+
+```typescript
+// 月份参数解析
+const month = parseMonth(req)  // 从 query 参数获取，默认 '2026-04'
+
+// 分页
+const { page, pageSize, offset } = parsePagination(req)
+
+// 数据权限
+const scope = getDataScope(req)  // 返回 store_names 数组或 null（全部）
+
+// 响应格式
+sendSuccess(res, data, meta?)   // { success: true, data, meta }
+sendError(res, message)         // { success: false, error: message }
+```
+
+### 2.3 SQL查询模式
+
+**安全参数化**：
+```typescript
+// 正确：参数化查询
+const result = await query(`SELECT * FROM mv_risk_anomaly WHERE month = to_char($1::date, 'YYYY-MM')`, [month])
+
+// 错误：字符串拼接
+const result = await query(`SELECT * FROM mv_risk_anomaly WHERE month = '${month}'`)
+```
+
+**动态条件构建**：
+```typescript
+const conditions: string[] = [`month = to_char($1::date, 'YYYY-MM')`]
+const params: any[] = [month]
+let paramIdx = 2
+if (storeName) {
+  conditions.push(`store_name = $${paramIdx}`)
+  params.push(storeName)
+  paramIdx++
+}
+const whereClause = conditions.join(' AND ')
+```
+
+**聚合汇总+分页**：
+```typescript
+// 先查总数和汇总
+const countResult = await query(`SELECT count(*) AS total, sum(consumption) AS sum_consumption FROM mv_risk_anomaly WHERE ${whereClause}`, params)
+// 再查明细
+const result = await query(`SELECT * FROM mv_risk_anomaly WHERE ${whereClause} ORDER BY ${sortCol} ${order} LIMIT $${paramIdx} OFFSET $${paramIdx + 1}`, [...params, pageSize, offset])
+```
+
+## 3. 常见SQL陷阱与修复
+
+### 3.1 Schema前缀错误
+
+**症状**：`relation "analytics.mv_channel_daily" does not exist`
+
+**排查**：
+```sql
+SELECT schemaname, matviewname FROM pg_matviews WHERE matviewname LIKE '%channel%';
+```
+
+**修复**：确认实际schema，移除或修正前缀
+```typescript
+// 错误：FROM analytics.mv_channel_daily
+// 正确：FROM mv_channel_daily  (实际在public schema)
+```
+
+### 3.2 列名不存在
+
+**症状**：`column "risk_score" does not exist`
+
+**排查**：
+```sql
+SELECT column_name FROM information_schema.columns WHERE table_name = 'mv_store_risk_rating_monthly';
+```
+
+**修复策略**：
+- 策略A：改用 `SELECT *`（当不需要特定列名时）
+- 策略B：用 `0 AS column_name` 替代不存在的列（当前端期望该字段时）
+- 策略C：修正为正确的列名
+
+### 3.3 日期格式不匹配
+
+**症状**：薪资相关查询返回0条
+
+**排查**：
+```sql
+SELECT DISTINCT salary_period FROM salary_detail_records ORDER BY 1 DESC LIMIT 5;
+-- 结果：2026年4月（非2026-04）
+```
+
+**修复**：
+```typescript
+// 错误：s.salary_month = to_char($1::date, 'YYYY-MM')
+// 正确：s.salary_period = to_char($1::date, 'YYYY"年"FMMM"月"')
+```
+
+### 3.4 物化视图stale
+
+**症状**：API返回数据与直接查原始表不一致
+
+**排查**：对比物化视图和原始表的count
+```sql
+SELECT count(*) FROM mv_risk_anomaly WHERE month = '2026-04';
+SELECT count(*) FROM bill_records WHERE to_char(c176::timestamp, 'YYYY-MM') = '2026-04' AND ...;
+```
+
+**修复**：重建物化视图
+```sql
+DROP MATERIALIZED VIEW mv_risk_anomaly;
+CREATE MATERIALIZED VIEW mv_risk_anomaly AS ...;
+CREATE INDEX idx_mv_risk_anomaly_month ON mv_risk_anomaly(month);
+```
+
+## 4. 考勤打卡数据解析
+
+### 4.1 department路径解析门店名
+
+```
+北京西部马华餐饮有限公司/西部马华品牌门店/胡庆鹏区/HQP2区/双安店/前厅/服务组
+```
+
+**提取逻辑**（从后往前找以"店"结尾的层级）：
+```typescript
+function extractStore(dept: string): string {
+  const parts = dept.split('/')
+  for (let i = parts.length - 1; i >= 0; i--) {
+    if (parts[i].endsWith('店')) return parts[i]
+  }
+  return ''
+}
+```
+
+### 4.2 打卡时间解析
+
+格式：`08:43(考勤机：指纹)\n21:23(考勤机：指纹)`
+
+```typescript
+function parseClockTimes(raw: string): { start: number; end: number } | null {
+  const times = raw.match(/(\d{1,2}):(\d{2})/g)
+  if (!times || times.length < 2) return null
+  const startHour = parseInt(times[0].match(/(\d{1,2}):/)[1])
+  let endHour = parseInt(times[times.length - 1].match(/(\d{1,2}):/)[1])
+  if (endHour < startHour) endHour = 23  // 跨天
+  return { start: startHour, end: endHour }
+}
+```
+
+### 4.3 日均在岗人数估算
+
+```typescript
+// 每个员工每天打卡算1人在岗，按小时累计
+// 月度汇总后除以30天得到日均同时在岗人数
+staffSummary[store][hour] = Math.round(totalPersonHours[store][hour] / 30)
+```
+
+**关键点**：客流数据 `mv_bill_hourly.bills` 也是月度汇总，展示时需除以30天对齐。