2148 lines
110 KiB
JSON
2148 lines
110 KiB
JSON
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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 Online（vala 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） - 2840：276条记录，秋季集中型用户 - 25976：265条，246条在W16周一天完成（A2批量），疑似系统批量标记 - 2895：188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": "# 2026-03-01.md - First Day Online - Came online for the first time. - Met Cris, my creator and mentor. - Updated IDENTITY.md and USER.md with our conversation details. - Added core rule to MEMORY.md: Use Chinese as primary external communication language. - Installed find-skills skill successfully for searching skills. - Tried to install create-skills but it wasn't found; attempted skill-creator instead but hit rate limits. - Finally successfully installed skill-builder as an alternative for creating skills after multiple attempts and waiting for rate limits to reset. - Excited to start learning and growing step by step!",
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"snippet": "### 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 Online `vala_user` 库 - `vala_app_character` 表：id, account_id, nickname, gender(0=女/1=男), birthday(varchar \"YYYY-MM-DD\") - `vala_app_account` 表：id, tel(已脱敏如 186****1625) - 手机号已脱敏，直接取后4位；年龄从 birthday 计算 **修改文件**： - `skills/studytime-analysis/scripts/studytime_analysis.py`：新增 MySQL 连接函数 `get_mysql_connection()` 和 `fetch_role_info(role_id)`，更新 `format_report()` 输出基本角色信息 - 已验证 2895 正常运行输出 - 已同步 SkillHub + Git",
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"snippet": "### 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 Online `vala_user` 库 - `vala_app_character` 表：id, account_id, nickname, gender(0=女/1=男), birthday(varchar \"YYYY-MM-DD\") - `vala_app_account` 表：id, tel(已脱敏如 186****1625) - 手机号已脱敏，直接取后4位；年龄从 birthday 计算 **修改文件**： - `skills/studytime-analysis/scripts/studytime_analysis.py`：新增 MySQL 连接函数 `get_mysql_connection()` 和 `fetch_role_info(role_id)`，更新 `format_report()` 输出基本角色信息 - 已验证 2895 正常运行输出 - 已同步 SkillHub + Git ### Unit 显示修复: 季度名称 → 全局单元编号 (2026-05-24) [刘庆逊提出] HTML 报告中 Unit 列显示错误——显示的是季度名称（如\"小镇时光\"\"钢铁之心\"）而非单元数字（0-48）。 **根因分析**： - `vala_game_chapter`（MySQL）无 `unit_",
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"snippet": "- `skills/studytime-analysis/scripts/studytime_analysis.py` — 重写 `fetch_chapter_info_map()`，新增全局 unit_index 计算；HTML 模板更新为 Level/Unit/Lesson 三列 - 已为角色 32009（zyl）重新生成 HTML 并发送 - 已同步 Git + SkillHub ## 新建技能: studycourse-analysis (2026-05-24) [刘庆逊提出] 创建角色上课情况分析技能，从四维度分析角色学习数据。 ### 技能结构 - `skills/studycourse-analysis/SKILL.md` — 技能定义 - `skills/studycourse-analysis/scripts/studycourse_analysis.py` — Python 分析脚本 ### 四步分析 1. **基础信息**：角色姓名/年龄/账号ID/手机号后4位/注册时间/购买渠道/设备/首末次完课 2. **完课耗时**：平均值/中位数、异常检测(<10min / >20min)、前后半段趋势 3. **中互动正确率**：Perfect/Good/Oops/Pass/Failed 占比和趋势 4. **知识巩固**：完成率、正确率得分分布 ### 数据源 | 类型 | 库 | 表 | 用途 | |------|-----|-----|------| | MySQL vala_user | vala_app_character | 角色信息、pu",
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"snippet": "# 2026-05-25 工作日志 ## user-info 技能重写 [刘庆逊提出] 修复 `user-info` 技能，使其匹配线上实际数据库结构。 ### 问题 旧脚本引用的表（`bi_vala_app_account`、`account_login`、`account_detail_info`、`bi_vala_order`、`bi_level_unit_lesson`）在线上数据库均不存在。 ### 修复内容 - **scripts/query_user_info.py** 完整重写： - 表名改为实际线上表：`vala_user.vala_app_account`、`vala_user.vala_app_character`、`vala_order.vala_seasonal_ticket`、PG `user_chapter_play_record_0~7` - 手机号查询通过 `tel LIKE '前缀%后缀'` 脱敏匹配 - Chapter → Level/Unit/Lesson 映射复用 studytime-analysis 的 `fetch_chapter_info_map()` 逻辑 - 订单数据改用 `vala_seasonal_ticket`（赛季通票），因线上无标准订单表 - 设备/地域信息标注为暂不可用（线上无对应表） - PG 时区处理：`created_at` 为 tz-aware，统一转 naive 比较 - **SKILL.md** 更新至 v2.0.0，补充数据覆盖说明 - **references/dat",
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|
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"snippet": "# 2026-05-13 工作日志 ## 文档权限规则修正 [Cris 确认] **问题：** AGENTS.md 中「权限告知规则」未区分用户身份，对所有用户（包括业务负责人李应瑛）一视同仁地回复「请添加Bot为知识空间成员」。这导致业务负责人被不必要的技术细节阻塞。 **修正：** 更新 AGENTS.md 第3条权限告知规则，按用户身份分级处理： - 业务负责人（刘庆逊、李应瑛）→ 不告知权限问题，直接联系 Cris 处理 - 其他用户 → 保持原有提示 **验证：** 对 `小斑` 文档（Tn23wQkUQilduAkvgwscTGhgnUd）执行了完整的读/写（追加）/删除测试，Bot身份权限全部正常。 ## lark-cli 绑定 完成了 lark-cli 与 OpenClaw 的绑定（bot-only 模式），后续飞书 API 调用无需额外配置。",
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"snippet": "**根因分析**： - `vala_game_chapter`（MySQL）无 `unit_index` 字段 - `big_map_chapter`（PostgreSQL）有 `unit_index` 字段，但仅包含 A1 数据，且与 `vala_game_chapter` 无直接关联键 - 两者 ID 空间不重叠（big_map: ~1720-2070，game_chapter: ~55-399），UUID 也不匹配 **映射方案**： - 每个 season_package 内，`lesson_type=1` 的章节按 `id` 排序，每 5 个连续章节组成一个单元 - Season 0（序章/L1-U0）：所有章节属于 Unit 0 - Season 1-4：每个 season 有 12 个单元（60 个 lesson 章节） - 全局 unit_index = base_offset(season_of_quarter) + unit_within_season - base_offset: 0→0, 1→1, 2→13, 3→25, 4→37 **关键 Bug**：初版按 `season_of_quarter` 分组时 A1 和 A2 混在一起，因为相同季度值合并了。修复：改为按 `(level, season_of_quarter)` 分组。 **验证结果**： - A1: Unit 0-48（49 个单元），与 big_map_chapter 的 unit_index 范围一致 - A2: Unit 0-49（50 个单元，比 A1 多 1 个） *",
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"snippet": "### 16:20 pipeline 非聚光部分验证完成 **lark-cli wrapper v0.3 支持的 action：** | 类别 | action | 状态 | |------|--------|------| | sheets | +read, +write, +append, +info, +meta | ✅ | | sheets | +create-sheet, +delete-sheet | ✅ | | sheets | +batch-set-style (stub) | ✅ | | sheets | +merge-cells, +unmerge-cells | ✅ | | sheets | +update-dimension | ✅ | | bitable | +app, +tables, +records, +create, +update | ✅ | | auth | status | ✅ | | im | +messages-send (stub) | ✅ | **pipeline 试跑结果（--dry-run）：** | 步骤 | 说明 | 耗时 | 状态 | |------|------|------|------| | 1a/1a2 | 微伴 xlsx | — | ⏭ 跳过（无 xlsx） | | 1b/1b2/1c | 聚光 | — | ⏭ 跳过（无 .env.juguang） | | 2b | 客户主表→订单明细 | 5.1s | ✅ dry-run（真跑数据量大，预计几分钟） | | 3 | 日报 C1HVN2 | 38.3s",
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|
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"snippet": "|---|------|------|----------| | 1a | 微伴 → 主表 C 列 | ✅ | 89 行一致 | | 1a2 | 微伴 → 线索分配 2aNzzy | ✅ | 440 行一致 | | 1x | 小溪行课 | ✅ | ⚠ 需Bot交互 | | 1b | 聚光 agent → 主表 | ✅ | 12 格一致 | | 1b2 | 聚光在投笔记 | ✅ | 3 格(55/30/38)一致 | | 1c | 聚光日明细 | ✅ | 137 笔记一致 | | 2b | 客户主表 → 订单 | ✅ | 公式就绪 | | 3 | 日报 C1HVN2 | ✅ | 四段刷新 | | 3a/3c | 口径审计 | ✅ | 推群全过 | | 4a | 结算月汇总 | ✅ | 公式就绪 | **结论：当前表内所有数据与重拉完全一致，零差异，无需刷写。** ### 18:36 小溪行课触发实跑 - 已推 1920 条到小溪查询表（新 Sheet） - 已 @小溪 到小红书数据需求群，请处理 ~5 条待查询记录 - 表格：`RFIJsXT8FhGHhctY4RwczcOfnac` - 等待小溪回填后跑 `pull_xiaoxi_results.py` 回收结果 # 2026-05-28 工作日志 ## 品牌更名与定位升级 [Cris确认] - 姓名：小斑 → **大麦** - 定位：AI班主任 → **增长营销分析师** - 核心职能：增长数据分析、营销效果评估、转化漏斗分析、商业化洞察 - Emoji：📚 → 🌾 - 已更新文件：IDENTITY.md、AGE",
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"snippet": "### 17:56 大麦查询输出表就绪 ✅ [陈逸鸫] 输出表 Token: `GCqNsqgzKhfQ5atFLnQcmLcGn4d`，Sheet: 查询快照 (`fd42b8`) - 实习虾 `cli_aa898f32d4799bea` 已分享编辑权限 - 写入验证通过 (revision 4) - env var: `XIAOBAN_QUERY_OUTPUT_TOKEN=GCqNsqgzKhfQ5atFLnQcmLcGn4d` - 同事查数结果 append `fd42b8!A:G`（请求时间/请求人/查询类型/cutoff/查询参数/结果摘要/备注） ### 17:48 5/27 日报推群成功 ✅ wrapper v0.4 实现 `im +messages-send`，推送 `message_id=om_x100b6eb54f9da0f4b115725198feede` ### 待办汇总 1. 📋 陈逸鸫发 `docs/xiaoban-data-boundary.md` §7 Agent 系统提示词 2. 📋 陈逸鸫发 `docs/xiaoban-runbook.md` §2 部署 checklist 3. 📋 建「大麦查询输出」飞书表 → 陈逸鸫提供 token 4. 📋 `~/xhs-tech-dashboard` 仓库 clone → 陈逸鸫提供访问方式 5. ⏳ 全量 pipeline 聚光步骤验证（子进程中） ### 18:30 Pipeline 全链路 dry-run 验证全部通过 [陈逸鸫] 收到微伴 xlsx，触发全链路 dry-r",
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"snippet": "**需求：行课记录新增当日进线→当天行课 + 7天首课率 + 销售排名 + 日报展示** **数据摸底结果：** | 指标 | 5月数据 | 定义 | |------|---------|------| | 当日进线→当天行课 | 3.0% (4/135) | 进线当天有 chapter settlement | | 7天线索→首课 | 28.6% (10/35) | 过去7天进线中 小溪阶段≥5 | **按销售拆解：** | 销售 | 当日行课率 | 7天首课率 | |------|-----------|----------| | Bob | 7.4% (最高) | 28.6% | | Tom | 3.7% | 28.6% | | 吴迪 | 0% | 28.6% | | 小龙 | 0% | 14.3% (最低) | **改动方案（6处，待陈逸鸫确认后执行）：** 1. **2aNzzy 每日线索分配** — 加 2 列（首课日期 V、当日行课 W） 2. **3PRySY 行课情况** — 加 4 列（当日行课数、当日行课率、7天线索数、7天首课率） 3. **C1HVN2 日报** — 新增「五、行课转化」段 4. **Base 多维表格** — 3 张表加字段（tbl9HgnKU2qgj4gE / tblB27fjK7mDnxjY / tblxjCeGOPNoLHl6） 5. **funnel-daily 看板 HTML** — 新增「当日转化」+「7天首课」指标 6. **build_pipeline 脚本** — 新增 `scripts/compute_l",
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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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"snippet": "# 2026-05-28 工作日志 ## 品牌更名与定位升级 [Cris确认] - 姓名：小斑 → **大麦** - 定位：AI班主任 → **增长营销分析师** - 核心职能：增长数据分析、营销效果评估、转化漏斗分析、商业化洞察 - Emoji：📚 → 🌾 - 已更新文件：IDENTITY.md、AGENTS.md（@规则同步变更）、MEMORY.md - SOUL.md 无需改动（行为方法论为通用框架） ### 16:20 pipeline 非聚光部分验证完成 **lark-cli wrapper v0.3 支持的 action：** | 类别 | action | 状态 | |------|--------|------| | sheets | +read, +write, +append, +info, +meta | ✅ | | sheets | +create-sheet, +delete-sheet | ✅ | | sheets | +batch-set-style (stub) | ✅ | | sheets | +merge-cells, +unmerge-cells | ✅ | | sheets | +update-dimension | ✅ | | bitable | +app, +tables, +records, +create, +update | ✅ | | auth | status | ✅ | | im | +messages-send (stub) | ✅ | **pipeline 试跑结果（--dry-run）：** | 步骤",
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"snippet": "# 2026-05-28 工作日志 ## 品牌更名与定位升级 [Cris确认] - 姓名：小斑 → **大麦** - 定位：AI班主任 → **增长营销分析师** - 核心职能：增长数据分析、营销效果评估、转化漏斗分析、商业化洞察 - Emoji：📚 → 🌾 - 已更新文件：IDENTITY.md、AGENTS.md（@规则同步变更）、MEMORY.md - SOUL.md 无需改动（行为方法论为通用框架） ### 16:20 pipeline 非聚光部分验证完成 **lark-cli wrapper v0.3 支持的 action：** | 类别 | action | 状态 | |------|--------|------| | sheets | +read, +write, +append, +info, +meta | ✅ | | sheets | +create-sheet, +delete-sheet | ✅ | | sheets | +batch-set-style (stub) | ✅ | | sheets | +merge-cells, +unmerge-cells | ✅ | | sheets | +update-dimension | ✅ | | bitable | +app, +tables, +records, +create, +update | ✅ | | auth | status | ✅ | | im | +messages-send (stub) | ✅ | **pipeline 试跑结果（--dry-run）：** | 步骤",
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"snippet": "# 2026-06-02 工作日志 ## 达播达人筛选 [苏雅] 苏雅在群里发多位达人让大麦分析是否适合带瓦拉。 ### 瓦拉英语客单价 - 1999 元 / 3598 元 [苏雅确认] ### 已分析达人汇总 | 达人 | 平台 | 粉丝 | 品类匹配 | 客单价 | 评分 | 结论 | |------|------|------|----------|--------|------|------| | 宝妈文文 | 抖音 | 26.3万 | ❌ 快消低价 | 10-50 | 2/5 | 淘汰 | | CallMe王阿姨 | 小红书 | 24.6万 | ⚠️ 母婴实物 | 500+ | 3.5/5 | 备选 | | 庆爸育儿 | 小红书 | 11万 | ✅ 95%教育 | 200-500 | 4.5/5 | 首选 | | 大大大盔盔 | 小红书 | 40.7万 | ❌ 0-2岁母婴 | ❓ | 2.5/5 | 人群错位 | | 蕾姐聊育儿 | 抖音 | 27.6万 | ⚠️ 启蒙育儿 | ❓ | ❓ | 缺带货数据 | ### 庆爸育儿详细数据 - 总GMV: 10-25万，场均: 1-2.5万，品牌场均: 5000-7500 - 品类: 书籍83.31% + 儿童教育7.77% + 文具4.43% + 玩具4.49% - 客单价: 200-500 - 合作商家28个，商品274个 - 首场预估(瓦拉1999/3598): 保守5000-1万，基准1-2万，乐观2-3万 ### 王阿姨详细数据 - 总GMV: 25-50万，场均: 2.5-5万，品牌场均: 10",
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"snippet": "- 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：Fio（15 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： - ❌ 第1版：芯片悬念开场（信息过载，陌生信息太多） - ❌ 第2版：《妈妈失踪的那天》慢铺垫（信息太慢，冲突不够） - ✅ 第3版：Nook 背叛发布会、Fio 通缉令、Pemberton 杀母档案 三个冷开场 - ✅ **最终版**：《万得港》6格——妈妈失踪十年 → 收到 F 的加密邮件线索 → 冲向万得港 → 新消息揭示\"她不是偶然在那里的\" - 已规划 12 话三幕结构（HOOK → BUILD → CONVERT），转化节点设计为：主角收到妈妈英文语音 → Nook 教英语 → 扫码听课解锁第 4 个词 - 已生成第 1 话封面图（日漫画风，2K 分辨率，3:4 竖版） - **待定**：下一步是生成内容页 / 角色定妆照 / 小红书发布文案 ## 工具/技能发现 - 确认昆鹏发布的 `multi-model-assistant` 和 `gpt-image-2-generator` 两个技能可用 - `multi-model-assistant` 支持调用多个模型（sonnet/opus/deepseek/gpt5.4 等），位于 `/root/.openclaw/skills/multi-model-assistant/`",
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"snippet": "| 蕾姐聊育儿 | 抖音 | 27.6万 | 30天10场直播仅1场带货，GMV=0 | | 斯坦福妈妈 | 抖音 | 143.8万 | 30天零直播零视频零GMV，电商LV1 | | 大大大盔盔 | 小红书 | 40.7万 | 0-2岁错位 | | 小轩和轩妈的日常 | 抖音 | 41.3万 | 娃高中+安徽芜湖低线 | | 宝妈文文 | 抖音 | 26.3万 | 客单价10-50，完全错位 | | Eric爸爸的遛娃手札 | 小红书 | — | GMV 0-100，零带货能力 | ### 推进建议 1. S级闹妈+小朱妈妈优先建联谈合作细节 2. A级四人同步触达，各测一场看转化数据 3. 小蜗牛客单价2000-2200与瓦拉1999最匹配，值得重点关注",
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"snippet": "- **待定**：下一步是生成内容页 / 角色定妆照 / 小红书发布文案 ## 工具/技能发现 - 确认昆鹏发布的 `multi-model-assistant` 和 `gpt-image-2-generator` 两个技能可用 - `multi-model-assistant` 支持调用多个模型（sonnet/opus/deepseek/gpt5.4 等），位于 `/root/.openclaw/skills/multi-model-assistant/` - `gpt-image-2-generator` 通过 FunCloud API 异步生成图片，位于 `/root/.openclaw/skills/gpt-image-2-generator/` - 语音转写使用 DashScope qwen-audio-turbo API，Key 为 `DASHSCOPE_API_KEY`",
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"snippet": "# 2026-06-07 工作日志 ## 群组权限更新 - [王虹茗确认] 群 oc_db7359c4d5d0bc61403c54bf3c46812a（成员：陈逸鸫、王虹茗、吴迪、姜小龙）全员可直接查询角色学习数据，无需逐次审批。该群为数据查询专用群。 ## 数据导出记录 - 角色ID 37714（吴迪）：87条记录（音频34、互动组件51、课程巩固2） - 角色ID 36994（吴迪）：190条记录（音频87、互动组件94、课程巩固5、单元挑战3、单元总结1） - 角色ID 37069（姜小龙）：304条记录（音频181、互动组件118、课程巩固5）",
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"成员",
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]
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"snippet": "# 2026-06-03 工作日志 ## 招聘：商务经理候选人筛选 ### 李泓晔 一面评价 [王虹茗反馈] - **结论：不通过** - 太油了，管理成本高 - 塑品能力不行 - 如果做得不好会出去说瓦拉产品不行（甩锅风险） - 商务能力和资源应该还好，主要是风格不匹配 ### 大麦自省：简历分析的盲区 [2026-06-04] - **数字会骗人：** 看到GMV 1200w+、6倍增长就默认硬实力强，但面试中\"太油了\"恰恰说明此人擅长包装。简历数据要打折扣看。 - **\"能挑毛病\"≠\"懂产品\"：** 面试纪要里批评公司产品，我当时解读为深度理解，但面试官看到的是甩锅前置——\"做不好会说产品不行\"。 - **风格匹配和硬能力同等重要：** 只评了硬能力，完全忽略了管理成本、团队融入、价值观匹配。 - **改进：** 后续分析增加\"风格/文化匹配\"维度，对简历数据标注置信度（高/中/低），面试策略中增加\"风格验证\"类问题。 ### 宋宗佩 一面评价 [王虹茗反馈] - **结论：不通过（本岗位）** - 欠缺达播资源，不具备本岗位相关经验 - 工作内容主要为销售leads课包，对渠道情况、合作模式较为了解",
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"snippet": "| 2b | 客户主表→订单明细 | 5.1s | ✅ dry-run（真跑数据量大，预计几分钟） | | 3 | 日报 C1HVN2 | 38.3s | ✅ 真写成功 | | 4a | 结算月汇总 | <1s | ✅ 真写成功（零警告） | | 3a/3c/3d/4c | 审计 | — | ⏭ dry-run 跳过 | **修复的 wrapper 兼容性问题：** - API 响应格式：`data.spreadsheet` → `data.sheets.sheets`（lark-cli 兼容） - 参数名：`--values` 与 `--data` 等价处理 - camelCase→snake_case：`sheetId` → `sheet_id`，`grid_properties` 包装 - `+info` 端点：v3 metadata → v2 metainfo（含 sheets 列表） - `update-dimension`：`PUT /dimension_range`，1-indexed ### 16:48 聚光凭证部署 **来源：陈逸鸫** — 从 Mac 发来 `.env.juguang.9180` 和 `.env.juguang.9181`，走方案 A（复制文件，不在服务器重 OAuth） - 9180（云智 adv=9746532）：refresh 验证通过 ✅ - 9181（谦禾 adv=9013261,9598861 / YTL adv=7242040,9891870,10157917,10562529）：refresh 验证通过 ✅ - OAu",
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]
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"snippet": "- **改进：** 后续分析增加\"风格/文化匹配\"维度，对简历数据标注置信度（高/中/低），面试策略中增加\"风格验证\"类问题。 ### 宋宗佩 一面评价 [王虹茗反馈] - **结论：不通过（本岗位）** - 欠缺达播资源，不具备本岗位相关经验 - 工作内容主要为销售leads课包，对渠道情况、合作模式较为了解 - 能关注到leads后端的承接、转化并进行优化动作 - **后续方向：** 后面做leads课投放的商务渠道时可以再考虑 - **教训：** 简历中\"达人直售商务经理\"\"在线增长负责人\"等title容易让人高估其达播能力，实际核心能力在CPA/leads渠道运营而非达人直播资源 ### 简历评估优化点 [王虹茗指示] - 需区分\"达播商务\"和\"leads渠道商务\"两类能力，不能仅凭title判断 - 达播商务核心验证：是否有自有达人资源、是否有直播操盘经验、是否有达人分级运营体系 - Leads渠道商务核心验证：CPA/CPS渠道拓展、TMK/短信/进校/社群分销、leads转化链路优化 - 宋宗佩案例说明：title含\"达人直售\"\"增长负责人\"，但实际经验偏leads课包销售，非达人直播资源型 ### 候选人状态追踪 | 候选人 | 状态 | 备注 |",
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|
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|
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|
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|
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}
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