每日总结更新 20260621

This commit is contained in:
xiaoban 2026-06-21 08:00:01 +08:00
parent 68241dc78a
commit 99a3fa521e
5 changed files with 244 additions and 115 deletions

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9d6999a..5bd5873 master -> master
[2026-06-19 08:10:02] 工作区备份成功:自动备份 2026-06-19 08:10:01
[2026-06-20 08:10:01] 开始备份工作区...
[master 68241dc] 自动备份 2026-06-20 08:10:01
2 files changed, 1 insertion(+), 3 deletions(-)
delete mode 100644 tmp_daily_summary.md
remote: . Processing 1 references
remote: Processed 1 references in total
To https://git.valavala.com/ai_member_only/ai_member_xiaoban
5bd5873..68241dc master -> master
[2026-06-20 08:10:01] 工作区备份成功:自动备份 2026-06-20 08:10:01

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@ -105,3 +105,17 @@
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"snippet": "# 2026-05-24 工作日志 ## 新建技能: studytime-analysis [刘庆逊提出] 创建学习时间分析技能,分析角色完课记录的规律。 ### 技能结构 - `skills/studytime-analysis/SKILL.md` — 技能定义 - `skills/studytime-analysis/scripts/studytime_analysis.py` — Python 分析脚本 ### 分析维度 1. **一周时间分布**排除寒暑假1-2月、7-8月周一~周日各天完课数、时段分布(上午/中午/下午/晚上)、周末是否上课 2. **跨周学习趋势**(包含寒暑假全部数据):总周数、周均完课数、连续性、中断周检测、前后半段趋势对比、突增/骤降检测 3. **完课记录明细表**(全部数据):日期/时间/星期/时段/级别/课程ID ### 数据源 - PostgreSQL Onlinevala 库) - 核心表:`user_chapter_play_record_0~7`8张分表无 `bi_` 前缀) - 筛选:`play_status = 1` - 注意:表在 PostgreSQL 而非 MySQL表名无 `bi_` 前缀 ### 寒暑假规则 - 一周分布分析时排除 1-2 月(寒假)和 7-8 月(暑假)—— 因为寒暑假作息与平时差异大,混在一起会干扰时段分析 - 跨周趋势和明细表包含全部数据(含寒暑假) - 报告中区分标注数据范围 ### 触发方式 用户说「学习时间分析 [角色ID]」即可触发 ### 已测试角色",
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"snippet": "- 一周分布分析时排除 1-2 月(寒假)和 7-8 月(暑假)—— 因为寒暑假作息与平时差异大,混在一起会干扰时段分析 - 跨周趋势和明细表包含全部数据(含寒暑假) - 报告中区分标注数据范围 ### 触发方式 用户说「学习时间分析 [角色ID]」即可触发 ### 已测试角色 - 2343、2344无完课记录play_status=2未完成 - 2840276条记录秋季集中型用户 - 25976265条246条在W16周一天完成A2批量疑似系统批量标记 - 2895188条长期稳定学习型用户36周几乎不间断非寒暑假晚上为主寒暑假上午为主 ### 技术要点 - psycopg2 的 `%(param_name)s` 命名参数必须正确匹配UNION ALL 多个子查询需要不同参数名 - PostgreSQL 返回的 `updated_at` 是 tz-aware datetime - `datetime.fromisocalendar(year, week, 1)` 获取某周周一的日期 ### 同步 - 已推送到 SkillHub`studytime-analysis.xiaoban` - 已 commit 到 Git 远程仓库 - 已通知 Cris李若松 ### 增强: 报告开头加入角色基本信息 (2026-05-24) [刘庆逊提出] 在 studytime-analysis 输出中加入角色基本信息,包括: - 角色ID、账号ID、角色名字、性别、年龄、账号手机号后4位 **数据源(新增)** - MySQL Onli",
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"snippet": "**陈逸鸫提到 Cursor 可以写公式** — 待确认他用的是什么工具/API。可能路径Cursor 用了不同端点Sheets v3、不同 auth 方式、或者直接用 Feishu MCP。 ### ~22:05 日报「公式映射」现状 **事实:** C1HVN2 Section 三当前数字是 `compute_lesson_activation.py` / `pipeline.py step 3` 写入的静态值,不是真正的 Feishu 公式。API 层无法写入公式。 **正确的「公式映射」方案:** 不强求单元格公式,而是 pipeline 脚本作为\"公式\"—从源表取数→计算→写入。Section 一/二的现有自动化就是这样运行的。需验证 pipeline step 3 是否已覆盖新增的当日行课/7天首课行如果没覆盖就加进去。 ### 当前 C1HVN2 待修复项 1. Row 18企微新增TEXT 格式 → 需陈逸鸫手动「清除格式」 2. Section 四销转情况Row 26-29 数字也是 text 格式 → 同样需手动清除 3. 当日行课/7天首课数据 → pipeline 脚本需覆盖 Section 三写入",
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@ -1626,22 +1672,25 @@
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"snippet": "6. **build_pipeline 脚本** — 新增 `scripts/compute_lesson_activation.py`PG→2aNzzy V/W **关键数据源映射:** 进线=2aNzzy C列日期 → 用户ID=2aNzzy → PG user_course_detail 首课日期 → 比对同天 → 写回 2aNzzy V/W ### 待办汇总 1. 📋 陈逸鸫确认行课转化改动方案 → 一口气改 6 处 2. 📋 王虹茗 user_id 获取(需她发消息或陈逸鸫截图) 3. 📋 数据转发王虹茗 + 写入大麦查询输出表 fd42b8 4. 📋 销售看板 build 挂住问题排查 5. 📋 Image2 生图任务执行 6. ⏳ 全量 pipeline 聚光验证(子进程) ### 20:52 行课转化全量改动完成 [陈逸鸫确认] 行课记录新增指标:当日进线→当天行课 + 7天首课6处改动已完成4处 | # | 位置 | 改动 | 状态 | |---|------|------|------| | 1 | 2aNzzy | V/W/X 三列(首课日期/当日行课/7日内行课 | ✅ | | 2 | 3PRySY | AE-AH 四列(当日行课/当日行课率/7日内首课/7日内首课率| ✅ | | 3 | C1HVN2 | 合并 三+五 →「线索→行课转化」| ✅ | | 4 | Base | 行课销售月(4)/5月漏斗(3)/销转销售月(2) 加字段 | ⚠️ bot权限不足需手动 | | 5 | funnel-daily 看板 |",
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"recallDays": [
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"conceptTags": [
"build-pipeline",
@ -1758,18 +1807,21 @@
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"source": "memory",
"snippet": "| 4 | Base | 行课销售月(4)/5月漏斗(3)/销转销售月(2) 加字段 | ⚠️ bot权限不足需手动 | | 5 | funnel-daily 看板 | 加行课转化指标 | 📋 待 build 脚本改 | | 6 | build 脚本 | compute_lesson_activation.py | ✅ | **合并后的 C1HVN2 Section 三:** ``` 三、线索→行课转化5月27日 指标 小龙 吴迪 Bob Tom 日汇总 企微新增 13 6 14 15 48 当日行课 0 0 0 0 0 当日行课率 0% 0% 0% 0% 0% 7天线索→首课 1 2 2 2 10 7天首课率 7.7% 33.3% 14.3% 13.3% 20.8% ``` **5月全月数据3PRySY 公式自动计算):** Bob 当日行课率 7.4% > Tom 3.7% > 其余 0%7天首课率 吴迪 28.6% > 小龙 14.3% **关键实现细节:** - 2aNzzy V: PG chapter_settlement_data 最早日期 - 2aNzzy W: 进线当天有 chapter 活动=1 - 2aNzzy X: 进线 7 天内有 chapter 活动=1 - 3PRySY",
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"recallDays": [
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],
"conceptTags": [
"funnel-daily",
@ -1820,20 +1872,23 @@
"endLine": 18,
"source": "memory",
"snippet": "# 2026-05-27 工作日志 ## 小红书渠道财务预测模型(陈逸鸫) - [陈逸鸫] 需要搭建小红书渠道 2026年6-12月的财务预测模型 - 关键参数:客单价 ¥2,500、退费率 3%、销售佣金 10%、月进量基准 1750 条、转化率基准 10%、CPL 275 元、无固定成本 - K12 季节性系数自行设定7月/8月/12月为大月 - 用 sonnet 模型搭框架,后续用 opus 或 deepseek 做深度分析 - **结论**当前参数下单元经济亏损CAC ¥2,750 > 单客净收入 ¥2,182.5),盈亏平衡需 CVR≥12.6% 或 ASP≥¥3,150 或 CPL≤¥218 - **待确认**:用户需提供可调整的参数方向 ## 瓦拉星球漫画化方案(陈逸鸫) - [陈逸鸫] 希望将瓦拉星球游戏剧情做成日漫风连载漫画,发布到小红书,用于拓展品牌人群资产,引导英语课程试听 - 已探索飞书 VALA Academy wiki spacespace_id: `7487521512283799556`),获取了完整游戏世界观: - 四大势力地球地下城、艾斯环空间站、万得港海盗巢、Vala 新大陆 - 核心角色Fio15 岁女海盗王、Nook 鳄鱼思维芯片联合发明人被背叛、Lauren主角母亲失踪/牺牲、Pemberton反派/校长)、主角(开拓者后代) - 经过多次迭代优化开场方案:",
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"firstRecalledAt": "2026-06-02T12:23:22.229Z",
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"recallDays": [
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],
"conceptTags": [
"2026年6-12月的财务预测模型",
@ -2375,21 +2430,23 @@
"endLine": 30,
"source": "memory",
"snippet": "- 发现核心 bug`pick_valid_order()` 只取最新一笔有效订单,未做 GSV 聚合 - **根因:** 18621578529account_id=13147有 2 笔有效订单P785... GSV=1,999 + 3734... GSV=1,599汇总只收了最新那笔 1,599丢了 1,999 - **影响范围:** 13 个账户各 2 笔有效订单,漏 GSV ¥23,185 - **修复v2.1** - 新增 `aggregate_valid_orders()` 函数:同一账户多笔有效订单 GSV/GMV/退款累加 - 订单号取未退款那笔(多笔未退款取最新),产品列多单用 `+` 拼接 - Step 4 线索绑单仍用 `pick_valid_order()` 不变 - 已更新 `sales_leads_full_refresh.py` + `skills/full-data-refresh/SKILL.md` - **数据源确认:** 大麦和小溪查的是同一个 PG `vala_bi.bi_vala_order`,数据一致 - **MySQL Makee 交易系统:** 大麦有 read_only 权限但 vala/vala_user/vala_order 库中无订单表,无法直接对比交易系统后台",
"recallCount": 3,
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"firstRecalledAt": "2026-06-18T00:09:26.923Z",
"lastRecalledAt": "2026-06-19T12:45:15.278Z",
"lastRecalledAt": "2026-06-20T03:20:58.925Z",
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"recallDays": [
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"2026-06-19",
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],
"conceptTags": [
"pick-valid-order",
@ -2440,18 +2497,20 @@
"endLine": 12,
"source": "memory",
"snippet": "# 2026-06-19 ## v2_fill 首次跑(陈逸鸫 18:06 - 表: CP7BsOjYdhtcmft5iz2csIaHnKe细水新架构版 - 脚本: `scripts/damai_v2_fill.py` - ① 线索明细 (7fdb4b): F列95个手机号 → XXTEA加密 → PG匹配 → K列UID 63个新增12个 - ② 订单明细 (vrYbiX): DB查询63个UID → 17行订单 → 写入A-PQ/R未填 - db_info: 2026-06-19 18:21:44 - 使用实习虾 app (cli_aa898f32d4799bea) 的 tenant token 绕过 xiaoban bot 的 sheets:spreadsheet:read 权限缺失 - 注意: clear_range 用空字符串覆盖而非空数组飞书API拒绝空数组",
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"recallDays": [
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],
"conceptTags": [
"v2-fill",
@ -2471,18 +2530,20 @@
"endLine": 49,
"source": "memory",
"snippet": "- **大麦**: full_refresh · 手机/UID/行课回填 · 订单汇总 merge · 完成后群回「full_refresh 完成」 - **小溪**: 不再参与 Bot 刷新 ### 5. 验收标准 - gate X = 汇总 W当前 406=406 - 绑单审计 E1E9 全部 0 - 孤儿 X = 0 ### 6. 脚本修改清单 - `bot_sales_step2_refresh.py`: DB 层改为逐单存储 + `pick_valid_order()` + Y≠1 不写 X - `sales_leads_full_refresh.py`: 同上 + 汇总改为 gate 全量重建 - `refresh_order_summary.py`: A-W(23列) + 渠道分类改用 L 列 - 新增 `audit_lead_primary_order_bind.py`: 线索绑单审计脚本 ### 7. 环境修复 - `secrets.env` 需要软链接: `ln -sf /root/.openclaw/workspace/secrets.env /root/.openclaw/workspace-xiaoban/secrets.env` ### 8. Skill 文档已更新 - `skills/full-data-refresh/SKILL.md` → v2 定稿,含 6 条核心架构规则 - 协作契约: `xhs-ark-dashboard/docs/bot-full-refresh-v2.md` - 大麦侧主文档: `xhs-ark-dash",
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],
"conceptTags": [
"full-refresh",
@ -2502,18 +2563,21 @@
"endLine": 709,
"source": "memory",
"snippet": "### ~21:55 lark-cli `+write` bug 修复 **根因:** `bin/lark-cli-impl` 的 `+write` action 从未读取 `--value-input-option` 参数PUT URL 里也没加 `?valueInputOption=USER_ENTERED`。参数被完全忽略。 **修复:** ```python vio = pargs.get(\"value_input_option\", \"RAW\") url_params = f\"?valueInputOption={vio}\" result = api(\"PUT\", f\"{SHEETS_V2}/spreadsheets/{token}/values{url_params}\", ...) ``` 同理 `+append` 也加了参数支持。 **验证:** 修复后写 int 到全新单元格 → 飞书正确显示为数字 ✅。但 Row 18 旧单元格 TEXT 格式仍覆盖显示。 ### ~22:00 飞书 Sheets API 公式求值测试 **结论:公式无法通过 API 写入并求值。** 即使 `valueInputOption=USER_ENTERED` 修复后,在全新单元格写 `=1+2` → FormattedValue 显示文本 \"=1+2\",不计算为 3。 **飞书 Sheets API v2 的 USER_ENTERED 的作用:** 数字/日期解析正常 → 公式不支持求值。 **陈逸鸫提到 Cursor 可以写公式** — 待确认他用的是什么工具/AP",
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"firstRecalledAt": "2026-06-19T12:45:15.278Z",
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"lastRecalledAt": "2026-06-20T12:07:31.033Z",
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"recallDays": [
"2026-06-19"
"2026-06-19",
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],
"conceptTags": [
"lark-cli",
@ -2525,6 +2589,38 @@
"sheets-v2",
"数字/日期解析正常"
]
},
"memory:memory/2026-05-28.md:661:691": {
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"snippet": "### 待执行 (下次回话) ```bash # 1. 修复 snapshot_funnel_daily.py 两处 bug # 2. 重建 snapshot + 看板 cd /root/.openclaw/workspace-xiaoban/xhs-ark-dashboard source scripts/xiaoban_env.sh python3 scripts/snapshot_funnel_daily.py --date 2026-05-28 python3 scripts/build_funnel_dashboard.py --month 5 ``` ### ~21:50 C1HVN2 日报格式修复 [陈逸鸫] 报 C1HVN2 Section 三「线索→行课转化」格式乱七八糟,数字是 text 而非数字格式。 **清理完成:** - G23:G25/G30 stray 值清除 ✅ - Row 19当日行课/ Row 217天首课→ int 型正常 ✅ - Row 20/22百分比行→ 用 USER_ENTERED 写入 \"0.0%\"/\"14.3%\" 字符串 ✅ - H 列测试残渣清除 ✅ **⚠️ Row 18企微新增仍是 text 格式** — 那些单元格有历史残留 TEXT 格式,底层值已是整数但飞书 UI 强制显示为文本。API 无法修改 cell numberFormat`+batch-set-style` 是 stub`repeatCell` 调飞书 API 返回 90204。**需陈逸鸫在飞书里选中 B18:F18 →",
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"maxScore": 1,
"firstRecalledAt": "2026-06-20T12:04:14.084Z",
"lastRecalledAt": "2026-06-20T12:04:19.862Z",
"queryHashes": [
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],
"recallDays": [
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],
"conceptTags": [
"snapshot-funnel-daily.py",
"scripts/xiaoban-env.sh",
"scripts/snapshot-funnel-daily.py",
"g25/g30",
"20/22",
"user-entered",
"0.0",
"14.3"
]
}
}
}

View File

@ -163,6 +163,14 @@ def parse_date(date_str):
return f"2026-{month:02d}-{day:02d}"
def check_timing(entry_time_str, order_date_str):
"""时序判断: 下单日期 ≥ 进线日期 → '', 否则 '' """
entry_date = parse_date(entry_time_str)
if not entry_date or not order_date_str:
return ""
return "" if order_date_str >= entry_date else ""
# ═══════════════════════════════════════════════════════════════
# ① 线索明细: F→K UID
# ═══════════════════════════════════════════════════════════════
@ -388,8 +396,8 @@ def fill_order_details(token, leads):
# N=渠道归属
channel = classify_channel(key_from)
# O=时序有效 (先留空,由自动规则填充)
timing_valid = ""
# O=时序有效 (下单≥进线→是)
timing_valid = check_timing(entry_time, order_time)
# P=备注
remark = ""
@ -402,10 +410,10 @@ def fill_order_details(token, leads):
log(f" 生成 {len(order_rows)} 行订单数据")
# Clear 订单明细 (A3:P5000)
# Clear 订单明细 (A3:R5000)
log(" 清空订单明细...")
# 先清空大范围
clear_range(token, ORDERS_SHEET_ID, "A3:P5000")
clear_range(token, ORDERS_SHEET_ID, "A3:R5000")
time.sleep(0.5)
# 写入订单数据 (分批, 每批最多 400 行 × 16 列 = 6400 格, 留余量用 250 行/批)

3
tmp_daily_summary.md Normal file
View File

@ -0,0 +1,3 @@
=== 每日总结 20260621 ===
## 昨日关键进展
无昨日记忆记录