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      "snippet": "3. **第三轮（用户要求重新发送三份文件后重算）：** 最终确认 **表1有但表2表3都没有 = 255个** - **第三轮详细统计：** - 三表共有：230 - 表1 ∩ 表2：492 - 表1 ∩ 表3：448 - 表2 ∩ 表3：427 - 表1有，表2没有：472（其中217个表3也有） - 最终：255个 - **关键发现：** - 表1（分类词表）覆盖了大量基础生活词汇，表3（L1词表）覆盖了其中的448个 - 最终的255个独有词主要集中在：抽象名词（advantage, attitude, courage）、学术/学科词汇（composition, grammar, pronunciation）、专业/特定领域词（cancer, clone, industry）等偏中高难度的词汇 - 表1和表3有大量重叠（448个），说明两个L1级别的词表覆盖范围高度一致 - 从上一轮260变成255（差5个），差异主要来自表2/表3重新解析后个别单词的增删 - **输出文件：** `/root/.openclaw/workspace-xiaoyan/output/单词对比结果_最终版.xlsx` - Sheet 1：255个单词完整清单（序号+单词+中文释义） - Sheet 2：全部统计指标汇总 - **用户 user_id：** `58fd6864`（租户级） - **发送消息时踩坑记录：** ou_xxx 是 open_id 非 user_id，Bot 缺少 contact:user.id:readonly 权限",
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        "学术/学科词汇",
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        "user-id",
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    "memory:memory/2026-05-07.md:215:235": {
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      "snippet": "3. He is (4) Japan. → from（男孩穿和服，背景富士山） 4. She is a (7). → student（女孩背书包进校门） - **JSON 结构：** questionSetID=020102, category=writing, type=writing_pic_qa - **关键教训：** - 初版设计错误：让学手写 Anna/China 等非知识点词，被用户纠正 - 初版 questionDesc \"She is a (7) girl.\" 不自然，修正为 \"She is a (7).\" - writing_pic_qa 题型核心考察点：知识点词本身（am/from），而非题干已知信息 - 挖空字母数标记（如(4)）必须与答案单词字母数一致 - **词库缺口发现：** L1和L2词库均缺失人称代词(I/you/he/she)、be动词(am/is/are)、介词(from)、国家名等基础功能词，写题时先绕过词汇校验硬性约束 ### 刘彦江 (ou_5af74c1fb96042e33cc0f16b5ca02cf4) — 单元挑战新增3个题型（已完结） - 详见上文 11:19-11:28 记录 ### 刘彦江 (ou_5af74c1fb96042e33cc0f16b5ca02cf4) — 写作看图回答题 \"I am ready / Thank you\" 样题生产 - **时间：** 15:53 ~ 15:55 - **需求：** 使用知识点 \"I am ready! / Thank you for...\" 再生产一套",
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      "conceptTags": [
        "writing-pic-qa",
        "anna/china",
        "am/from",
        "i/you/he/she",
        "am/is/are",
        "19-11",
        "japan",
        "男孩"
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    "memory:memory/2026-05-07.md:199:219": {
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      "snippet": "### 刘彦江 (ou_5af74c1fb96042e33cc0f16b5ca02cf4) — 写作看图回答题 \"I am... / I am from...\" 样题生产 - **时间：** 15:38 ~ 15:52 - **需求：** 使用知识点 \"I am... / I am from...\" 生产一套写作看图回答题（writing_pic_qa） - **状态：** ✅ 已完成，用户确认 - **题型级别：** L2（因L1词库缺少所有代词/be动词/介词/国家名） - **难度：** A级 - **题量：** 4小题 - **核心原则（用户明确）：** 1. 挖空必须是考察知识点本身的单词（am/from/student），不是手写姓名/国名等附带信息 2. 只能为1个单词挖空，不能两个及以上 3. 正确模式示例：`I (2) Anna.` → 挖空am，数字标记字母数 4. 图片提供语境线索（名牌→am，地标→from国家，书包→student），学生填写核心知识点词 - **输出文件：** `output/writing_pic_qa_I_am_from_020102.json` - **题目清单：** 1. I (2) Anna. → am（女孩指着名牌，图片语境提示姓名已给出） 2. I am (4) China. → from（女孩站在长城前，国家名已给出） 3. He is (4) Japan. → from（男孩穿和服，背景富士山） 4. She is a (7). → student（女孩背书包进校门） - **JSON",
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      "conceptTags": [
        "writing-pic-qa",
        "因l1词库缺少所有代词/be动词/介词/国家名",
        "am/from/student",
        "不是手写姓名/国名等附带信息",
        "彦江",
        "写作",
        "回答",
        "生产"
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    "memory:memory/2026-05-07.md:1:20": {
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      "path": "memory/2026-05-07.md",
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      "snippet": "# 2026-05-07 工作日志 ## 会话记录 ### 刘彦江 (ou_5af74c1fb96042e33cc0f16b5ca02cf4) — 单元挑战新增3个题型 - **时间：** 11:19 ~ 11:28 - **需求：** 单元挑战新增3个题型：阅读看图回答题（reading_pic_qa）、阅读看图判断题（reading_pic_judge）、写作看图回答题（writing_pic_qa） - **状态：** ✅ 已完成题型规范落地 - **交付内容：** 1. 创建3个题型SKILL.md： - `reading/common/reading_pic_qa/SKILL.md` — 阅读看图回答题（共享大图+多题Yes/No判断） - `reading/common/reading_pic_judge/SKILL.md` — 阅读看图判断题（每题独立配图+Yes/No判断） - `writing/common/writing_pic_qa/SKILL.md` — 写作看图回答题（看图+提示答案开头+填空） 2. 更新 `MEMORY.md` 全题型阶段归属规则 3. 明确题型JSON结构、难度等级（A/B/C/D四级）、能力标签、校验规则 - **关键决策：** 3个题型均为 L1&L2 共用，通过难度参数区分阶段；reading_pic_qa 共享大图，reading_pic_judge 每题独立配图 ### 李应瑛 (ou_1bd7317ae2ccfeb57e1132028847279e) — 单词表对比请求",
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      "maxScore": 1,
      "firstRecalledAt": "2026-05-08T01:18:18.412Z",
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        "2026-05-09",
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      "conceptTags": [
        "reading-pic-qa",
        "reading-pic-judge",
        "writing-pic-qa",
        "创建3个题型skill.md",
        "多题yes/no判断",
        "yes/no判断",
        "memory.md",
        "a/b/c/d四级"
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    },
    "memory:memory/2026-04-13.md:1:5": {
      "key": "memory:memory/2026-04-13.md:1:5",
      "path": "memory/2026-04-13.md",
      "startLine": 1,
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      "source": "memory",
      "snippet": "## 2026-04-13 12:28 [童瑶需求] 读取飞书文档https://makee-interactive.feishu.cn/wiki/QkY5wkcZYindgzkv5O0cpApRnzh内L1S1_Unit 11【其他需求】中所有的图片，并根据【描述】列的ID重命名为\"ID.png\" [执行结果] 完成35张图片的提取和重命名，保存到unit11_final_images/目录下，包含L1-L5全级别教研图、选项图，全部符合命名规则。",
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      "dailyCount": 0,
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      "maxScore": 1,
      "firstRecalledAt": "2026-05-11T02:19:37.985Z",
      "lastRecalledAt": "2026-05-11T02:19:37.985Z",
      "queryHashes": [
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      "recallDays": [
        "2026-05-11"
      ],
      "conceptTags": [
        "id.png",
        "保存到unit11-final-images/目录下",
        "包含l1-l5全级别教研图",
        "需求",
        "https",
        "makee",
        "interactive.feishu.cn",
        "wiki"
      ]
    },
    "memory:memory/2026-05-08.md:33:55": {
      "key": "memory:memory/2026-05-08.md:33:55",
      "path": "memory/2026-05-08.md",
      "startLine": 33,
      "endLine": 55,
      "source": "memory",
      "snippet": "**图片资源新规：** - 每个题组共享一张图（非每题独立配图） - 产出 JSON 同时输出图片描述 prompt（英文，卡通简线条风格） - prompt 写入 bitable `图片描述` 列，格式 `{\"first\": \"...\", \"second\": \"...\"}` **通用化写入流程：** - 单元挑战全题型适用：定位 bitable 表 → 创建/更新记录 → 写入 `题目集合 ID` + `jsonData` + `图片描述` - 各题型仅 jsonData 结构不同，写入流程统一 **重写文件：** - `business_production/单元挑战/skills/unit_challenge/questions/writing/common/writing_pic_qa/SKILL.md`（11节完整规范） - `business_production/单元挑战/skills/unit_challenge/questions/writing/writing_pic_qa/SKILL.md`（简化为快速入口） **bitable 更新：** 已将新 JSON（每题组1图2题）+ 图片描述写入 `recviZlAxxXlAb` ### 刘彦江 (ou_5af74c1fb96042e33cc0f16b5ca02cf4) — 图片描述格式修正 - **时间：** 09:46 ~ 09:51 - **修正：** 用户给出中文样例格式，要求图片描述从英文 prompt 改为纯中文结构化列表 - **新格式：** 编号 `1.` / `2.` 自上而下，每段",
      "recallCount": 2,
      "dailyCount": 0,
      "groundedCount": 0,
      "totalScore": 2,
      "maxScore": 1,
      "firstRecalledAt": "2026-05-11T02:19:37.985Z",
      "lastRecalledAt": "2026-05-11T02:37:23.203Z",
      "queryHashes": [
        "6f88450e9f9b",
        "be437071312f"
      ],
      "recallDays": [
        "2026-05-11"
      ],
      "conceptTags": [
        "创建/更新记录",
        "图片",
        "资源",
        "共享",
        "一张",
        "每题",
        "独立",
        "同时"
      ]
    },
    "memory:memory/2026-05-08.md:1:23": {
      "key": "memory:memory/2026-05-08.md:1:23",
      "path": "memory/2026-05-08.md",
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      "source": "memory",
      "snippet": "### 刘彦江 (ou_5af74c1fb96042e33cc0f16b5ca02cf4) — writing_pic_qa 样题生产 \"I am / I am going to / I am ready / Thank you for\" - **时间：** 09:26 ~ 09:34 - **需求：** 生产 writing_pic_qa A级样题，ID=000001，2题组各2小题 - **状态：** ✅ 已完成，已写入飞书多维表格 - **目标表格：** 单元挑战 → 写作-P3-看图回答题 (tblFc9TVl2PeM2tg)，record_id=recviZlAxxXlAb - **题目清单：** 题组1 (first): 1. I (2) a student. → am（女孩穿校服举手，考察be动词am） 2. I am (5) to school. → going（男孩背书包走向校门，考察going） 题组2 (second): 3. I am (5)! → ready（男孩穿泳衣戴泳镜，考察状态词ready） 4. Thank you (3) the book. → for（女孩接书微笑，考察介词for） - **核心修正（用户反馈）：** 1. 挖空必须考察知识点核心词，非附带信息（you → for） 2. 不能挖空题干已有信息（如姓名/国家名），只挖知识点词本身 3. 只能为1个单词挖空 4. question与questionDesc人称必须一致（统一改为 What does [角色] say? → 第一人称直接",
      "recallCount": 1,
      "dailyCount": 0,
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      "totalScore": 1,
      "maxScore": 1,
      "firstRecalledAt": "2026-05-11T02:37:23.203Z",
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      "recallDays": [
        "2026-05-11"
      ],
      "conceptTags": [
        "writing-pic-qa",
        "写作-p3-看图回答题",
        "record-id",
        "如姓名/国家名",
        "彦江",
        "生产",
        "going",
        "ready"
      ]
    },
    "memory:memory/2026-05-11.md:39:55": {
      "key": "memory:memory/2026-05-11.md:39:55",
      "path": "memory/2026-05-11.md",
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      "snippet": "- `基础信息表达｜个人信息问答` — 姓名/年龄/家庭/外貌类 - `表达喜好与理由` — 偏好/观点/意愿类 - `过去经历描述｜Past Activities` — 过去事件类 - `互动应答｜问答交流` — 社交场景类 - `信息交换｜双向问答` — 物品归属/需求类 - 未使用标签（属看图/发音题型专用）：图片描述类(3个)、图片对比、故事讲述、发音与语调 - **分类逻辑**：基于关键词匹配（what do you say → 互动应答; what did you/last → 过去经历; favorite/like/want → 喜好; name/age/from/family → 个人信息; whose/need → 信息交换） ### 刘彦江 — reading_matchInfo 阅读信息匹配题（4套: 010901/011001/011101/011201，18:55 ~ 19:15） - **需求：** 4套 reading_matchInfo，L2 A级，能力标签 标识与通知理解｜标识 & 通知 - 每套 first=5q + second=5q，每题含 questionImage/question/options/answer/ability/explanation - **表：** 阅读-P1-信息匹配题（tblCgfYDnnqwLfgH） - **自动化问题：** 该表存在异步自动化，创建后会将 jsonData 改写为模板壳（减少题量+覆盖 ability） - **解决方案：** 两阶段延迟写入（先创建空记录→等35s让",
      "recallCount": 2,
      "dailyCount": 0,
      "groundedCount": 0,
      "totalScore": 2,
      "maxScore": 1,
      "firstRecalledAt": "2026-05-12T01:33:44.968Z",
      "lastRecalledAt": "2026-05-12T01:41:17.155Z",
      "queryHashes": [
        "4ab75020b1ab",
        "7ca0207f1308"
      ],
      "recallDays": [
        "2026-05-12"
      ],
      "conceptTags": [
        "姓名/年龄/家庭/外貌类",
        "偏好/观点/意愿类",
        "物品归属/需求类",
        "属看图/发音题型专用",
        "you/last",
        "favorite/like/want",
        "name/age/from/family",
        "whose/need"
      ]
    },
    "memory:memory/2026-05-11.md:20:43": {
      "key": "memory:memory/2026-05-11.md:20:43",
      "path": "memory/2026-05-11.md",
      "startLine": 20,
      "endLine": 43,
      "source": "memory",
      "snippet": "- **需求：** 2套 reading_pic_qa，L2 A级，能力标签 图文判断｜句图一致性 - 每套5+5道 Y/N 判断，3Y2N平衡，4-7词陈述句 - **状态：** ✅ 已完成，2套全部入库 + 图片描述回填验证通过 - **脚本：** `scripts/batch_reading_pic_qa_2.py` | ID | 题组1 | 题组2 | record_id | |----|-------|-------|-----------| | 010701 | notebook/star/folder/diary/contact | friendly/crazy/brilliant/kind/afraid | recvjiQuGtsVp8 | | 010801 | uncle/aunt/grandma/neighbour/pet | expensive/entrance/upstairs/downstairs/toast | recvjiQvc8EsB8 | - 表：阅读-P7-看图回答题（tblweY65jGBiwSdt） - 当前该表累计：11条记录（000001~010801，含reading_pic_judge类型 4 条及其他） ### 刘彦江 — 口语-P1-日常回答 ability 标签填充（18:15 ~ 18:25） - **需求：** 从能力标签名称图片中，选择与已生成题目契合的标签填入 jsonData - 表：口语-P1-日常回答（tblRGv7k4WH58Jgq），26条有效记录，185道题 - **状态：** ✅ 全部完成 - *",
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      "maxScore": 1,
      "firstRecalledAt": "2026-05-12T01:33:44.968Z",
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      "queryHashes": [
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      "recallDays": [
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      "conceptTags": [
        "reading-pic-qa",
        "y/n",
        "4-7词陈述句",
        "record-id",
        "uncle/aunt/grandma/neighbour/pet",
        "阅读-p7-看图回答题",
        "含reading-pic-judge类型",
        "口语-p1-日常回答"
      ]
    },
    "memory:memory/2026-05-11.md:66:83": {
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      "source": "memory",
      "snippet": "1. 图片应是**真实标识/通知**（非标签式），如零售楼层导览那种 2. 图片上的文字**至少为一句话**，L2 A级难度，不能只有一个词 - **处理：** 4 套 reading_matchInfo 全部重新设计（题目+图片描述），两阶段延迟写入 - **新record_ids:** recvjj2Nuw9MJd / recvjj2NZz75zb / recvjj2Ov8Stks / recvjj2OX0Dmo5 - **改进要点：** - 每张图改为真实通知/标识，如 \"TRAINS to the NORTH. Go to Platform 3.\" - 图片文字至少 1 句完整陈述，含足够信息供阅读提取 - 题目围绕通知/标识内容提问，考察学生从标识中抓取关键信息的能力 ### 刘彦江 — reading_matchInfo 阅读信息匹配题（6套L2 B级: 021301-021801，19:30 ~ 19:45） - **需求：** 6套 reading_matchInfo，L2 B级，能力标签 标识与通知理解｜标识 & 通知 - **B级规范：** 文本3-5词短句，图片为同类差异，简单对应；每张图是真实的标识/通知（非标签式） - **状态：** ✅ 全部完成（两阶段延迟写入策略，避免自动化覆盖） - **脚本：** `scripts/batch_reading_matchInfo.py` | ID | 题组1 | 题组2 | record_id | |----|-------|-------|-----------| | 021301 |",
      "recallCount": 1,
      "dailyCount": 0,
      "groundedCount": 0,
      "totalScore": 1,
      "maxScore": 1,
      "firstRecalledAt": "2026-05-12T01:41:17.155Z",
      "lastRecalledAt": "2026-05-12T01:41:17.155Z",
      "queryHashes": [
        "7ca0207f1308"
      ],
      "recallDays": [
        "2026-05-12"
      ],
      "conceptTags": [
        "真实标识/通知",
        "reading-matchinfo",
        "新record-ids",
        "每张图改为真实通知/标识",
        "题目围绕通知/标识内容提问",
        "021301-021801",
        "文本3-5词短句",
        "每张图是真实的标识/通知"
      ]
    },
    "memory:memory/2026-05-11.md:51:68": {
      "key": "memory:memory/2026-05-11.md:51:68",
      "path": "memory/2026-05-11.md",
      "startLine": 51,
      "endLine": 68,
      "source": "memory",
      "snippet": "- **自动化问题：** 该表存在异步自动化，创建后会将 jsonData 改写为模板壳（减少题量+覆盖 ability） - **解决方案：** 两阶段延迟写入（先创建空记录→等35s让自动化完成→PUT jsonData），010901/011201 修复后验证通过 | ID | 题组1 | 题组2 | record_id | |----|-------|-------|-----------| | 010901 | north/east/south/west/exit（方向标识） | businessman/job/letter/call/guard（职场） | recvjiYAHtp05c | | 011001 | beat/dancer/drum/player/work（音乐体育） | aged/good-looking/mistake/weakness/be good at（人物描述） | recvjiXLdt5itq | | 011101 | dangerous/badly/worst/steal/run away（危险） | minute/close/kilometre/second/away（时间距离） | recvjiXLOOWMsq | | 011201 | summer/winter/Earth/holiday/term（季节） | examination/plus/minus/biology/study（学校） | recvjiYBd8Mejs | - **脚本：** `scripts/batch_reading_matchInfo.py` - *",
      "recallCount": 1,
      "dailyCount": 0,
      "groundedCount": 0,
      "totalScore": 1,
      "maxScore": 1,
      "firstRecalledAt": "2026-05-12T01:41:17.155Z",
      "lastRecalledAt": "2026-05-12T01:41:17.155Z",
      "queryHashes": [
        "7ca0207f1308"
      ],
      "recallDays": [
        "2026-05-12"
      ],
      "conceptTags": [
        "010901/011201",
        "record-id",
        "north/east/south/west/exit",
        "beat/dancer/drum/player/work",
        "dangerous/badly/worst/steal/run",
        "summer/winter/earth/holiday/term",
        "自动",
        "问题"
      ]
    }
  }
}