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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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        "排除寒暑假1-2月",
        "7-8月",
        "上午/中午/下午/晚上",
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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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    "memory:memory/2026-03-01.md:1:11": {
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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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        "vala-app-character",
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        "女/1",
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        "vala-app-account",
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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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    "memory:memory/2026-05-24.md:85:110": {
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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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        "unit-index",
        "level/unit/lesson",
        "studycourse-analysis",
        "平均值/中位数",
        "perfect/good/oops/pass/failed",
        "vala-user",
        "vala-app-character"
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    },
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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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        "user-info",
        "bi-vala-app-account",
        "account-login",
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        "bi-vala-order",
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        "scripts/query-user-info.py",
        "vala-user.vala-app-account"
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      "snippet": "| MySQL vala_user | vala_app_character | 角色信息、purchase_season_package | | MySQL vala_user | vala_app_account | 下载渠道、手机号、注册时间 | | MySQL vala | vala_game_chapter + season_package | 章节映射 | | PostgreSQL vala | user_course_detail | 课程激活/到期时间 | | PostgreSQL vala | user_login_app_info | 设备信息 | | PostgreSQL vala | user_chapter_play_record_0~7 | 完课记录(play_status=1) | | PostgreSQL vala | user_component_play_record_0~7 | 中互动记录(play_result) | | PostgreSQL vala | user_chapter_settlement_data_0~7 | 巩固数据(settlement_data JSON) | ### 关键发现 - **设备信息**来自 `user_login_app_info`（device_name/model/type/os_info/city） - **购买渠道**来自 `vala_app_account.download_channel` + `key_from` - **巩固判断**：`settlement_data.practiceS",
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        "vala-user",
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        "vala-app-account",
        "vala-game-chapter",
        "season-package",
        "user-course-detail",
        "课程激活/到期时间"
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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",
      "recallCount": 1,
      "dailyCount": 0,
      "groundedCount": 0,
      "totalScore": 1,
      "maxScore": 1,
      "firstRecalledAt": "2026-05-28T09:07:57.953Z",
      "lastRecalledAt": "2026-05-28T09:07:57.953Z",
      "queryHashes": [
        "c6c7ff4ed75d"
      ],
      "recallDays": [
        "2026-05-28"
      ],
      "conceptTags": [
        "lark-cli",
        "v0.3",
        "create-sheet",
        "delete-sheet",
        "batch-set-style",
        "merge-cells",
        "unmerge-cells",
        "update-dimension"
      ]
    }
  }
}