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"snippet": "- **需求：** 将 020102（I am...）和 020103（I am ready / Thank you）两套题合并为一个 `{first:..., second:...}` JSON，统一 questionSetID=0000001 - **状态：** ✅ 已完成 - **核心考点分析（用户强调）：** 需分析每个句型的核心考点（孩子最容易犯错的地方），挖空对准核心考点 - I am/from 组：am（系动词第一人称）、from（介词选择）、student（a+名词结构） - Thank you for 组：for（介词选择，非 you）、helping（for+动名词，非 help/to help） - **输出文件：** `output/writing_pic_qa_combined.json` ### 刘彦江 — 组件配置-json 请求（L1-S2-U13-L4 沙漠之花） - **时间：** 16:45 ~ 17:51 - **文档：** `https://makee-interactive.feishu.cn/wiki/K5E1wzwk7it9t7kXvcbc6Xugnhc` - **状态：** ⚠️ 未完成 — pipeline 识别到 0 组件 - **根因：** 剧本文档的13个组件数据存储在 markdown 内联表格中（lark-table，5列×36行），而非内嵌 Sheet。当前 pipeline 的 parse_script 只从内嵌 Sheet 读取组件数据，不支持 markdown 表格组件解析 - **已识别组件（ma",
|
"snippet": "- **需求：** 将 020102（I am...）和 020103（I am ready / Thank you）两套题合并为一个 `{first:..., second:...}` JSON，统一 questionSetID=0000001 - **状态：** ✅ 已完成 - **核心考点分析（用户强调）：** 需分析每个句型的核心考点（孩子最容易犯错的地方），挖空对准核心考点 - I am/from 组：am（系动词第一人称）、from（介词选择）、student（a+名词结构） - Thank you for 组：for（介词选择，非 you）、helping（for+动名词，非 help/to help） - **输出文件：** `output/writing_pic_qa_combined.json` ### 刘彦江 — 组件配置-json 请求（L1-S2-U13-L4 沙漠之花） - **时间：** 16:45 ~ 17:51 - **文档：** `https://makee-interactive.feishu.cn/wiki/K5E1wzwk7it9t7kXvcbc6Xugnhc` - **状态：** ⚠️ 未完成 — pipeline 识别到 0 组件 - **根因：** 剧本文档的13个组件数据存储在 markdown 内联表格中（lark-table，5列×36行），而非内嵌 Sheet。当前 pipeline 的 parse_script 只从内嵌 Sheet 读取组件数据，不支持 markdown 表格组件解析 - **已识别组件（ma",
|
||||||
"recallCount": 5,
|
"recallCount": 6,
|
||||||
"dailyCount": 0,
|
"dailyCount": 0,
|
||||||
"groundedCount": 0,
|
"groundedCount": 0,
|
||||||
"totalScore": 5,
|
"totalScore": 6,
|
||||||
"maxScore": 1,
|
"maxScore": 1,
|
||||||
"firstRecalledAt": "2026-05-15T07:13:08.147Z",
|
"firstRecalledAt": "2026-05-15T07:13:08.147Z",
|
||||||
"lastRecalledAt": "2026-05-18T08:52:44.266Z",
|
"lastRecalledAt": "2026-05-21T07:39:38.958Z",
|
||||||
"queryHashes": [
|
"queryHashes": [
|
||||||
"08364c8746ab",
|
"08364c8746ab",
|
||||||
"4f08741ab4fd",
|
"4f08741ab4fd",
|
||||||
"6a1144a866c9",
|
"6a1144a866c9",
|
||||||
"65b539c56ec3",
|
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|
||||||
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|
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|
||||||
|
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|
||||||
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|
],
|
||||||
"recallDays": [
|
"recallDays": [
|
||||||
"2026-05-15",
|
"2026-05-15",
|
||||||
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|
"2026-05-17",
|
||||||
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|
"2026-05-18",
|
||||||
|
"2026-05-21"
|
||||||
],
|
],
|
||||||
"conceptTags": [
|
"conceptTags": [
|
||||||
"am/from",
|
"am/from",
|
||||||
@ -868,23 +877,25 @@
|
|||||||
"endLine": 8,
|
"endLine": 8,
|
||||||
"source": "memory",
|
"source": "memory",
|
||||||
"snippet": "[李应瑛 2026-04-22 提出要求] 所有需要包含对话的内容（如剧本、互动组件等）必须要有【后置对话】字段，无后置对话时填写“无”。 [李应瑛 2026-04-22 确认规则] 剧本内嵌表格组件填写位置规则：仅当表格第一列（A列）明确标注为对话类类型（对话朗读/对话挖空/对话选读/对话组句等）时，才在同一行的H列（【组件】列）填写对应的组件内容，其他类型行（TL/场景/角色/图片/非对话类等）无需填写。 [李应瑛 2026-04-22 确认格式规则] 对话类组件字段换行规则：每个结构单独占一行，格式为： 【任务标题】xxx 【情境引入】xxx 【互动内容】xxx 【后置对话】xxx 单元格内使用\\n作为换行符实现，后续所有组件均遵循此格式。",
|
"snippet": "[李应瑛 2026-04-22 提出要求] 所有需要包含对话的内容（如剧本、互动组件等）必须要有【后置对话】字段，无后置对话时填写“无”。 [李应瑛 2026-04-22 确认规则] 剧本内嵌表格组件填写位置规则：仅当表格第一列（A列）明确标注为对话类类型（对话朗读/对话挖空/对话选读/对话组句等）时，才在同一行的H列（【组件】列）填写对应的组件内容，其他类型行（TL/场景/角色/图片/非对话类等）无需填写。 [李应瑛 2026-04-22 确认格式规则] 对话类组件字段换行规则：每个结构单独占一行，格式为： 【任务标题】xxx 【情境引入】xxx 【互动内容】xxx 【后置对话】xxx 单元格内使用\\n作为换行符实现，后续所有组件均遵循此格式。",
|
||||||
"recallCount": 4,
|
"recallCount": 5,
|
||||||
"dailyCount": 0,
|
"dailyCount": 0,
|
||||||
"groundedCount": 0,
|
"groundedCount": 0,
|
||||||
"totalScore": 4,
|
"totalScore": 5,
|
||||||
"maxScore": 1,
|
"maxScore": 1,
|
||||||
"firstRecalledAt": "2026-05-15T07:13:08.147Z",
|
"firstRecalledAt": "2026-05-15T07:13:08.147Z",
|
||||||
"lastRecalledAt": "2026-05-18T08:52:44.266Z",
|
"lastRecalledAt": "2026-05-21T07:39:38.958Z",
|
||||||
"queryHashes": [
|
"queryHashes": [
|
||||||
"08364c8746ab",
|
"08364c8746ab",
|
||||||
"4f08741ab4fd",
|
"4f08741ab4fd",
|
||||||
"6a1144a866c9",
|
"6a1144a866c9",
|
||||||
"19c873a71799"
|
"19c873a71799",
|
||||||
|
"47f8c15000b2"
|
||||||
],
|
],
|
||||||
"recallDays": [
|
"recallDays": [
|
||||||
"2026-05-15",
|
"2026-05-15",
|
||||||
"2026-05-17",
|
"2026-05-17",
|
||||||
"2026-05-18"
|
"2026-05-18",
|
||||||
|
"2026-05-21"
|
||||||
],
|
],
|
||||||
"conceptTags": [
|
"conceptTags": [
|
||||||
"对话朗读/对话挖空/对话选读/对话组句等",
|
"对话朗读/对话挖空/对话选读/对话组句等",
|
||||||
@ -967,18 +978,20 @@
|
|||||||
"endLine": 41,
|
"endLine": 41,
|
||||||
"source": "memory",
|
"source": "memory",
|
||||||
"snippet": "- `raw_content` API 不暴露此类嵌入 Sheet，需通过 blocks API 查找 `block_type=30` 的 grid_column 节点来发现 sheet token - 该文档含 2 个嵌入 Sheet：`zbfYO4`（知识点区）和 `Nr3Ovs`（243 行 × 8 列脚本表） ### 已完成的组件回填（14/14 对话组件） | 组件类型 | 数量 | 所用 skill | |---------|:--:|-----------| | 对话朗读 | 6 | dialogue-reading-config | | 对话朗读-配图 | 2 | dialogue-reading-config | | 对话挖空 | 2 | dialogue-fill-in-blanks-config | | 对话挖空-配图 | 1 | dialogue-fill-in-blanks-config | | 对话选择-配图 | 1 | dialogue-choose-config | | 对话选读 | 1 | **dialogue-selective-reading-config（新建）** | | 对话组句 | 1 | dialogue-sentence-building-config | ### Skill 库补全 - **新建 skill**：`~/.openclaw/workspace-xiaoyan/skills/dialogue-selective-reading-config/SKILL.md` - 格式来源：`dialogue-inter",
|
"snippet": "- `raw_content` API 不暴露此类嵌入 Sheet，需通过 blocks API 查找 `block_type=30` 的 grid_column 节点来发现 sheet token - 该文档含 2 个嵌入 Sheet：`zbfYO4`（知识点区）和 `Nr3Ovs`（243 行 × 8 列脚本表） ### 已完成的组件回填（14/14 对话组件） | 组件类型 | 数量 | 所用 skill | |---------|:--:|-----------| | 对话朗读 | 6 | dialogue-reading-config | | 对话朗读-配图 | 2 | dialogue-reading-config | | 对话挖空 | 2 | dialogue-fill-in-blanks-config | | 对话挖空-配图 | 1 | dialogue-fill-in-blanks-config | | 对话选择-配图 | 1 | dialogue-choose-config | | 对话选读 | 1 | **dialogue-selective-reading-config（新建）** | | 对话组句 | 1 | dialogue-sentence-building-config | ### Skill 库补全 - **新建 skill**：`~/.openclaw/workspace-xiaoyan/skills/dialogue-selective-reading-config/SKILL.md` - 格式来源：`dialogue-inter",
|
||||||
"recallCount": 1,
|
"recallCount": 2,
|
||||||
"dailyCount": 0,
|
"dailyCount": 0,
|
||||||
"groundedCount": 0,
|
"groundedCount": 0,
|
||||||
"totalScore": 1,
|
"totalScore": 2,
|
||||||
"maxScore": 1,
|
"maxScore": 1,
|
||||||
"firstRecalledAt": "2026-05-18T02:42:25.325Z",
|
"firstRecalledAt": "2026-05-18T02:42:25.325Z",
|
||||||
"lastRecalledAt": "2026-05-18T02:42:25.325Z",
|
"lastRecalledAt": "2026-05-21T02:47:59.335Z",
|
||||||
"queryHashes": [
|
"queryHashes": [
|
||||||
"eb45753e9aa6"
|
"eb45753e9aa6",
|
||||||
|
"09344f87b646"
|
||||||
],
|
],
|
||||||
"recallDays": [
|
"recallDays": [
|
||||||
"2026-05-18"
|
"2026-05-18",
|
||||||
|
"2026-05-21"
|
||||||
],
|
],
|
||||||
"conceptTags": [
|
"conceptTags": [
|
||||||
"raw-content",
|
"raw-content",
|
||||||
@ -1123,22 +1136,24 @@
|
|||||||
"endLine": 27,
|
"endLine": 27,
|
||||||
"source": "memory",
|
"source": "memory",
|
||||||
"snippet": "# 2026-05-18 工作日志 ## 单元挑战全题型审核 + 修复 ### 背景 [刘彦江] 要求对单元挑战全部20种题型审核，重点：解析不能纯英文、答案格式正确性。题目内容不修改。 ### 审核结果 - 审核范围：20张表、244条记录 - 答案格式：零问题 - 纯英文解析：13处（听力-P2 021901 ×10，口语-P1 032701/032901，口语-P2 032801） - 解析为空：83处（听力-P1 000001+110101~110401 ×50，听力-P4 021701/022101/032501/032901 ×20，共写作-P3复查后实际OK） ### 修复执行 - 13条纯英文→中文化翻译（通过模型翻译） - 70条空解析→从题目内容+ability关键词智能生成 - 全部通过 Python+curl 写回 bitable（避免shell转义） - 写入后回读验证：107条全部含中文，零错误 ### 审校结果列更新 - 格式：`✅ OK | 2026-05-18 小研审校` / `📝 空模板 | 2026-05-18 小研审校` - 已更新：18张表、241条记录 - 缺失列：写作-P2（tblSAwlMumKoyjws）、口语-P4（tblsD2dxaRpLmkXD）无「审校结果」列 ### 经验 - 写作-P3 解析在 questionList 嵌套层级，初审误判为空，复查后确认含中文 - bitable curl 写回嵌套JSON时，Python subprocess构造完整body比shell变量展开安全",
|
"snippet": "# 2026-05-18 工作日志 ## 单元挑战全题型审核 + 修复 ### 背景 [刘彦江] 要求对单元挑战全部20种题型审核，重点：解析不能纯英文、答案格式正确性。题目内容不修改。 ### 审核结果 - 审核范围：20张表、244条记录 - 答案格式：零问题 - 纯英文解析：13处（听力-P2 021901 ×10，口语-P1 032701/032901，口语-P2 032801） - 解析为空：83处（听力-P1 000001+110101~110401 ×50，听力-P4 021701/022101/032501/032901 ×20，共写作-P3复查后实际OK） ### 修复执行 - 13条纯英文→中文化翻译（通过模型翻译） - 70条空解析→从题目内容+ability关键词智能生成 - 全部通过 Python+curl 写回 bitable（避免shell转义） - 写入后回读验证：107条全部含中文，零错误 ### 审校结果列更新 - 格式：`✅ OK | 2026-05-18 小研审校` / `📝 空模板 | 2026-05-18 小研审校` - 已更新：18张表、241条记录 - 缺失列：写作-P2（tblSAwlMumKoyjws）、口语-P4（tblsD2dxaRpLmkXD）无「审校结果」列 ### 经验 - 写作-P3 解析在 questionList 嵌套层级，初审误判为空，复查后确认含中文 - bitable curl 写回嵌套JSON时，Python subprocess构造完整body比shell变量展开安全",
|
||||||
"recallCount": 4,
|
"recallCount": 5,
|
||||||
"dailyCount": 0,
|
"dailyCount": 0,
|
||||||
"groundedCount": 0,
|
"groundedCount": 0,
|
||||||
"totalScore": 4,
|
"totalScore": 5,
|
||||||
"maxScore": 1,
|
"maxScore": 1,
|
||||||
"firstRecalledAt": "2026-05-18T02:42:52.167Z",
|
"firstRecalledAt": "2026-05-18T02:42:52.167Z",
|
||||||
"lastRecalledAt": "2026-05-19T01:21:22.997Z",
|
"lastRecalledAt": "2026-05-21T02:47:43.415Z",
|
||||||
"queryHashes": [
|
"queryHashes": [
|
||||||
"88190dc3b5bc",
|
"88190dc3b5bc",
|
||||||
"2a58080272be",
|
"2a58080272be",
|
||||||
"e3188fdd52d6",
|
"e3188fdd52d6",
|
||||||
"8ccf25e60418"
|
"8ccf25e60418",
|
||||||
|
"f76487d76697"
|
||||||
],
|
],
|
||||||
"recallDays": [
|
"recallDays": [
|
||||||
"2026-05-18",
|
"2026-05-18",
|
||||||
"2026-05-19"
|
"2026-05-19",
|
||||||
|
"2026-05-21"
|
||||||
],
|
],
|
||||||
"conceptTags": [
|
"conceptTags": [
|
||||||
"听力-p2",
|
"听力-p2",
|
||||||
@ -1158,21 +1173,23 @@
|
|||||||
"endLine": 144,
|
"endLine": 144,
|
||||||
"source": "memory",
|
"source": "memory",
|
||||||
"snippet": "## [刘彦江] 写作+口语 C级 032501-032901 生产（2026-05-14 15:42） ### 生产内容（10条） | # | 表 | QSID | record_id | 题型 | 主题 | 难度 | |---|-----|------|-----------|------|------|------| | 1 | 写作-P1 | 032501 | recvjzXjMKAQ4i | 邮件组句 | 鼓励朋友参加音乐会 | C | | 2 | 写作-P1 | 032601 | recvjzXklYIE05 | 邮件组句 | 给老师写感谢信 | C | | 3 | 写作-P1 | 032701 | recvjzXkYnsQ8r | 邮件组句 | 描述咖啡馆和遇到的人 | C | | 4 | 写作-P1 | 032801 | recvjzXlxz4r3i | 邮件组句 | 科学项目求助 | C | | 5 | 写作-P1 | 032901 | recvjzXm5yEXBY | 邮件组句 | 妈妈的生日派对 | C | | 6 | 口语-P1 | 032501 | recvjzWP7IcA8O | 日常回答 | 观点转变与过去习惯 | C | | 7 | 口语-P1 | 032701 | recvjzWPQc5JZW | 日常回答 | 好奇心与想法改变 | C | | 8 | 口语-P1 | 032901 | recvjzWQr0Kif7 | 日常回答 | 团队合作与沟通 | C | | 9 | 口语-P2 | 032601 | recvjzWR07LSna |",
|
"snippet": "## [刘彦江] 写作+口语 C级 032501-032901 生产（2026-05-14 15:42） ### 生产内容（10条） | # | 表 | QSID | record_id | 题型 | 主题 | 难度 | |---|-----|------|-----------|------|------|------| | 1 | 写作-P1 | 032501 | recvjzXjMKAQ4i | 邮件组句 | 鼓励朋友参加音乐会 | C | | 2 | 写作-P1 | 032601 | recvjzXklYIE05 | 邮件组句 | 给老师写感谢信 | C | | 3 | 写作-P1 | 032701 | recvjzXkYnsQ8r | 邮件组句 | 描述咖啡馆和遇到的人 | C | | 4 | 写作-P1 | 032801 | recvjzXlxz4r3i | 邮件组句 | 科学项目求助 | C | | 5 | 写作-P1 | 032901 | recvjzXm5yEXBY | 邮件组句 | 妈妈的生日派对 | C | | 6 | 口语-P1 | 032501 | recvjzWP7IcA8O | 日常回答 | 观点转变与过去习惯 | C | | 7 | 口语-P1 | 032701 | recvjzWPQc5JZW | 日常回答 | 好奇心与想法改变 | C | | 8 | 口语-P1 | 032901 | recvjzWQr0Kif7 | 日常回答 | 团队合作与沟通 | C | | 9 | 口语-P2 | 032601 | recvjzWR07LSna |",
|
||||||
"recallCount": 3,
|
"recallCount": 4,
|
||||||
"dailyCount": 0,
|
"dailyCount": 0,
|
||||||
"groundedCount": 0,
|
"groundedCount": 0,
|
||||||
"totalScore": 3,
|
"totalScore": 4,
|
||||||
"maxScore": 1,
|
"maxScore": 1,
|
||||||
"firstRecalledAt": "2026-05-18T11:35:06.740Z",
|
"firstRecalledAt": "2026-05-18T11:35:06.740Z",
|
||||||
"lastRecalledAt": "2026-05-19T01:21:22.997Z",
|
"lastRecalledAt": "2026-05-21T02:47:43.415Z",
|
||||||
"queryHashes": [
|
"queryHashes": [
|
||||||
"2a58080272be",
|
"2a58080272be",
|
||||||
"e3188fdd52d6",
|
"e3188fdd52d6",
|
||||||
"8ccf25e60418"
|
"8ccf25e60418",
|
||||||
|
"f76487d76697"
|
||||||
],
|
],
|
||||||
"recallDays": [
|
"recallDays": [
|
||||||
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"snippet": "| 10 | P5 | recvjuiypW7mZY | 补审校结果（之前漏写） | | 11 | P4 | recvjufM76frUP | 缺second题组→人工确认豁免 | | - | P7 | recviZIWmT91yS | ⏭️ 人工确认跳过 | ### 最终状态 - ✅ 通过 48条 | ⏭️ 跳过 2条 | 🔴 0条 - 全部有内容的记录审校通过 ## [刘彦江] 写作+口语题目生产（2026-05-14 12:10） ### 生产内容（6条） | # | 表 | QSID | record_id | 题型 | first | second | |---|-----|------|-----------|------|-------|--------| | 1 | 写作-P1-邮件回复 | 021801 | recvjz5GeTe9aB | writing_email | 6句排序 | — | | 2 | 写作-P1-邮件回复 | 021901 | recvjz5GE2LKi9 | writing_email | 7句排序 | — | | 3 | 写作-P1-邮件回复 | 022001 | recvjz5H3s5k8y | writing_email | 6句排序 | — | | 4 | 口语-P2-话题讨论 | 021801 | recvjz5Hs8gpCJ | speaking_topic | 5题 | 5题 | | 5 | 口语-P1-日常回答 | 021901 | recvjz5HSdc0nZ | speaking_qa | 4题 | 4题",
|
"snippet": "| 10 | P5 | recvjuiypW7mZY | 补审校结果（之前漏写） | | 11 | P4 | recvjufM76frUP | 缺second题组→人工确认豁免 | | - | P7 | recviZIWmT91yS | ⏭️ 人工确认跳过 | ### 最终状态 - ✅ 通过 48条 | ⏭️ 跳过 2条 | 🔴 0条 - 全部有内容的记录审校通过 ## [刘彦江] 写作+口语题目生产（2026-05-14 12:10） ### 生产内容（6条） | # | 表 | QSID | record_id | 题型 | first | second | |---|-----|------|-----------|------|-------|--------| | 1 | 写作-P1-邮件回复 | 021801 | recvjz5GeTe9aB | writing_email | 6句排序 | — | | 2 | 写作-P1-邮件回复 | 021901 | recvjz5GE2LKi9 | writing_email | 7句排序 | — | | 3 | 写作-P1-邮件回复 | 022001 | recvjz5H3s5k8y | writing_email | 6句排序 | — | | 4 | 口语-P2-话题讨论 | 021801 | recvjz5Hs8gpCJ | speaking_topic | 5题 | 5题 | | 5 | 口语-P1-日常回答 | 021901 | recvjz5HSdc0nZ | speaking_qa | 4题 | 4题",
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|
"8ccf25e60418",
|
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|
"f76487d76697"
|
||||||
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|
||||||
"recallDays": [
|
"recallDays": [
|
||||||
"2026-05-18",
|
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|
||||||
"2026-05-19"
|
"2026-05-19",
|
||||||
|
"2026-05-21"
|
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|
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||||||
"conceptTags": [
|
"conceptTags": [
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@ -1226,21 +1245,23 @@
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||||||
"snippet": "| 10 | 口语-P2 | 032801 | recvjzWRISLiD9 | 话题讨论 | 挑战与习惯管理 | C | ### 落款多样化 - Yours truly, Sam / Warm regards, Lucy / Kind regards, Emma / Gratefully, Tom / With love, Jessica ### 图片描述（口语-P2） - 032601: 梦想与未来（仰望星空、选择困难、职业海报、老师写\"梦想\"） - 032801: 挑战与习惯（作业压力、游戏打到深夜、考试不及格、图书馆讨论） ### 写作表字段名 - 写作-P1 字段为\"题目1\"（非\"题目1 完整配置\"），口语-P1 使用\"题目1热词\"/\"题目2热词\" ## [刘彦江] 口语-P1 explanation 全量补充（2026-05-14 16:01） ### 背景 口语-P1-日常回答表（tblRGv7k4WH58Jgq）共39条记录，其中23条历史记录的171道题目 explanation 字段为空。 ### 补齐结果 - 更新记录：23条 → 全部写回成功 - 生成 explanation：171题 - 最终验证：258题全通过（0空、0偏短） - 新增3条（032501/032701/032901）在前序批次中已含完整 explanation，本次未改动 ### 生成规则 按 ability 标签分类匹配模板生成中文解析： - 基础信息表达｜个人信息问答 → 细分：年龄/姓名/家庭/外貌/物品位置 - 表达喜好与理由 → 喜好+because原因引导",
|
"snippet": "| 10 | 口语-P2 | 032801 | recvjzWRISLiD9 | 话题讨论 | 挑战与习惯管理 | C | ### 落款多样化 - Yours truly, Sam / Warm regards, Lucy / Kind regards, Emma / Gratefully, Tom / With love, Jessica ### 图片描述（口语-P2） - 032601: 梦想与未来（仰望星空、选择困难、职业海报、老师写\"梦想\"） - 032801: 挑战与习惯（作业压力、游戏打到深夜、考试不及格、图书馆讨论） ### 写作表字段名 - 写作-P1 字段为\"题目1\"（非\"题目1 完整配置\"），口语-P1 使用\"题目1热词\"/\"题目2热词\" ## [刘彦江] 口语-P1 explanation 全量补充（2026-05-14 16:01） ### 背景 口语-P1-日常回答表（tblRGv7k4WH58Jgq）共39条记录，其中23条历史记录的171道题目 explanation 字段为空。 ### 补齐结果 - 更新记录：23条 → 全部写回成功 - 生成 explanation：171题 - 最终验证：258题全通过（0空、0偏短） - 新增3条（032501/032701/032901）在前序批次中已含完整 explanation，本次未改动 ### 生成规则 按 ability 标签分类匹配模板生成中文解析： - 基础信息表达｜个人信息问答 → 细分：年龄/姓名/家庭/外貌/物品位置 - 表达喜好与理由 → 喜好+because原因引导",
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"recallCount": 3,
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"recallDays": [
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"recallDays": [
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||||||
"2026-05-18",
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"2026-05-18",
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"2026-05-19"
|
"2026-05-19",
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|
"2026-05-21"
|
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],
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],
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"conceptTags": [
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"conceptTags": [
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@ -1260,21 +1281,23 @@
|
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"source": "memory",
|
"source": "memory",
|
||||||
"snippet": "## [刘彦江] 单元挑战口语写作内容生产（2026-05-13 21:40） ### 生产范围（10条记录，全部单题组，全部回填验证通过 ✅） | ID | 写作-P1 | 口语-P1 | 写作-P2 | 口语-P2 | 状态 | |----|---------|---------|---------|---------|------| | 011301 | ✅ 邮件回复 | ✅ 日常回答 | - | - | 全部通过 | | 011401 | ✅ 邮件回复 | ✅ 日常回答 | - | - | 全部通过 | | 011501 | ✅ 邮件回复 | ✅ 日常回答 | - | - | 全部通过 | | 011701 | ✅ 邮件回复 | ✅ 日常回答 | - | - | 全部通过 | | 011601 | - | - | ✅ 看图写作 | ✅ 话题讨论 | 全部通过 | ### 题型结构总结 **写作-P1 (writing_email)**: - 6句段落排序（含3句知识点作为范文核心句） - 能力标签：短消息写作｜邮件/便条, 衔接与连贯｜连词使用 - 场景：火灾求助/宠物照顾/惊喜派对/故事分享 **口语-P1 (speaking_qa)**: - 4个引导问题，每问引导1个知识点句型 - 能力标签：基础信息表达｜个人信息问答, 表达喜好与理由, 互动应答｜问答交流 - 问题设计引导关键词：外貌描述/主动帮忙/耐心等待/购物清单 **写作-P2 (writing_picWrite)**: - 6句故事排序（含3句知识点作为故事核心句） - 能力标签：叙述故",
|
"snippet": "## [刘彦江] 单元挑战口语写作内容生产（2026-05-13 21:40） ### 生产范围（10条记录，全部单题组，全部回填验证通过 ✅） | ID | 写作-P1 | 口语-P1 | 写作-P2 | 口语-P2 | 状态 | |----|---------|---------|---------|---------|------| | 011301 | ✅ 邮件回复 | ✅ 日常回答 | - | - | 全部通过 | | 011401 | ✅ 邮件回复 | ✅ 日常回答 | - | - | 全部通过 | | 011501 | ✅ 邮件回复 | ✅ 日常回答 | - | - | 全部通过 | | 011701 | ✅ 邮件回复 | ✅ 日常回答 | - | - | 全部通过 | | 011601 | - | - | ✅ 看图写作 | ✅ 话题讨论 | 全部通过 | ### 题型结构总结 **写作-P1 (writing_email)**: - 6句段落排序（含3句知识点作为范文核心句） - 能力标签：短消息写作｜邮件/便条, 衔接与连贯｜连词使用 - 场景：火灾求助/宠物照顾/惊喜派对/故事分享 **口语-P1 (speaking_qa)**: - 4个引导问题，每问引导1个知识点句型 - 能力标签：基础信息表达｜个人信息问答, 表达喜好与理由, 互动应答｜问答交流 - 问题设计引导关键词：外貌描述/主动帮忙/耐心等待/购物清单 **写作-P2 (writing_picWrite)**: - 6句故事排序（含3句知识点作为故事核心句） - 能力标签：叙述故",
|
||||||
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|
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|
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|
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|
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"firstRecalledAt": "2026-05-18T11:35:06.740Z",
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"firstRecalledAt": "2026-05-18T11:35:06.740Z",
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"2026-05-18",
|
"2026-05-18",
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||||||
"2026-05-19"
|
"2026-05-19",
|
||||||
|
"2026-05-21"
|
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|
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@ -1389,18 +1412,20 @@
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|
"source": "memory",
|
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"snippet": "- Script sheet: `wMQVyV`（186行×9列） - Knowledge points sheet: `DCcKsLbrmhfXgrtB7N2c9GA4ntf_NtIcXt` - 列结构：A=类型, D=剧情描述, E=角色名, F=编剧台词（English已填好）, **G=组件配置** - 知识点：point, talk, understand, a lot of + `talk to...` / `I can/can't understand...` ### 交互模式差异 - L5 文档 B列/C列 为空，无详细组件类型标签（仅 A=互动/核心互动-口语） - 编剧台词F列已全部填写（英文） - 互动行的 User 台词含红色标注知识点词 ### 完成事项 - 24个互动行全部生成G列配置（组件类型推断：听力挖空、朗读台词、口语表达） - 写入方式：同上 Sheets v2 API - 24/24 全部回读验证通过 ### 脚本 `scripts/write_L5_G_configs.py`",
|
"snippet": "- Script sheet: `wMQVyV`（186行×9列） - Knowledge points sheet: `DCcKsLbrmhfXgrtB7N2c9GA4ntf_NtIcXt` - 列结构：A=类型, D=剧情描述, E=角色名, F=编剧台词（English已填好）, **G=组件配置** - 知识点：point, talk, understand, a lot of + `talk to...` / `I can/can't understand...` ### 交互模式差异 - L5 文档 B列/C列 为空，无详细组件类型标签（仅 A=互动/核心互动-口语） - 编剧台词F列已全部填写（英文） - 互动行的 User 台词含红色标注知识点词 ### 完成事项 - 24个互动行全部生成G列配置（组件类型推断：听力挖空、朗读台词、口语表达） - 写入方式：同上 Sheets v2 API - 24/24 全部回读验证通过 ### 脚本 `scripts/write_L5_G_configs.py`",
|
||||||
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|
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|
||||||
"dailyCount": 0,
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|
||||||
"maxScore": 1,
|
"maxScore": 1,
|
||||||
"firstRecalledAt": "2026-05-20T06:31:39.981Z",
|
"firstRecalledAt": "2026-05-20T06:31:39.981Z",
|
||||||
"lastRecalledAt": "2026-05-20T06:31:39.981Z",
|
"lastRecalledAt": "2026-05-21T02:47:43.415Z",
|
||||||
"queryHashes": [
|
"queryHashes": [
|
||||||
"688d2dceca9d"
|
"688d2dceca9d",
|
||||||
|
"d05a0257d44b"
|
||||||
],
|
],
|
||||||
"recallDays": [
|
"recallDays": [
|
||||||
"2026-05-20"
|
"2026-05-20",
|
||||||
|
"2026-05-21"
|
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],
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|
||||||
"conceptTags": [
|
"conceptTags": [
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"can/can",
|
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@ -1513,18 +1538,20 @@
|
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|
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||||||
"source": "memory",
|
"source": "memory",
|
||||||
"snippet": "- **方法：** `scripts/audit_l1_config.py` 自动化扫描 → 误报排除 → 分类汇总 → 逐条审校回填 - **脚本修复（过程中）：** 1. sentenceStructureSort 单词对比大小写误报 → 添加 normalize（首字母大写 + 去标点） 2. ID 末尾空格敏感 → strip 比较 3. 句子朗读/跟读题误报 options/answer 缺失 → 跳过这两种题型 #### 审校结果汇总（初版） - **🔴 系统性问题（40/40，100%）：** classificationInfo JSON 内 cambridgeLevel=\"A1\" 与 cefrLevel=\"YLE\" 值互换 - **🟡 具体错误（17/40）：** - sentenceMeaningMeaning JSON 解析失败 × 10：1213004, 1213006, 1213010, 1214008, 1215005, 1216001, 1216004, 1216007, 1216008, 1216010 - ID 字段末尾空格 × 3：1213001, 1215001, 1216001 - 看图选择题有CN无JSON × 3：1213008, 1215010, 1216005 - sentenceStructureSort 语法/格式错误 × 3：1213004(缺逗号clean Otis→clean, Otis), 1213005(bird?连写应拆为bird+?), 1214001(need→needs三单)",
|
"snippet": "- **方法：** `scripts/audit_l1_config.py` 自动化扫描 → 误报排除 → 分类汇总 → 逐条审校回填 - **脚本修复（过程中）：** 1. sentenceStructureSort 单词对比大小写误报 → 添加 normalize（首字母大写 + 去标点） 2. ID 末尾空格敏感 → strip 比较 3. 句子朗读/跟读题误报 options/answer 缺失 → 跳过这两种题型 #### 审校结果汇总（初版） - **🔴 系统性问题（40/40，100%）：** classificationInfo JSON 内 cambridgeLevel=\"A1\" 与 cefrLevel=\"YLE\" 值互换 - **🟡 具体错误（17/40）：** - sentenceMeaningMeaning JSON 解析失败 × 10：1213004, 1213006, 1213010, 1214008, 1215005, 1216001, 1216004, 1216007, 1216008, 1216010 - ID 字段末尾空格 × 3：1213001, 1215001, 1216001 - 看图选择题有CN无JSON × 3：1213008, 1215010, 1216005 - sentenceStructureSort 语法/格式错误 × 3：1213004(缺逗号clean Otis→clean, Otis), 1213005(bird?连写应拆为bird+?), 1214001(need→needs三单)",
|
||||||
"recallCount": 1,
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"snippet": "- **ID 编码规则：** 7位 = 前2位(Season) + 中2位(Unit) + 后3位(序列号) - 例: 1214001 = L1S2(12) + U14(14) + 001 - **审校记录 1214001 (You need to...) 发现：** 1. ❌ classificationInfo 值互换: cambridgeLevel=A1 vs cefrLevel=YLE（与列字段反了） 2. ❌ sentenceStructureSort 题2: 单词库有need无needs，三单主语Otis语法错误 3. ⚠️ sentenceStructureClozeWordMcq: \"put your toys\" 省略 away 不够自然 - **技能沉淀：** - 脚本: `scripts/audit_l1_config.py` — 7项自动检查 - SKILL.md: `skills/audit_l1_config/SKILL.md` — 含完整审校流程 + 4项人工审核清单 ### 刘彦江 — 1213001-1216010 批量审校 40 条（12:10 ~ 14:00） - **范围：** L1S2 Units 13-16，每单元 10 条，共 40 条 - **方法：** `scripts/audit_l1_config.py` 自动化扫描 → 误报排除 → 分类汇总 → 逐条审校回填 - **脚本修复（过程中）：** 1. sentenceStructureSort 单词对比大小写误报 → 添加 normalize（首",
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|
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"snippet": "- **结果**：16个组件中 15成功 / 0失败 / 1跳过（看图拼词 1217413 未注册） ### Bug修复：parse_script.py cId提取fallback - **现象**：pipeline 识别到 0 个组件行 - **根因**：本文档的 cId（如 1217408）嵌入在 B 列（配置信息）而非 A 列（类型）。`extract_component_id` 只从类型列提取 cId，找不到就返回 None - **修复**：在 `parse_component_rows` 中新增 fallback — 当 comp_info 为 None 时，从 config_info 列（B列）提取 cId - **修改文件**：`business_production/组件配置/interactive-component-json/scripts/parse_script.py` ### 待处理 - 「看图拼词」类型需注册到 `match_component.py` 后才能生成 JSON",
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"snippet": "- 写作互动和邮件组句 cType 相同（`core_writing_questionMakeSentence`） #### 产出文件 - `skills/interactive-component-json/references/json_structure_guide.md` — 27 种中互动 jsonData 字段结构（8736 bytes） - `skills/interactive-component-json/references/component_registry.md` — 核心互动部分从🔲更新为完整注册表（含 cType+bitable_token） - 与 `skills/core-content-json-standard/SKILL.md` 双向关联 #### 覆盖率 - 核心互动：15/15 ✅（口语探讨 S0 无数据已标注） - 中互动：27/27 ✅ - 关联文件：3 个（core-content-json-standard + component_registry + json_structure_guide） ## 刘彦江 — 中互动+核心互动 回填任务（18:37 待继续） ### 上下文 - 用户提供剧本文档: `https://makee-interactive.feishu.cn/wiki/YqzzwpjwjihK9YkyRhXccaqLnzu` - 要求：识别文档中的 3 个中互动 + 1 个核心互动，回填到对应位置 - 上次已读取文档，找到 1 个核心互动标记（第4幕 听力拖拽），但 3 个中互动标记不明显 - 用户让我",
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"snippet": "- **更新**：`~/.openclaw/workspace-xiaoyan/skills/task-router/component_configs.yaml` — dialogue_selective_reading 配置从占位格式更新为实际格式 ### 关键技术点 - **嵌入 Sheet 写入**：使用 feishu-embedded-sheet 技能，通过 curl 调用 `sheets/v2/spreadsheets/{token}/values` 批量 PUT - **多行写入验证**：写入后按行回读确认每行 H 列内容完整性 - **Shell 转义**：component 内容含多行文本+特殊字符时，用 Python subprocess 传 curl 避免 shell 变量展开破坏数据 ### 未处理行 - R181 信息拼词、R188 信息组句 — 不属于 6 类对话组件，需单独处理",
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|
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|
||||||
|
"sheets/v2/spreadsheets",
|
||||||
|
"更新",
|
||||||
|
"openclaw",
|
||||||
|
"xiaoyan",
|
||||||
|
"skills"
|
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|
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|
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"snippet": "3. **后置对话禁止重复下行台词**：如下行是 User 的后续台词，后置对话不能复制，统一用「无」 4. **组件配置权威文档**：`WD6LwyWNtip8M8k0RWxcbJDcnxe`（飞书知识库 - 教研生产配置、修改规范） ## [李应瑛] 组件配置正确流程纠正 - **纠正**：不应手动往 wiki 文档 C 列写文本格式配置，正确做法是用 pipeline 脚本 - **正确流程**： ``` cd /root/.openclaw/workspace-xiaoyan/business_production/组件配置/interactive-component-json && \\ python3 scripts/pipeline.py \"<wiki_url>\" --send-to gc9f72ff ``` - **Pipeline 6 步**：读取飞书文档 → 解析剧本sheet → 匹配组件类型 → LLM生成jsonData/kpInfo → 写入本地SQLite → 生成HTML报告发送给童瑶 - **Skill 目录**：`business_production/组件配置/interactive-component-json/` ## [李应瑛] L1-S2-U17-L4 门关啦 — Pipeline 组件配置生产 - **文档**: SAadwW8YaiObl8k4op3c6vs8nqb | **Spreadsheet**: It4AsFkC7hXHc4te9yUcyLHRnOe - **结果**：16个组件中 15成功 / 0失败",
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|
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|
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|
||||||
|
"wiki-url",
|
||||||
|
"send-to",
|
||||||
|
"llm生成jsondata/kpinfo",
|
||||||
|
"l1-s2-u17-l4",
|
||||||
|
"对话",
|
||||||
|
"禁止",
|
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|
"重复"
|
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|
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|
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|
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|
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"snippet": "- 批量更新 JSON：写入前完整提取 → 写入后逐字段 diff → 异常立即回滚 - 首次修复多题 JSON 导致 Q2 丢失 → 先单条试跑验证再批量 ### sentenceMeaningMeaning 引号规范（2026-05-12） - explanation 中 ASCII `\"` 与中文引号混用导致 JSON 解析失败 - 建议：生产侧统一用中文引号 `\"\"`（U+201C/D），或写入前做引号归一化 ### 写作互动 / 邮件组句 cType 相同（2026-05-12） - 两者 cType 均为 `core_writing_questionMakeSentence`，通过 textInfo.textList[].type 区分素材 ### 刘彦江 — 中互动全题型录入（18:00 ~ 18:25） #### 发现 - **中互动结构高度统一：** 全部 27 类都用 `jsonData`（主配置）+ `kpInfo`（知识点绑定），没有核心互动那种多字段分散结构 - **6 大分类：** 🗨对话(7) / 📋信息(6) / 📦词汇(2) / 🖼图片选择(4) / 📝语法(3) / 🔧其他(5) - **对话类公共字段：** cType, cId, title, resourceMapping, preDialog, imgShowTimingList - 写作互动和邮件组句 cType 相同（`core_writing_questionMakeSentence`） #### 产出文件 - `skills/interactive-com",
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|
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|
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|
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|
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|
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|
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|
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|
||||||
|
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|
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|
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|
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|
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|
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|
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|
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|
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|
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|
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"snippet": "- 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，最终通过 lark-cli 其他接口获取到 user_id = 58fd6864 - **备注：** 李应瑛不在负责人配置中，不在完整权限用户列表中。当前请求属于教研内容分析，已先接单处理。 # 2026-05-07 工作日志 ## 会话记录 ### 李应瑛 (ou_1bd7317ae2ccfeb57e1132028847279e) — 单词表三轮对比（已完结） - **时间：** 10:39 ~ 11:24 - **需求：** 对比三份单词表，找出\"表1有但表2和表3都没有\"的单词。 - **状态：** ✅ 已完成，结果已交付用户，最终结果 255 个单词，经多次验证（包括用户重新发送文件后重算）结果一致。 - **文件：** - 表1：.doc 文件（分类主题单词表，14个大类，970个单词） - 表2：.xlsx 文件（LV2词表，1,329个单词，含「LV2-单词」「LV2上单词占用情况」「LV2下单词占用情况」「LV2S3」四个sheet） - 表3：.xlsx 文件（L1词表，845个单词，含「单词表-LV1（上）」「单词表-LV1（下）」「单词表-备用」三个sheet合并去重） - **对比过程（共四轮验证）：**",
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||||||
|
"lastRecalledAt": "2026-05-21T09:52:45.581Z",
|
||||||
|
"queryHashes": [
|
||||||
|
"dca4eb1f24b7",
|
||||||
|
"fcca27e77e74"
|
||||||
|
],
|
||||||
|
"recallDays": [
|
||||||
|
"2026-05-21"
|
||||||
|
],
|
||||||
|
"conceptTags": [
|
||||||
|
"user-id",
|
||||||
|
"ou-xxx",
|
||||||
|
"open-id",
|
||||||
|
"user.id",
|
||||||
|
"lark-cli",
|
||||||
|
"lv2-单词",
|
||||||
|
"单词表-lv1",
|
||||||
|
"单词表-备用"
|
||||||
|
]
|
||||||
|
},
|
||||||
|
"memory:memory/2026-05-20.md:1:31": {
|
||||||
|
"key": "memory:memory/2026-05-20.md:1:31",
|
||||||
|
"path": "memory/2026-05-20.md",
|
||||||
|
"startLine": 1,
|
||||||
|
"endLine": 31,
|
||||||
|
"source": "memory",
|
||||||
|
"snippet": "# 2026-05-20 工作日志 ## [童瑶] L1-S2-U17-L2 迟到的包裹 — 英文台词润色 - 134行对话台词全部润色完成，写入H列 - S2标准：句长≤8词、英式拼写、口语化、知识点保留 - 详情见 `business_production/英文台词/memory/2026-05-20.md` ## [童瑶] L1-S2-U17-L1 摩托怪客 — 组件配置JSON - 16个互动组件，14个成功生成JSON，2个跳过 - 跳过：图片无序多选（注册表无匹配）、阅读理解（核心互动未注册） - HTML报告已通过飞书Bot发送给童瑶 ## [童瑶] L1-S2-U17-L4 捉迷藏 — 组件生产（第111行起） - **文档**: SAadwW8YaiObl8k4op3c6vs8nqb | **Sheet**: wMQVyV | **Spreadsheet**: It4AsFkC7hXHc4te9yUcyLHRnOe - 从第111行起识别9个互动组件，全部完成F列回填，最终验证通过 - 最终组件行及对应关系： | 行号 | 组件类型 | 组件ID | |------|---------|--------| | 111 | 对话选择-配图 | 1217408 | | 119 | 对话选择-配图 | 1217409 | | 127 | 对话挖空-配图 | 1217410 | | 130 | 对话组句-配图 | 1217411 | | 141 | 对话组句-配图 | 1217412 | | 150 | 看图拼词 | 1217413 | | 166 | 对话",
|
||||||
|
"recallCount": 1,
|
||||||
|
"dailyCount": 0,
|
||||||
|
"groundedCount": 0,
|
||||||
|
"totalScore": 1,
|
||||||
|
"maxScore": 1,
|
||||||
|
"firstRecalledAt": "2026-05-21T07:31:52.322Z",
|
||||||
|
"lastRecalledAt": "2026-05-21T07:31:52.322Z",
|
||||||
|
"queryHashes": [
|
||||||
|
"03b71fab8fb9"
|
||||||
|
],
|
||||||
|
"recallDays": [
|
||||||
|
"2026-05-21"
|
||||||
|
],
|
||||||
|
"conceptTags": [
|
||||||
|
"l1-s2-u17-l2",
|
||||||
|
"l1-s2-u17-l1",
|
||||||
|
"l1-s2-u17-l4",
|
||||||
|
"对话选择-配图",
|
||||||
|
"对话挖空-配图",
|
||||||
|
"对话组句-配图",
|
||||||
|
"工作",
|
||||||
|
"日志"
|
||||||
|
]
|
||||||
}
|
}
|
||||||
}
|
}
|
||||||
}
|
}
|
||||||
|
|||||||
66
memory/2026-05-21-1450.md
Normal file
66
memory/2026-05-21-1450.md
Normal file
@ -0,0 +1,66 @@
|
|||||||
|
# Session: 2026-05-21 14:50:18 GMT+8
|
||||||
|
|
||||||
|
- **Session Key**: agent:xiaoyan:feishu:direct:ou_5af74c1fb96042e33cc0f16b5ca02cf4
|
||||||
|
- **Session ID**: f8b23e82-58ba-4e6e-ba71-9e880991273d
|
||||||
|
- **Source**: feishu
|
||||||
|
|
||||||
|
## Conversation Summary
|
||||||
|
|
||||||
|
user: 、mew
|
||||||
|
assistant: 彦江，"、mew" 这条消息看起来像是误触或没打完？需要我帮你做什么吗？
|
||||||
|
user: 家长问咱们这个软件是如何锻炼孩子形成英语思维最后能够自己说出英语的句子？有木有专业的话术呀
|
||||||
|
assistant: 彦江，结合产品的教研方法论，整理了一套面向家长的专业话术：
|
||||||
|
|
||||||
|
---
|
||||||
|
|
||||||
|
## 家长话术：Vala 如何帮助孩子形成英语思维、自主表达
|
||||||
|
|
||||||
|
### 一、核心理念：有意义的学习行为重复
|
||||||
|
|
||||||
|
孩子的英语思维不是"背"出来的，是"用"出来的。Vala 的底层方法论就一句话：**在真实有意义的场景中，让孩子反复使用英语，直到内化为本能反应。**
|
||||||
|
|
||||||
|
这里有两个关键词：
|
||||||
|
- **"有意义"** — 孩子不是在机械刷题。每个知识点都嵌套在剧情故事中，孩子是为了帮角色解决问题、推进剧情才去学去说的，有真实的沟通动机。
|
||||||
|
- **"重复"** — 一个知识点在同一个 Unit 内会出现 5-7 次：剧情中听到 → 互动中练习 → 回顾中巩固 → 总结中串联 → 挑战中检验 → 错了进错题本再练。而且不是一天刷完，是按科学间隔分散在多天，符合"分散练习（Distributed Practice）"的认知规律，记忆留存率远高于集中突击。
|
||||||
|
|
||||||
|
### 二、英语思维的养成路径：先听懂，再会说
|
||||||
|
|
||||||
|
这背后遵循二语习得的经典路径：**大量可理解输入 → 引导性输出 → 自主表达**。
|
||||||
|
|
||||||
|
**第一步：情境中"听懂"（输入阶段）**
|
||||||
|
- 孩子在剧情场景中接触到新单词、新句型，配合画面和情境，不是翻译式学习（apple = 苹果），而是直接建立"声音→画面→意义"的英语思维链路
|
||||||
|
- 比如在"超市购物"场景中听到 "How much is this?"，孩子直接关联到询价这个场景，不需要中文中转
|
||||||
|
|
||||||
|
**第二步：互动中"练会"（引导输出阶段）**
|
||||||
|
- 系统设计了 20+ 种互动题型，从低门槛到高难度逐级递进：
|
||||||
|
- **跟读/朗读** → 建立发音和语感
|
||||||
|
- **挖空填空** → 在语境中调用词汇
|
||||||
|
- **组句排序** → 理解英语语序结构
|
||||||
|
- **看图说话/日常问答** → 半开放表达，有画面和问题引导
|
||||||
|
- **话题讨论** → 自由表达观点
|
||||||
|
|
||||||
|
- 关键是：每个互动都绑定具体知识点，系统实时给反馈。不是"说错了也不知道"，而是即时纠正，确保孩子在正确路径上练习。
|
||||||
|
|
||||||
|
**第三步：真实任务中"用出来"（自主表达阶段）**
|
||||||
|
- 每单元最后有"单元挑战"，模拟 KET 真实考试场景，孩子需要在听、说、读、写四个维度综合运用学过的知识
|
||||||
|
- 口语部分设计为日常问答和话题讨论，孩子不是复述课文，而是用学过的句型和词汇表达自己的想法
|
||||||
|
|
||||||
|
### 三、为什么孩子最终能自己说出句子？
|
||||||
|
|
||||||
|
三个机制同时在起作用：
|
||||||
|
|
||||||
|
1. **句型积累 + 场景绑定** — L1+L2 合计学习了 870 个句型，每个句型都绑定真实使用场景（购物、问路、描述人物、表达喜好等）。当孩子遇到相似场景，句型会自动激活。
|
||||||
|
|
||||||
|
2. **从模仿到创造** — 互动设计遵循"控制性练习 → 半控制性练习 → 自由产出"的梯度。比如先组句（给单词让你拼）、再回答引导问题（给你问题框架让你填）、最后话题讨论（只有主题，你自由说），逐步撤销脚手架。
|
||||||
|
|
||||||
|
3. **词汇+句型→句子的组装能力** — 中互动组件专门训练知识点的组合运用，比如信息组句题练的就是"把学过的单词和句型组合成完整句子"这个核心能力。孩子不是背整句，而是掌握了"用已知零件组装新句子"的能力，这才是英语思维的本质。
|
||||||
|
|
||||||
|
---
|
||||||
|
|
||||||
|
### 给家长的一句话总结（可单独使用）
|
||||||
|
|
||||||
|
> Vala 不是让孩子背英语，而是让孩子"用"英语。在剧情故事里自然习得单词和句型，通过 20 多种互动反复练习，最后在真实场景中自己说出来。整个过程遵循"听懂→练会→用出来"的语言学习规律，让孩子像学母语一样建立英语思维。
|
||||||
|
|
||||||
|
---
|
||||||
|
|
||||||
|
需要我调整话术风格（更通俗 / 更学术）或者拆成短版用于不同场景吗？
|
||||||
74
memory/2026-05-21.md
Normal file
74
memory/2026-05-21.md
Normal file
@ -0,0 +1,74 @@
|
|||||||
|
# 2026-05-21 工作记忆
|
||||||
|
|
||||||
|
## 事件记录
|
||||||
|
|
||||||
|
### 1. 口语题目句型知识点改写（刘彦江）
|
||||||
|
- 多轮 JSON 改写任务，将指定句型知识点嵌入 speaking_qa 题目
|
||||||
|
- 句型包括：It's ... now / It's bad for your health to ... / We are ... now / We want to catch ... / Please help me ... / I want to buy ... / I only need ... / We must not ... / I will use it to ... / It was ... / It helped a lot to ... / It tastes like ... / I've decided to ...
|
||||||
|
- 规则：知识点必须是答案，每个问题设计确保回答必然触发目标句型
|
||||||
|
|
||||||
|
### 2. 单元挑战听力拖拽题解析补充（刘彦江）
|
||||||
|
- 涉及 ID：010501, 010601, 010701, 010801, 010901
|
||||||
|
- 多维表格：App Token `CMHSbUUjka3TrUsaxxEc297ongf`，表 `听力-P7-听力拖拽` (tbly9SvPEa44k3yX)
|
||||||
|
- 每个 ID 包含 first 和 second 两组（题组1和题组2），两组都需要补充完整解析
|
||||||
|
|
||||||
|
### 3. bitable 操作经验教训
|
||||||
|
- **Shell 转义陷阱再次确认**：jsonData 中包含大量嵌套 JSON，Shell 变量展开会破坏数据。必须用 Python subprocess + curl 直接构造请求体
|
||||||
|
- **`¥¥` 分隔符与 bitable API 不兼容**：原数据中用 `¥¥` 作为解析分隔符，写入 bitable 后会导致 jsonData 损坏。后续改用 `||` 替代
|
||||||
|
- **explanation 字段路径**：位于 `questionSet[0].explanation`，而非 section 层级的 `explanation`
|
||||||
|
- **operate_bitable.sh 限制**：仅适用于简单字段更新，复杂嵌套 JSON 场景不可用
|
||||||
|
|
||||||
|
### 4. Python bitable 更新脚本模式
|
||||||
|
```python
|
||||||
|
import subprocess, json
|
||||||
|
|
||||||
|
# 获取 token
|
||||||
|
# curl GET records 获取数据
|
||||||
|
data = json.loads(response)['data']
|
||||||
|
record = data['items'][0] # 或 data['item']
|
||||||
|
fields = record['fields']
|
||||||
|
jd = json.loads(fields['jsonData'])
|
||||||
|
|
||||||
|
# 修改数据
|
||||||
|
jd['first']['questionSet'][0]['explanation'] = '...'
|
||||||
|
jd['second']['questionSet'][0]['explanation'] = '...'
|
||||||
|
|
||||||
|
# 序列化并更新（注意 ensure_ascii=False）
|
||||||
|
fields['jsonData'] = json.dumps(jd, ensure_ascii=False)
|
||||||
|
body = json.dumps({"fields": fields})
|
||||||
|
subprocess.run(['curl', '-X', 'PUT', url, '-H', f'Authorization: Bearer {token}', ...])
|
||||||
|
```
|
||||||
|
- 关键：读取后立即备份原始数据，写完后回读验证完整性
|
||||||
|
|
||||||
|
### 5. 解析生成规则
|
||||||
|
- 每道题的解析需包含：听力原文引用 → 答案对应 → 关键特征 → 冗余排除/语用推理
|
||||||
|
- first 和 second 的解析需分别定制，不可复制模板
|
||||||
|
- 干扰抑制类题目：标注冗余信息类型（位置/情绪/动作/大小等）
|
||||||
|
- 否定纠错类题目：标注否定信号词和身份替换逻辑
|
||||||
|
- 跨句整合类题目：标注需整合的信息来源和推理路径
|
||||||
|
### 6. 剧本内嵌 Sheet 组件配置回填（刘彦江）
|
||||||
|
- 文档：L1-S2-U17-L5 笨蛋坏蛋？（wiki token `U1zEwHZaaie07TkjmOOchurgnIh`）
|
||||||
|
- 内嵌 Sheet `wMQVyV`，剧本表 265 行 × 9 列（A=类型, B=ID, C=配置整理, D=剧情描述, E=角色名, F=英文台词, G=组件配置, H=知识点, I=编剧台词）
|
||||||
|
- 共 17 个互动行：对话朗读-配图(6) / 对话朗读(1) / 对话挖空-配图(1) / 对话挖空(4) / 对话选择-配图(1) / 对话选读(2) / 对话组句-配图(1) / 对话组句(1) / 看图说话(1)
|
||||||
|
|
||||||
|
#### 组件类型 A 列取值与技能映射（新增类型）
|
||||||
|
| A列类型 | 对应技能 | 备注 |
|
||||||
|
|---------|---------|------|
|
||||||
|
| 对话朗读 / 对话朗读-配图 | dialogue-reading-config | -配图需加图片时机和音频载体 |
|
||||||
|
| 对话挖空 / 对话挖空-配图 | dialogue-fill-in-blanks-config | 同上 |
|
||||||
|
| 对话选择 / 对话选择-配图 | dialogue-choose-config | 同上 |
|
||||||
|
| **对话选读** | dialogue-selective-reading-config | 开放表达，无正确选项，每选项必带反馈 |
|
||||||
|
| **对话组句** | dialogue-sentence-building-config | 单词排序组句，含答案+辅助信息 |
|
||||||
|
| **看图说话** | dialogue-image-description-config | 导览配置+对话配置，含Q&A/通过规则/示例对话 |
|
||||||
|
|
||||||
|
#### 类型区别关键点
|
||||||
|
- **对话选择 vs 对话选读**：前者有对错判断（正确选项标注），后者开放表达（无正确选项，每选项均带反馈）
|
||||||
|
- **对话挖空**：`___` 必需三下划线，选项2-3个，反馈角色非 User
|
||||||
|
- **对话组句**：选项为独立单词/短语，答案填完整正确句，必须有辅助信息
|
||||||
|
- **看图说话 v2.0**：结构最复杂，包含导览配置（任务标题/背景/描述/知识）+ 对话配置（角色/背景/Q&A/通过规则/示例对话）
|
||||||
|
- **-配图后缀**：资源配置需添加 `图片时机：互动内容\n互动反馈\n\n音频载体：Pioneer Band`
|
||||||
|
|
||||||
|
#### 写入脚本模式
|
||||||
|
- G 列写入使用 Python subprocess + curl（避免 shell 转义）
|
||||||
|
- SST = spreadsheet_token, SID = sheet_id（格式 `SST!G{row}:G{row}`）
|
||||||
|
- 写入后必须回读验证内容完整性
|
||||||
184
scripts/backfill_G_152_plus.py
Normal file
184
scripts/backfill_G_152_plus.py
Normal file
@ -0,0 +1,184 @@
|
|||||||
|
#!/usr/bin/env python3
|
||||||
|
"""Regenerate G column for all components from Row 152 onwards — strict skill formats."""
|
||||||
|
import subprocess, json
|
||||||
|
|
||||||
|
APP_SECRET = json.load(open('/root/.openclaw/credentials/xiaoyan/config.json'))['apps'][0]['appSecret']
|
||||||
|
r = subprocess.run(['curl', '-s', '-X', 'POST',
|
||||||
|
'https://open.feishu.cn/open-apis/auth/v3/tenant_access_token/internal',
|
||||||
|
'-H', 'Content-Type: application/json',
|
||||||
|
'-d', json.dumps({"app_id": "cli_a931175d41799cc7", "app_secret": APP_SECRET})],
|
||||||
|
capture_output=True, text=True)
|
||||||
|
TOKEN = json.loads(r.stdout)['tenant_access_token']
|
||||||
|
SST = 'DCcKsLbrmhfXgrtB7N2c9GA4ntf'
|
||||||
|
SID = 'wMQVyV'
|
||||||
|
|
||||||
|
configs = [
|
||||||
|
# === Row 161: 对话挖空 (1217511) ===
|
||||||
|
(161, """【任务标题】你明白了什么？
|
||||||
|
【资源配置】无
|
||||||
|
【情境引入】Ben : Speedy Monkey? School? Gift?
|
||||||
|
【互动内容】Ben! I think I ___!（音频）
|
||||||
|
选项1：understand（正确）
|
||||||
|
选项2：talk
|
||||||
|
【互动反馈】
|
||||||
|
正确 Ben : What do you understand?
|
||||||
|
错误 Ben : Think about the marks on the blackboard again.
|
||||||
|
【后置对话】无"""),
|
||||||
|
|
||||||
|
# === Row 168: 对话挖空 (1217512) ===
|
||||||
|
(168, """【任务标题】和 Ben 单独聊聊
|
||||||
|
【资源配置】无
|
||||||
|
【情境引入】Ben : What do you think it means?
|
||||||
|
【互动内容】We need to ___! You and me!（音频）
|
||||||
|
选项1：talk（正确）
|
||||||
|
选项2：point
|
||||||
|
【互动反馈】
|
||||||
|
正确 Ben : Okay. Let's figure this out together.
|
||||||
|
错误 Ben : We need to do more than just point. Let's talk.
|
||||||
|
【后置对话】无"""),
|
||||||
|
|
||||||
|
# === Row 181: 对话选读 (1217513) ===
|
||||||
|
(181, """【任务标题】向镇长求助
|
||||||
|
【资源配置】无
|
||||||
|
【情境引入】Ben : What should we do now?
|
||||||
|
【互动内容】
|
||||||
|
要求：选择一个你想表达的观点
|
||||||
|
选项：
|
||||||
|
选项1：We need to call Mayor Tom! Let's talk about it!
|
||||||
|
- 反馈 Ben : Good idea. Let's call him now!
|
||||||
|
选项2：We need to go find more proof first.
|
||||||
|
- 反馈 Ben : Hmm, we already have enough proof. Let's take action.
|
||||||
|
选项3：Let's keep watching the robot for now.
|
||||||
|
- 反馈 Ben : No, we need to do something fast!
|
||||||
|
【后置对话】无"""),
|
||||||
|
|
||||||
|
# === Row 194: 对话挖空 (1217514) ===
|
||||||
|
(194, """【任务标题】指给镇长看
|
||||||
|
【资源配置】无
|
||||||
|
【情境引入】Tom : Where is the spy?
|
||||||
|
【互动内容】Look! I ___ at it.（音频）
|
||||||
|
选项1：point（正确）
|
||||||
|
选项2：talk
|
||||||
|
【互动反馈】
|
||||||
|
正确 Tom : The robot? You think it is a spy?
|
||||||
|
错误 Tom : What are you doing? Show me.
|
||||||
|
【后置对话】无"""),
|
||||||
|
|
||||||
|
# === Row 207: 对话组句 (1217515) ===
|
||||||
|
(207, """【任务标题】给镇长看黑板上的证据
|
||||||
|
【资源配置】无
|
||||||
|
【情境引入】Tom : I don't understand. Anything else?
|
||||||
|
【互动内容】
|
||||||
|
题目：告诉镇长：你看，黑板上有很多奇怪的记号！
|
||||||
|
Look! Here are a lot of strange marks!（音频）
|
||||||
|
选项1：Look
|
||||||
|
选项2：Here
|
||||||
|
选项3：are
|
||||||
|
选项4：a lot of
|
||||||
|
选项5：strange
|
||||||
|
选项6：marks
|
||||||
|
答案：Look! Here are a lot of strange marks!
|
||||||
|
辅助信息：用 a lot of 表示"很多"；Look 引导祈使句
|
||||||
|
|
||||||
|
【互动反馈】
|
||||||
|
正确 Tom : Hmm, I see. Let me take a closer look.
|
||||||
|
错误 Tom : Try again. Use all the words to make a full sentence.
|
||||||
|
【后置对话】无"""),
|
||||||
|
|
||||||
|
# === Row 224: 对话选读 (1217516) ===
|
||||||
|
(224, """【任务标题】到底怎么回事？
|
||||||
|
【资源配置】无
|
||||||
|
【情境引入】Tom : The school isn't a gift to Speedy Monkey!
|
||||||
|
【互动内容】
|
||||||
|
要求：选择一个你想表达的观点
|
||||||
|
选项：
|
||||||
|
选项1：Wait. I don't understand.
|
||||||
|
- 反馈 Tom : Let these two workers explain everything.
|
||||||
|
选项2：Then what is the robot doing here?
|
||||||
|
- 反馈 Tom : Good question. Let the workers tell you.
|
||||||
|
选项3：I knew it was all wrong!
|
||||||
|
- 反馈 Tom : Yes, you were wrong. Now listen carefully.
|
||||||
|
【后置对话】无"""),
|
||||||
|
|
||||||
|
# === Row 245: 看图说话 (1217517) ===
|
||||||
|
(245, """【任务标题】向 Jay 和 Lin 道歉
|
||||||
|
|
||||||
|
【任务背景】
|
||||||
|
你之前误会了 Jay 和 Lin 是坏人，现在你需要向他们真诚道歉，表达你的歉意。
|
||||||
|
|
||||||
|
【任务描述】
|
||||||
|
你需要对 Jay 和 Lin 说出你的歉意和反思。
|
||||||
|
|
||||||
|
【知识】
|
||||||
|
I should talk to you. 我应该和你谈谈。
|
||||||
|
I should understand you. 我应该理解你。
|
||||||
|
I can understand you now. 我现在能理解你了。
|
||||||
|
|
||||||
|
【对话角色】
|
||||||
|
Lin, Jay
|
||||||
|
|
||||||
|
【角色背景】
|
||||||
|
你是 Lin 和 Jay，你们因为长相凶恶经常被误会。现在有两个孩子来向你们道歉了。
|
||||||
|
|
||||||
|
【互动问题】
|
||||||
|
#图片编号：00
|
||||||
|
Q: What do you want to say to us?
|
||||||
|
A: I should talk to you.
|
||||||
|
|
||||||
|
Q: What else?
|
||||||
|
A: I should understand you.
|
||||||
|
|
||||||
|
Q: And now?
|
||||||
|
A: I can understand you now.
|
||||||
|
|
||||||
|
【通过规则】
|
||||||
|
用户说出：
|
||||||
|
1. 我应该和你谈谈
|
||||||
|
2. 我应该理解你
|
||||||
|
3. 我现在能理解你了
|
||||||
|
|
||||||
|
【示例对话】
|
||||||
|
Lin: What do you want to say to us?
|
||||||
|
User: I should talk to you.
|
||||||
|
Jay: What else?
|
||||||
|
User: I should understand you.
|
||||||
|
Lin: And now?
|
||||||
|
User: I can understand you now.
|
||||||
|
Jay: Thank you. We feel much better.
|
||||||
|
Lin: I understand. We all make mistakes.""")
|
||||||
|
]
|
||||||
|
|
||||||
|
success = fail = 0
|
||||||
|
for row, text in configs:
|
||||||
|
cell = f"{SID}!G{row}:G{row}"
|
||||||
|
body = json.dumps({"valueRange": {"range": cell, "values": [[text]]}}, ensure_ascii=False)
|
||||||
|
r = subprocess.run(['curl', '-s', '-X', 'PUT',
|
||||||
|
f'https://open.feishu.cn/open-apis/sheets/v2/spreadsheets/{SST}/values',
|
||||||
|
'-H', f'Authorization: Bearer {TOKEN}',
|
||||||
|
'-H', 'Content-Type: application/json; charset=utf-8',
|
||||||
|
'-d', body], capture_output=True, text=True, timeout=10)
|
||||||
|
resp = json.loads(r.stdout)
|
||||||
|
title = text.split('\n')[0].replace('【任务标题】', '')
|
||||||
|
if resp.get('code') == 0:
|
||||||
|
success += 1
|
||||||
|
print(f' ✅ Row {row:3d} | {title}')
|
||||||
|
else:
|
||||||
|
fail += 1
|
||||||
|
print(f' ❌ Row {row:3d} | {resp.get("msg","?")}')
|
||||||
|
|
||||||
|
print(f'\n写入结果：{success}成功 / {fail}失败')
|
||||||
|
|
||||||
|
if fail == 0:
|
||||||
|
print('\n=== 回读验证 ===')
|
||||||
|
import re
|
||||||
|
for row, _ in configs:
|
||||||
|
cell = f"{SID}!G{row}:G{row}"
|
||||||
|
r = subprocess.run(['curl', '-s', '-X', 'GET',
|
||||||
|
f'https://open.feishu.cn/open-apis/sheets/v2/spreadsheets/{SST}/values/{cell}?valueRenderOption=ToString',
|
||||||
|
'-H', f'Authorization: Bearer {TOKEN}'], capture_output=True, text=True, timeout=10)
|
||||||
|
resp = json.loads(r.stdout)
|
||||||
|
vals = resp.get('data',{}).get('valueRange',{}).get('values',[[]])
|
||||||
|
content = vals[0][0] if vals and vals[0] else ''
|
||||||
|
m = re.search(r'【任务标题】([^\n]*)', content)
|
||||||
|
title = m.group(1) if m else '(empty)'
|
||||||
|
print(f' ✅ Row{row}: {title}')
|
||||||
215
scripts/write_L5_G_configs_v2.py
Normal file
215
scripts/write_L5_G_configs_v2.py
Normal file
@ -0,0 +1,215 @@
|
|||||||
|
#!/usr/bin/env python3
|
||||||
|
"""Generate G列 component configs for L1-S2-U17-L5 笨蛋坏蛋？(v2 — updated row numbers)"""
|
||||||
|
import subprocess, json
|
||||||
|
|
||||||
|
APP_SECRET = json.load(open('/root/.openclaw/credentials/xiaoyan/config.json'))['apps'][0]['appSecret']
|
||||||
|
r = subprocess.run(['curl', '-s', '-X', 'POST',
|
||||||
|
'https://open.feishu.cn/open-apis/auth/v3/tenant_access_token/internal',
|
||||||
|
'-H', 'Content-Type: application/json',
|
||||||
|
'-d', json.dumps({"app_id": "cli_a931175d41799cc7", "app_secret": APP_SECRET})],
|
||||||
|
capture_output=True, text=True)
|
||||||
|
TOKEN = json.loads(r.stdout)['tenant_access_token']
|
||||||
|
SST = 'DCcKsLbrmhfXgrtB7N2c9GA4ntf'
|
||||||
|
SID = 'wMQVyV'
|
||||||
|
|
||||||
|
# ===== 对话朗读 (6) =====
|
||||||
|
# ===== 对话挖空 (3) =====
|
||||||
|
# ===== 互动 (7) =====
|
||||||
|
# ===== 核心互动-口语 (1) =====
|
||||||
|
|
||||||
|
configs = [
|
||||||
|
# --- 对话朗读 ---
|
||||||
|
(14, """【任务标题】机器人在指向什么？
|
||||||
|
【资源配置】图片时机：无
|
||||||
|
【情境引入】Ben : It points at something!
|
||||||
|
【互动内容】It points at the blackboard.（朗读）
|
||||||
|
【后置对话】Ben : That's right. And it also talks a lot!"""),
|
||||||
|
|
||||||
|
(29, """【任务标题】机器人在自言自语吗？
|
||||||
|
【资源配置】图片时机：无
|
||||||
|
【情境引入】Robot : Bip bop! Bip bop bip!
|
||||||
|
【互动内容】Hmm, it talks to itself.（朗读）
|
||||||
|
【后置对话】Ben : ...in a language we can't understand!"""),
|
||||||
|
|
||||||
|
(42, """【任务标题】机器人为什么走不动？
|
||||||
|
【资源配置】图片时机：无
|
||||||
|
【情境引入】Ben : What is it doing now?
|
||||||
|
【互动内容】But a lot of our desks block it.（朗读）
|
||||||
|
【后置对话】Ben : Yes! The desks are in its way."""),
|
||||||
|
|
||||||
|
(66, """【任务标题】我们该怎么办？
|
||||||
|
【资源配置】图片时机：无
|
||||||
|
【情境引入】Ben : Fine. You're right. What should we do now?
|
||||||
|
【互动内容】Let's talk to it!（朗读）
|
||||||
|
【后置对话】Ben : Talk to it? But it's a robot!"""),
|
||||||
|
|
||||||
|
(77, """【任务标题】你能听懂机器人吗？
|
||||||
|
【资源配置】图片时机：无
|
||||||
|
【情境引入】Robot : Bip bop!
|
||||||
|
【互动内容】We can't understand it.（朗读）
|
||||||
|
【后置对话】Ben : What's your name?"""),
|
||||||
|
|
||||||
|
(89, """【任务标题】你明白了什么？
|
||||||
|
【资源配置】图片时机：无
|
||||||
|
【情境引入】Robot points at the number "11" on its chest.
|
||||||
|
【互动内容】Oh, I understand!（朗读）
|
||||||
|
【后置对话】Ben : You understand? Tell me!"""),
|
||||||
|
|
||||||
|
# --- 对话挖空 ---
|
||||||
|
(96, """【任务标题】指出机器人的名字
|
||||||
|
【资源配置】无
|
||||||
|
【情境引入】Ben : Wow, it is pointing at itself!
|
||||||
|
【互动内容】It ___ to its name.（音频）
|
||||||
|
选项1：points（正确）
|
||||||
|
选项2：talks
|
||||||
|
【互动反馈】
|
||||||
|
正确 Ben : Yes! It points to its name. Its name is 11!
|
||||||
|
错误 Ben : What is the robot doing? Think again.
|
||||||
|
【后置对话】User : Its name is 11! We call it 11!"""),
|
||||||
|
|
||||||
|
(119, """【任务标题】机器人想做什么？
|
||||||
|
【资源配置】无
|
||||||
|
【情境引入】Robot draws on the blackboard.
|
||||||
|
【互动内容】Oh! It tries to ___ to us.（音频）
|
||||||
|
选项1：talk（正确）
|
||||||
|
选项2：point
|
||||||
|
【互动反馈】
|
||||||
|
正确 Ben : Yes! It wants to talk with pictures!
|
||||||
|
错误 Ben : It is not pointing. What else?
|
||||||
|
【后置对话】Ben : That is the Speedy Monkey logo!"""),
|
||||||
|
|
||||||
|
(138, """【任务标题】机器人又指了什么？
|
||||||
|
【资源配置】无
|
||||||
|
【情境引入】Robot draws a school mark on the blackboard.
|
||||||
|
【互动内容】It ___ at another mark.（音频）
|
||||||
|
选项1：points（正确）
|
||||||
|
选项2：talks
|
||||||
|
【互动反馈】
|
||||||
|
正确 Ben : Is that... a school?
|
||||||
|
错误 Ben : Look at what the robot is doing with the mark.
|
||||||
|
【后置对话】Ben : Is that a school?"""),
|
||||||
|
|
||||||
|
# --- 互动 ---
|
||||||
|
(150, """【任务标题】又是什么标记？
|
||||||
|
【资源配置】无
|
||||||
|
【情境引入】Robot draws a gift mark on the blackboard.
|
||||||
|
【互动内容】It points at another mark.
|
||||||
|
KP：point — v. 指向
|
||||||
|
【互动反馈】
|
||||||
|
正确 → Ben : It is a gift!
|
||||||
|
错误 → Ben : Look at the mark. What is it?
|
||||||
|
【后置对话】Ben : Speedy Monkey? School? Gift?"""),
|
||||||
|
|
||||||
|
(161, """【任务标题】你发现了什么？
|
||||||
|
【资源配置】无
|
||||||
|
【情境引入】Ben : Speedy Monkey? School? Gift?
|
||||||
|
【互动内容】Ben! I think I understand!
|
||||||
|
KP：understand — v. 理解
|
||||||
|
【互动反馈】
|
||||||
|
正确 → Ben : What do you understand?
|
||||||
|
错误 → Ben : Look at the marks again.
|
||||||
|
【后置对话】User explains the spy theory"""),
|
||||||
|
|
||||||
|
(168, """【任务标题】和 Ben 单独商量
|
||||||
|
【资源配置】无
|
||||||
|
【情境引入】User thinks the robot is a spy.
|
||||||
|
【互动内容】We need to talk! You and me!
|
||||||
|
KP：talk — v. 说话
|
||||||
|
【互动反馈】
|
||||||
|
正确 → Ben : Okay! Let's figure this out.
|
||||||
|
错误 → Ben : We need to talk about what we found!
|
||||||
|
【后置对话】User : Vala School is a gift to Speedy Monkey!"""),
|
||||||
|
|
||||||
|
(181, """【任务标题】快告诉镇长！
|
||||||
|
【资源配置】无
|
||||||
|
【情境引入】Ben : What should we do now?
|
||||||
|
【互动内容】We need to call Mayor Tom! Let's talk about it!
|
||||||
|
KP：talk about... — 谈论...
|
||||||
|
【互动反馈】
|
||||||
|
正确 → Ben : Good idea. Let's call him now!
|
||||||
|
错误 → Ben : Who should we call for help?
|
||||||
|
【后置对话】Calling Mayor Tom..."""),
|
||||||
|
|
||||||
|
(194, """【任务标题】指给镇长看
|
||||||
|
【资源配置】无
|
||||||
|
【情境引入】Tom : So you kids want to talk to me?
|
||||||
|
【互动内容】Look! I point at it.
|
||||||
|
KP：point — v. 指向
|
||||||
|
【互动反馈】
|
||||||
|
正确 → Tom : The robot?
|
||||||
|
错误 → Tom : What are you pointing at?
|
||||||
|
【后置对话】Tom : Oh? A spy? In the classroom?"""),
|
||||||
|
|
||||||
|
(207, """【任务标题】给镇长看证据
|
||||||
|
【资源配置】无
|
||||||
|
【情境引入】Tom : I don't understand. Anything else?
|
||||||
|
【互动内容】Look! Here are a lot of strange marks!
|
||||||
|
KP：a lot of — det. 大量的
|
||||||
|
【互动反馈】
|
||||||
|
正确 → Tom : Hmm, I see.
|
||||||
|
错误 → Tom : Are there many strange marks?
|
||||||
|
【后置对话】User shows the blackboard to Tom"""),
|
||||||
|
|
||||||
|
(224, """【任务标题】到底怎么回事？
|
||||||
|
【资源配置】无
|
||||||
|
【情境引入】Tom : The school isn't a gift to Speedy Monkey!
|
||||||
|
【互动内容】Wait. I don't understand.
|
||||||
|
KP：I can/can't understand...
|
||||||
|
【互动反馈】
|
||||||
|
正确 → Lin : Why not let it tell you itself?
|
||||||
|
错误 → Lin : Let me help you understand.
|
||||||
|
【后置对话】Lin fixes the robot"""),
|
||||||
|
|
||||||
|
# --- 核心互动-口语 ---
|
||||||
|
(245, """【任务标题】向 Jay 和 Lin 道歉
|
||||||
|
【资源配置】无
|
||||||
|
【情境引入】Tom : Kids, do you have something to say?
|
||||||
|
【互动内容】
|
||||||
|
（口语表达）
|
||||||
|
I should talk to you.
|
||||||
|
I should understand you.
|
||||||
|
I can understand you now.
|
||||||
|
KP：talk / understand
|
||||||
|
【互动反馈】
|
||||||
|
正确 → Jay : Thank you. We feel much better now.
|
||||||
|
错误 → Lin : Go on. Say what's in your heart.
|
||||||
|
【后置对话】Jay : I understand. Lin : We all make mistakes."""),
|
||||||
|
]
|
||||||
|
|
||||||
|
# Write
|
||||||
|
success = fail = 0
|
||||||
|
for row, text in configs:
|
||||||
|
cell = f"{SID}!G{row}:G{row}"
|
||||||
|
body = json.dumps({"valueRange": {"range": cell, "values": [[text]]}}, ensure_ascii=False)
|
||||||
|
r = subprocess.run(['curl', '-s', '-X', 'PUT',
|
||||||
|
f'https://open.feishu.cn/open-apis/sheets/v2/spreadsheets/{SST}/values',
|
||||||
|
'-H', f'Authorization: Bearer {TOKEN}',
|
||||||
|
'-H', 'Content-Type: application/json; charset=utf-8',
|
||||||
|
'-d', body], capture_output=True, text=True, timeout=15)
|
||||||
|
resp = json.loads(r.stdout)
|
||||||
|
if resp.get('code') == 0:
|
||||||
|
success += 1
|
||||||
|
title = text.split('\n')[0].replace('【任务标题】', '')
|
||||||
|
print(f' ✅ Row {row:3d} | {title}')
|
||||||
|
else:
|
||||||
|
fail += 1
|
||||||
|
print(f' ❌ Row {row:3d} | {resp.get("msg","?")}')
|
||||||
|
print(f' debug: {r.stdout[:200]}')
|
||||||
|
|
||||||
|
print(f'\n写入结果：{success}成功 / {fail}失败')
|
||||||
|
|
||||||
|
if fail == 0:
|
||||||
|
print('\n=== 回读验证 ===')
|
||||||
|
for row, _ in configs:
|
||||||
|
cell = f"{SID}!G{row}:G{row}"
|
||||||
|
r = subprocess.run(['curl', '-s', '-X', 'GET',
|
||||||
|
f'https://open.feishu.cn/open-apis/sheets/v2/spreadsheets/{SST}/values/{cell}?valueRenderOption=ToString',
|
||||||
|
'-H', f'Authorization: Bearer {TOKEN}'], capture_output=True, text=True, timeout=15)
|
||||||
|
resp = json.loads(r.stdout)
|
||||||
|
vals = resp.get('data',{}).get('valueRange',{}).get('values',[[]])
|
||||||
|
content = vals[0][0] if vals and vals[0] else None
|
||||||
|
title = content.split('\n')[0].replace('【任务标题】', '') if content else 'EMPTY'
|
||||||
|
status = '✅' if content else '❌ EMPTY'
|
||||||
|
print(f' {status} Row{row}: {title}')
|
||||||
|
else:
|
||||||
|
print('\n⚠️ 有失败项，请检查')
|
||||||
Loading…
Reference in New Issue
Block a user