补上结束页和封面，收尾第 2 讲

补一页像第 1 讲那样的课堂结束页，不照抄，概念与上一讲保持一致；提交 MR。你合并后又发现第 2 讲没有封面，补上后直接推到 main，79 分钟。

10:35
我觉得还是要加一个类似于第一讲那种课堂结束页，总结一下课堂内容，并且将所有概念再列一遍
我会参照第一讲的课堂总结页，在 Q&A 前补一页：回顾第二讲的内容，并列出正式引入的概念及其关系。

干了不到 1 分钟，3 步

运行 3 条命令

10:35:49运行 git status --short; tail -65 slides/01.md; tail -55 slides/02.md; cat slides/AGENTS.md; rg -n '课堂总结|概念|结束|正式引入' 'cou…

text(await tools.exec_command({cmd:"git status --short; tail -65 slides/01.md; tail -55 slides/02.md; cat slides/AGENTS.md; rg -n '课堂总结|概念|结束|正式引入' 'course/课程内容/02 - 从「回答」到「执行」.md' 'course/课程内容/02/2.2.md'; rg -n 'lesson-summary|course-conclusion' slides/styles/index.css","max_output_tokens":5300}));

Script completed
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Output:

{"chunk_id":"847fcf","wall_time_seconds":0.000004125,"exit_code":0,"original_token_count":2833,"output":" D \"course/\\347\\264\\240\\346\\235\\220\\344\\270\\216\\350\\215\\211\\347\\250\\277/03.md\"\n?? \"course/\\350\\257\\276\\347\\250\\213\\345\\206\\205\\345\\256\\271/03 - \\344\\270\\200\\346\\227\\245\\351\\241\\276\\351\\227\\256.md\"\n## 为什么这样的回答仍然可能不可靠\n\n<div class=\"abs-tr m-6 px-2 py-1

…（中间省略 5459 字）…

6:.course-conclusion .course-conclusion__support { margin: 0; font-size: 18px; font-weight: 400; line-height: 1.5; }\n"}

10:36:03运行 cat slides/pages/01/4.3.md; sed -n '35,90p' 'course/课程内容/01 - AI 是这么说的.md'; sed -n '9,20p' course/课程内容/02/2.2.md; se…

text(await tools.exec_command({cmd:"cat slides/pages/01/4.3.md; sed -n '35,90p' 'course/课程内容/01 - AI 是这么说的.md'; sed -n '9,20p' course/课程内容/02/2.2.md; sed -n '1,25p' slides/pages/02/2.2.md; rg -n '课堂总结|summary' ~/.codex/memories/MEMORY.md | head -4; git branch --show-current","max_output_tokens":4100}));

Script completed
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Output:

{"chunk_id":"d46f19","wall_time_seconds":0.000002083,"exit_code":0,"original_token_count":3649,"output":"---\nlayout: default\ntitle: AI 是这么说的不是论据\n---\n\n# 4.3「AI 是这么说的」不是论据 <span>— 信源要自己核对，结论要自己推导</span>\n\n<div class=\"abs-tr\"><span class=\"bg-[#FB8F68]/15 text-[#C85F3C]\">重点</span></div>\n\n<section class=\"relative mx-auto mt-3 h-[500px] w-[1120px]\">\n<div class=\"absolute left-0 top-[16px] h

…（中间省略 10025 字）…

rollout_summary_files\n41:### rollout_summary_files\n57:### rollout_summary_files\nfeat/lesson-02-authoring-workflow\n"}

10:36:12运行 rg -n -A55 -B4 '课堂总结|lesson-summary' slides/01.md; sed -n '1,40p' 'course/课程内容/02 - 从「回答」到「执行」.md'; sed -n '1,35p' s…

text(await tools.exec_command({cmd:"rg -n -A55 -B4 '课堂总结|lesson-summary' slides/01.md; sed -n '1,40p' 'course/课程内容/02 - 从「回答」到「执行」.md'; sed -n '1,35p' slides/DESIGN.md; rg -n '总结|本轮|七页|Q&A|结束页' slides/02-plan.md; sed -n '1,42p' ~/.codex/skills/slidev/SKILL.md","max_output_tokens":1700}));

Script completed
Wall time 0.1 seconds
Output:

{"chunk_id":"0b368d","wall_time_seconds":0.000003458,"exit_code":0,"original_token_count":1753,"output":"Warning: truncated output (original token count: 1753)\nTotal output lines: 118\n\n---\naliases: \ntags: \ndate: 2026-09-03\nmodified: 2026-09-06\nstatus: 七页正文与两页过渡已制作；结束页待审阅，单页效果以各任务确认状态为准\n---\n\n> [!abstract] 本讲定位\n> 第一讲建立模型的核心认识，第二讲让同事看到：模型接上可操作的工具后，可以通过 Agent Loop 连续推进实际工作，由此打开想象力。Agent 是整体系

…（中间省略 3896 字）…

ot.\n\n## Basic Syntax\n\n```md\n---\ntheme: default\ntitle: My Presentation\n---\n\n# First Slide\n\nContent here\n\n"}

这一页会用朴素的左右两栏：左边回顾“工作方式的变化、Agent 的原理、能力与控制的取舍”，右边重列 Agent、工具调用、Agent Loop，并说明 Tool 在其中的作用。所有内容一次展示，方便课堂最后回看。

干了 3 分钟，8 步

运行 6 条命令，写 1 个文件，其他操作 3 次

10:36:34运行 cat ~/.codex/skills/slidev/references/layout-slots.md; rg -n 'lesson-summary|::left::|::right::' slide…

text(await tools.exec_command({cmd:"cat ~/.codex/skills/slidev/references/layout-slots.md; rg -n 'lesson-summary|::left::|::right::' slides/01.md slides/pages/01/*.md | head -10; sed -n '1,70p' node_modules/.pnpm/@slidev+client@51.8.2_@nuxt+kit@3.21.11_@vue+compiler-sfc@3.5.42_markdown-it-async@2.2._7737a783d5eec247a9a3c098b443b869/node_modules/@slidev/client/layouts/two-cols-header.vue; tail -17 'course/课程内容/02 - 从「回答」到「执行」.md'","max_output_tokens":1500}));

Script completed
Wall time 0.1 seconds
Output:

{"chunk_id":"fc62a4","wall_time_seconds":0.000003833,"exit_code":0,"original_token_count":725,"output":"---\nname: slot-sugar\ndescription: Shorthand syntax for layout named slots in multi-column layouts\n---\n\n# Slot Sugar for Layouts\n\nShorthand syntax for layout named slots.\n\n## Standard Vue Slot Syntax\n\n```md\n---\nlayout: two-cols\n---\n\n<template v-slot:default>\n\n# Left\n\nThis shows 

…（中间省略 2127 字）…

\n> 使用已有 `end` 布局与浅色背景，以「Q&A」为标题，显示上述收束句与「感谢聆听！欢迎提问和讨论」。初始即最终状态，不设 Click，不追加新概念或下一讲预定目录。概念回顾保留在讲师备注，衔接 3.3 的能力与控制取舍。\n"}

10:37:04运行 rg -n '对齐|授权|概念|🆕|定义' course/课程内容/02/{3.1,3.2,3.3}.md slides/pages/02/{3.1,3.2,3.3}.md | head -22; git log -1 --one…

text(await tools.exec_command({cmd:"rg -n '对齐|授权|概念|🆕|定义' course/课程内容/02/{3.1,3.2,3.3}.md slides/pages/02/{3.1,3.2,3.3}.md | head -22; git log -1 --oneline","max_output_tokens":1400}));

Script completed
Wall time 0.1 seconds
Output:

{"chunk_id":"291c20","wall_time_seconds":0.000003125,"exit_code":0,"original_token_count":1962,"output":"Warning: truncated output (original token count: 1962)\nTotal output lines: 23\n\nslides/pages/02/3.3.md:71:<span class=\"course-conclusion__support\">有限授权能限制影响范围，结果是否正确仍需判断。</span>\nslides/pages/02/3.3.md:89:[click] 让 Agent 在明确范围内把工作做下去，把关键决定留给人。有限授权能限制影响范围，结果是否正确仍需判断。第一讲认识模型的能力与局限，这一讲看见工具调用带来行动

…（中间省略 2086 字）…

依次形成对比；同类窗口重复视觉规则，不同设备保留可辨认外形。教学物件非产品实录，不显示未经核实的项目结果。\nf12c605 docs(course): separate research from slide production\n"}

10:37:39运行 python3 - <<'PY'

text(await tools.exec_command({cmd:"python3 - <<'PY'\nfrom pathlib import Path\np=Path('~/Library/Mobile Documents/iCloud~md~obsidian/Documents/Note/Areas/大模型(LLM)/AI 通识课程/课程内容/02 - 从「回答」到「执行」.md')\ns=p.read_text();assert '## 4 课堂总结' not in s\ns=s.replace('modified: 2026-09-06','modified: 2026-09-07').replace('status: 七页正文与两页过渡已制作；结束页待审阅，单页效果以各任务确认状态为准','status: 七页正文、两页过渡、课堂总结与 Q&A 已制作；新增总结页待审阅')\nsummary='''## 4 课堂总结\n\n> [!abstract] 为什么需要这一页\n>

…（中间省略 1081 字）…

ibrary/Mobile Documents/iCloud~md~obsidian/Documents/Note/Areas/大模型(LLM)/AI 通识课程/' course/","max_output_tokens":700}));

Script completed
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Output:

{"chunk_id":"60ee9a","wall_time_seconds":0.00000325,"exit_code":0,"original_token_count":140,"output":"Transfer starting: 45 files\n.d..t.... ./\n.d..t.... 素�\\#235\\#220�\\#216�\\#215\\#211稿/\n>f.st.... 素�\\#235\\#220�\\#216�\\#215\\#211稿/02-第�\\#214讲�\\#234��\\#207\\#207�\\#224�素�\\#235\\#220.md\n.d..t.... 课�\\#213�\\#206\\#205容/\n>f.st.... 课�\\#213�\\#206\\#205容/02 - �\\#216�\\#200\\#214�\\#233\\

…（中间省略 154 字）…

.t.... 课�\\#213设计/\n\nsent 2457 bytes  received 62 bytes  2290000 bytes/sec\ntotal size is 263300  speedup is 104.53\n"}

10:38:07运行 ./scripts/sync-course.sh 等 2 条命令；写入 02.md

text(await tools.exec_command({cmd:"./scripts/sync-course.sh","max_output_tokens":300}));
text(await tools.apply_patch("*** Begin Patch\n*** Update File: ~/code/ai-literacy-series/slides/02.md\n@@\n src: ./pages/02/3.3.md\n ---\n \n+---\n+layout: two-cols-header\n+title: 课堂总结\n+class: lesson-summary\n+layoutClass: gap-x-12\n+clicks: 0\n+---\n+\n+# 4 课堂总结\n+\n+::left::\n+\n+## 这节课回答了什么\n+\n+1. **工作方式发生了什么变化？**  \n+   Agent 接着读取、处理和保存材料，减少人的来回交接。\n

…（中间省略 853 字）…

y-02-class-summary > /tmp/ai-literacy-02-class-summary-build.log 2>&1","yield_time_ms":1000,"max_output_tokens":300}));

Script completed
Wall time 1.2 seconds
Output:

{"chunk_id":"870aef","wall_time_seconds":0.000003708,"exit_code":0,"original_token_count":0,"output":""}
{}
{"chunk_id":"3b205d","wall_time_seconds":1.001927583,"session_id":48739,"original_token_count":0,"output":""}

10:38:28连接第二讲预览

{
  "code": "let ppt = await cua.getTab(\"1\", { browser: \"1\" });",
  "title": "连接第二讲预览"
}

Wall time: 0.4714 seconds
Output:
## Computer Use

Control native apps and browsers on the user’s computer by reading or operating UI. Prefer purpose-built connectors, APIs, or CLIs when available.

- Use `cua_repl` (JavaScript) for all UI actions.
- Do not use other technologies besides `cua_repl` for computer interactions, unless specifically requested by the user (e.g. AppleScript, `osascript`, JXA, System Events, CGEvent synthesis).
- Prefer 

…（中间省略 51560 字）…

e Options
				34 text 9  / 11

The focused UI element is 0 AXWebArea 从「回答」到「执行」 - Slidev, URL: localhost:3032/9?clicks=7

10:38:41运行 tail -2 /tmp/ai-literacy-02-class-summary-build.log; git diff --stat -- slides/02.md 'course/课程内容/02 - 从「回答」到「执行」.md…

text(await tools.write_stdin({session_id:48739,chars:"","yield_time_ms":1000,"max_output_tokens":400}));
text(await tools.exec_command({cmd:"tail -2 /tmp/ai-literacy-02-class-summary-build.log; git diff --stat -- slides/02.md 'course/课程内容/02 - 从「回答」到「执行」.md'; python3 - <<'PY'\nfrom pathlib import Path\nsrc=Path('~/Library/Mobile Documents/iCloud~md~obsidian/Documents/Note/Areas/大模型(LLM)/AI 通识课程/课程内容/02 - 从「回答」到「执行」.md')\nassert src.read_bytes()==Path('course/课程内容/02 - 从「回答」到「执行」.md').read_bytes()\nprint('第二讲源与镜像一致')\nPY","max_output_tokens":450}));

Script completed
Wall time 0.1 seconds
Output:

{"chunk_id":"4faebb","wall_time_seconds":0.000002125,"exit_code":0,"original_token_count":0,"output":""}
{"chunk_id":"974a93","wall_time_seconds":0.000001958,"exit_code":0,"original_token_count":101,"output":"../../../../../tmp/ai-literacy-02-class-summary/assets/modules/vue-FxgGn04Y.js                                             258.67 kB │ gzip: 96.71 kB\n✓ built in 1.43s\n ...200\\214\\346\\211\\

…（中间省略 88 字）…

                          | 44 ++++++++++++++++++++++\n 2 files changed, 73 insertions(+), 3 deletions(-)\n第二讲源与镜像一致\n"}

10:38:48打开新增的课堂总结页

{
  "code": "await ppt.goto(\"http://localhost:3032/10\"); await ppt.getAXState();",
  "title": "打开新增的课堂总结页"
}

Wall time: 0.3645 seconds
Output:
Browser tab: 1, Title: "从「回答」到「执行」 - Slidev", URL: "http://localhost:3032/10".
1 AXWebArea 从「回答」到「执行」 - Slidev, URL: localhost:3032/10
	2 container app
		3 container slide-container
			4 container slide-content
				5 container
					6 heading 4 课堂总结, Value: 1
					7 heading 这节课回答了什么, Value: 2
					8 heading 本讲学到的概念, Value: 2
				9 image
			10 container
				11 button Enter fullscreen
				12 button Go to previous sl

…（中间省略 314 字）…

ton More Options
				22 text 10  / 11

The focused UI element is 1 AXWebArea 从「回答」到「执行」 - Slidev, URL: localhost:3032/10

10:38:54检查总结两栏的内容完整性和排版

{
  "code": "await ppt.getAXStateAndScreenshot();",
  "title": "检查总结两栏的内容完整性和排版"
}

Wall time: 0.1954 seconds
Output:
Browser tab: 1, Title: "从「回答」到「执行」 - Slidev", URL: "http://localhost:3032/10".
1 AXWebArea 从「回答」到「执行」 - Slidev, URL: localhost:3032/10
	2 container app
		3 container slide-container
			4 container slide-content
				5 container
					6 heading 4 课堂总结, Value: 1
						23 text 4 课堂总结
					7 heading 这节课回答了什么, Value: 2
						24 text 这节课回答了什么
					25 content list
						26 container
							27 AXListMarker 1. 
							28 te

…（中间省略 1239 字）…

ore Options
				22 text 10  / 11

The focused UI element is 1 AXWebArea 从「回答」到「执行」 - Slidev, URL: localhost:3032/10
[图片]

10:39:17思考：**Checking browser viewport**
Checking browser viewport

总结页已加入，讲稿已同步，第二讲构建通过。课堂主线和概念都已完整展示；我再检查一下阅读尺寸与前后翻页效果。

干了不到 1 分钟，3 步

其他操作 3 次

10:39:21读取 PPT 预览尺寸控制方式

{
  "code": "let previewBrowser = await cua.getBrowser({ id: \"1\" }); nodeRepl.write(await (await previewBrowser.capabilities.get(\"viewport\")).documentation());",
  "title": "读取 PPT 预览尺寸控制方式"
}

Wall time: 0.0953 seconds
Output:
# Browser Capability: viewport
Browser viewport override control. Do not set the viewport during normal browser setup; most tasks should use the existing/default viewport. Use `set()` only when the user asks for specific dimensions, asks to test a responsive breakpoint or device size, or the task cannot be answered correctly without a specific viewport. Do not resize the browser just to make a screenshot larger, 

…（中间省略 477 字）…

fault browser sizing.
  set(options: ViewportSize): Promise<void>; // Apply an explicit browser viewport override.
}
```

10:39:37检查正文边界并翻到 Q&A

{
  "code": "nodeRepl.write(await ppt.playwright.evaluate(() => { const page = document.querySelector('.slidev-page-10 .slidev-layout') || document.querySelector('.slidev-layout.two-cols-header'); if (!page) return {found:false}; const box = page.getBoundingClientRect(); return {found:true, font:getComputedStyle(page).fontSize, overflow:page.scrollHeight>page.clientHeight, columns:[...page.querySelectorAll('.col-left,.col-right')].map(e=>({width:

…（中间省略 217 字）…

.map(e=>e.textContent)}; })); await ppt.pressKey(\"ArrowRight\"); await ppt.getAXState();",
  "title": "检查正文边界并翻到 Q&A"
}

Wall time: 0.2876 seconds
Output:
Browser tab: 1, Title: "从「回答」到「执行」 - Slidev", URL: "http://localhost:3032/11".
1 AXWebArea 从「回答」到「执行」 - Slidev, URL: localhost:3032/11
	2 container app
		3 container slide-container
			4 container slide-content
				23 container slideshow
					24 container
						25 heading 4 课堂总结, Value: 1
							26 text 4 课堂总结
						27 heading 这节课回答了什么, Value: 2
							28 text 这节课回答了什么
						29 content list
							30 container
		

…（中间省略 1616 字）…

eight: 538, scrollHeight: 538, width: 560 }
  ],
  font: '17.6px',
  found: true,
  overflow: false,
  textOutside: []
}

10:39:48回到课堂总结页供审阅

{
  "code": "await ppt.pressKey(\"ArrowLeft\"); await ppt.getAXState(); await ppt.markDeliverable();",
  "title": "回到课堂总结页供审阅"
}

Wall time: 0.2594 seconds
Output:
Browser tab: 1, Title: "从「回答」到「执行」 - Slidev", URL: "http://localhost:3032/10".
The following is a diff from the previous accessibility tree with ~ and + representing changed and added elements, respectively. Removed elements are summarized by ID range.
Removed element IDs: 31, 35, 39, 47, 51, 55
~1 AXWebArea 从「回答」到「执行」 - Slidev, URL: localhost:3032/10
+								63 AXListMarker 1. 
+								64 AXListMarker 2. 
+			

…（中间省略 92 字）…

 AXListMarker ■ 
~				22 text 10  / 11
The focused UI element is 1 AXWebArea 从「回答」到「执行」 - Slidev, URL: localhost:3032/10

已加好：查看课堂总结页。
- 左栏回顾整讲的三个问题与结论。
- 右栏重列 Agent、Tool、工具调用、Agent Loop 及其关系。
- 全部一次展示，后接 Q&A。
讲稿已同步，构建和浏览器检查通过，效果待你审阅。
你看看第一讲是如何写的？
10:40
我先对照第一讲的实际写法，看看这页在内容和呈现上哪里偏离了。

干了不到 1 分钟，1 步

运行 1 条命令

10:40:39运行 rg -n -A42 -B5 '课堂总结|这节课回答了什么|本讲学到的概念' slides/01.md slides/pages/01/*.md 'course/课程内容/01 - AI 是这么说的.md'; sed -n '85,…

text(await tools.exec_command({cmd:"rg -n -A42 -B5 '课堂总结|这节课回答了什么|本讲学到的概念' slides/01.md slides/pages/01/*.md 'course/课程内容/01 - AI 是这么说的.md'; sed -n '85,131p' slides/02.md","max_output_tokens":2200}));

Script completed
Wall time 0.1 seconds
Output:

{"chunk_id":"730194","wall_time_seconds":0.000003583,"exit_code":0,"original_token_count":1455,"output":"course/课程内容/01 - AI 是这么说的.md-37-\ncourse/课程内容/01 - AI 是这么说的.md-38-[[课程内容/01/4.2]]\ncourse/课程内容/01 - AI 是这么说的.md-39-\ncourse/课程内容/01 - AI 是这么说的.md-40-[[课程内容/01/4.3]]\ncourse/课程内容/01 - AI 是这么说的.md-41-\ncourse/课程内容/01 - AI 是这么说的.md:42:## 5 课堂总结\ncourse/课程内容/01 - AI 是这么说的.md-43-\ncourse/课程内容/01 - AI 

…（中间省略 2622 字）…

模型与 Context 沿用第一讲的概念，不作为本讲新增术语。\n\n本页只回顾已讲内容，定义与依据沿用 2.2，不补充新概念或产品事实。能继续执行不保证正确，有限授权也不能代替人的判断。接下来进入 Q&A。\n-->\n\n---\n"}

第一讲的课堂总结写法很简洁：
- 左栏：三个问题，最后一句课程结论。
- 右栏：只列概念名称。
- 具体解释留在讲稿，页面不加卡片或 Click。
我刚才给每个问题加了回答、给每个概念加了定义，右栏又补了一段总结，确实没有遵循这个写法。第二讲也应收回到“三个问题＋一句结论／概念清单”的结构。
看一下 PPT
我打开第一讲的实际 PPT，对照看一下收尾页。

干了不到 1 分钟，4 步

其他操作 4 次

10:41:14查看第一讲实际收尾页

{
  "code": "let firstDeck = await cua.createBrowserTab(\"iab\", \"http://localhost:3030/15\", { visible: false });",
  "title": "查看第一讲实际收尾页"
}

Wall time: 0.3726 seconds
Output:
Browser tab: 2, Title: "AI æ˜¯è¿™ä¹ˆè¯´çš„ - Slidev", URL: "http://localhost:3030/15".
0 AXWebArea AI æ˜¯è¿™ä¹ˆè¯´çš„ - Slidev, URL: localhost:3030/15

The focused UI element is 0 AXWebArea AI æ˜¯è¿™ä¹ˆè¯´çš„ - Slidev, URL: localhost:3030/15

10:41:21读取第一讲 PPT 的实际画面

{
  "code": "await firstDeck.getAXStateAndScreenshot();",
  "title": "读取第一讲 PPT 的实际画面"
}

Wall time: 0.3589 seconds
Output:
Browser tab: 2, Title: "AI 是这么说的 - Slidev", URL: "http://localhost:3030/15".
0 AXWebArea AI 是这么说的 - Slidev, URL: localhost:3030/15
	1 container app
		2 container slide-container
			3 container slide-content
				4 container
					5 heading 4.3「AI 是这么说的」不是论据 — 信源要自己核对，结论要自己推导, Value: 1
						6 text 4.3「AI 是这么说的」不是论据  — 信源要自己核对，结论要自己推导
					7 text 重点
					8 container
						9 text AI 输出 候选线索 「B 供应商更便宜、交付更快，因此迁移风险可以接受，

…（中间省略 2321 字）…

 More Options
				70 text 15  / 16

The focused UI element is 0 AXWebArea AI 是这么说的 - Slidev, URL: localhost:3030/15
[图片]

10:41:30展开第一讲收尾页的全部内容

{
  "code": "await firstDeck.goto(\"http://localhost:3030/15?clicks=5\"); await firstDeck.getAXState();",
  "title": "展开第一讲收尾页的全部内容"
}

Wall time: 0.5923 seconds
Output:
Browser tab: 2, Title: "AI 是这么说的 - Slidev", URL: "http://localhost:3030/15?clicks=5".
1 AXWebArea AI 是这么说的 - Slidev, URL: localhost:3030/15?clicks=5
	2 container app
		3 container slide-container
			4 container slide-content
				5 container
					6 heading 4.3「AI 是这么说的」不是论据 — 信源要自己核对，结论要自己推导, Value: 1
						7 text 4.3「AI 是这么说的」不是论据  — 信源要自己核对，结论要自己推导
					8 text 重点
					9 container
						10 text AI 输出 候选线索 「B 供应商更

…（中间省略 2344 字）…

e Options
				71 text 15  / 16

The focused UI element is 1 AXWebArea AI 是这么说的 - Slidev, URL: localhost:3030/15?clicks=5

10:41:38检查第一讲总结概念的实际排布

{
  "code": "await firstDeck.getScreenshot();",
  "title": "检查第一讲总结概念的实际排布"
}

Wall time: 0.1362 seconds
Output:
[图片]

看到了，刚才我只看了讲稿里的画面说明，判断错了。

第一讲的实际收尾页是：
- 上半页用具体案例和图形收束课程主张。
- 中间用一句明确结论承上启下。
- 下半页逐行列出概念，每行包含名称、简短定义和关键边界。
所以，概念定义应该保留。第二讲需要改进的是上半页的总结表达，以及下半页概念的整齐排列，不能简单退回两栏文字清单。
嗯，继续？不要抄它的，但我们可以尽可能做得一样好
嗯，继续？不要抄它的，尽可能找一个合适我们这一讲的模式
我建议做成“一项工作交给 Agent 之后”的全景图，把课堂总结和概念放在同一张图里。

画面从左到右展开：

交代目标和材料 → Agent 连续推进 → 得到待检查的结果

中间的 Agent 是主体，内部直接标清：
- Agent：根据目标和反馈，借助工具推进任务的整体系统。
- Tool／工具调用：模型提出请求，工具执行读取、搜索、保存等动作。
- Agent Loop：动作结果返回，模型据此判断下一步。
人的位置贯穿这项工作：开始时确定目标与操作范围，遇到关键判断时参与，最后检查结果、决定采用。这里不画成每一步都要人批准。

这样，一张图就能回顾本讲的三个层次：工作可以接着做了 → 为什么能接着做 → 为什么仍要控制范围。 概念就标在对应对象和动作旁，读者不用在图与概念清单之间来回寻找。

底部只留一句收束：

工具扩展了模型能做的事，判断与边界决定这些能力怎样进入工作。
可以试试？不要纯文字，要有点隐喻的图画？
我会把它画成一张“工作台”：左边是任务和材料，中间让模型与工具接力工作，右边留下可检查的产物；人的确认落在具体动作旁。概念直接标在图中对应的位置。

干了 4 分钟，3 步

运行 3 条命令

10:44:54运行 git status --short; sed -n '86,160p' slides/02.md; sed -n '66,125p' 'course/课程内容/02 - 从「回答」到「执行」.md'; sed -n '1,26p'…

text(await tools.exec_command({cmd:"git status --short; sed -n '86,160p' slides/02.md; sed -n '66,125p' 'course/课程内容/02 - 从「回答」到「执行」.md'; sed -n '1,26p' slides/AGENTS.md; sed -n '220,230p' slides/styles/index.css","max_output_tokens":2700}));

Script completed
Wall time 0.1 seconds
Output:

{"chunk_id":"d7e49c","wall_time_seconds":0.000002917,"exit_code":0,"original_token_count":2439,"output":" M \"course/\\347\\264\\240\\346\\235\\220\\344\\270\\216\\350\\215\\211\\347\\250\\277/02-\\347\\254\\254\\344\\272\\214\\350\\256\\262\\346\\234\\252\\351\\207\\207\\347\\224\\250\\347\\264\\240\\346\\235\\220.md\"\n D \"course/\\347\\264\\240\\346\\235\\220\\344\\270\\216\\350\\215\\211\\347\\

…（中间省略 4990 字）…

n-booklist p, .lesson-booklist figure { margin: 0; }\n.lesson-booklist__intro { font-size: 18px; line-height: 1.5; }\n"}

10:45:27思考：**Implementing diagram layout**
Implementing diagram layout
10:45:54思考：**Implementing diagram layout** **我完善 Agent 总结图布局**
Implementing diagram layout

我完善 Agent 总结图布局

10:46:14运行 python3 - <<'PY'

text(await tools.exec_command({cmd:"python3 - <<'PY'\nfrom pathlib import Path\np=Path('~/Library/Mobile Documents/iCloud~md~obsidian/Documents/Note/Areas/大模型(LLM)/AI 通识课程/课程内容/02 - 从「回答」到「执行」.md')\ns=p.read_text();a=s.index('> [!note] PPT 画面',s.index('## 4 课堂总结'));b=s.index('\\n## 结束与讨论',a)\ns=s[:a]+'''> [!note] PPT 画面\n> 采用「一项工作交给 Agent 之后」的工作台全景，概念与实际对象放在同一张图中，不使用两栏文字清单，也不照搬第一讲的论证桥。\n>\n> 从左到右是任务夹与资料、运行 Agent 的电脑、待检查的产物。任务夹显示目标与要求，资料画成有表格和文字的纸

…（中间省略 637 字）…

ibrary/Mobile Documents/iCloud~md~obsidian/Documents/Note/Areas/大模型(LLM)/AI 通识课程/' course/","max_output_tokens":500}));

Script completed
Wall time 0.1 seconds
Output:

{"chunk_id":"00eff7","wall_time_seconds":0.000004625,"exit_code":0,"original_token_count":65,"output":"Transfer starting: 45 files\n>f.st.... 课�\\#213�\\#206\\#205容/02 - �\\#216�\\#200\\#214�\\#233\\#236�\\#255\\#224�\\#200\\#215�\\#210��\\#200\\#214�\\#211��\\#214�\\#200\\#215.md\n\nsent 2421 bytes  received 26 bytes  789354 bytes/sec\ntotal size is 264441  speedup is 108.07\n"}

10:46:44思考：**Drafting SVG flow diagram**
Drafting SVG flow diagram
10:47:06思考：**Drafting SVG flow diagram** **Refining SVG flow layout**
Drafting SVG flow diagram

Refining SVG flow layout

10:48:38运行 ./scripts/sync-course.sh

text(await tools.exec_command({cmd:"./scripts/sync-course.sh\ncat > /tmp/lesson02-summary-workbench.md <<'EOF'\n---\nlayout: default\ntitle: 课堂总结\nclicks: 0\n---\n\n# 4 课堂总结 <span>— 一项工作交给 Agent 之后</span>\n\n<svg class=\"absolute inset-0 w-full h-full\" viewBox=\"0 0 1280 720\" role=\"img\" aria-label=\"从任务与材料到待检查产物的工作台全景：Agent 内部由模型请求工具执行，结果反馈构成 Agent Loop；人确定范围、补充关键判断并检查采用。\" font-family=\"PingFang SC, sans-serif\">\n<defs>\n<marker id=\"summar

…（中间省略 8433 字）…

02-summary-workbench > /tmp/ai-literacy-02-summary-workbench.log 2>&1","yield_time_ms":1000,"max_output_tokens":400}));

Script completed
Wall time 1.2 seconds
Output:

{"chunk_id":"faa846","wall_time_seconds":1.001971625,"session_id":96061,"original_token_count":0,"output":""}

10:48
图形版已写好：任务夹、电脑里的模型与工具、右侧待检查的文档共同组成一项工作。反馈回路放在电脑内，概念贴着对应对象；人的判断则落在交代范围、回答疑问和检查结果三个位置。现在检查图形是否清楚、文字是否拥挤。

干了 2 分钟，7 步

读 1 个文件，运行 3 条命令，写 1 个文件，其他操作 3 次

10:48:50运行 tail -2 /tmp/ai-literacy-02-summary-workbench.log; git diff --stat -- slides/02.md 'course/课程内容/02 - 从「回答」到「执行」.md'

text(await tools.write_stdin({session_id:96061,chars:"","yield_time_ms":1000,"max_output_tokens":350}));
text(await tools.exec_command({cmd:"tail -2 /tmp/ai-literacy-02-summary-workbench.log; git diff --stat -- slides/02.md 'course/课程内容/02 - 从「回答」到「执行」.md'","max_output_tokens":350}));

Script completed
Wall time 0.1 seconds
Output:

{"chunk_id":"35678b","wall_time_seconds":0.000003208,"exit_code":0,"original_token_count":0,"output":""}
{"chunk_id":"645332","wall_time_seconds":0.000002958,"exit_code":0,"original_token_count":94,"output":"../../../../../tmp/ai-literacy-02-summary-workbench/assets/modules/vue-FxgGn04Y.js                                             258.67 kB │ gzip: 96.71 kB\n✓ built in 1.35s\n ...200\\214\\346\\21

…（中间省略 74 字）…

                                    | 90 ++++++++++++++++++++++\n 2 files changed, 125 insertions(+), 3 deletions(-)\n"}

10:48:59查看课堂总结的图形版本

{
  "code": "let summaryTab = await cua.getTab(\"1\", { browser: \"1\" });",
  "title": "查看课堂总结的图形版本"
}

Wall time: 0.4163 seconds
Output:
## Computer Use

Control native apps and browsers on the user’s computer by reading or operating UI. Prefer purpose-built connectors, APIs, or CLIs when available.

- Use `cua_repl` (JavaScript) for all UI actions.
- Do not use other technologies besides `cua_repl` for computer interactions, unless specifically requested by the user (e.g. AppleScript, `osascript`, JXA, System Events, CGEvent synthesis).
- Prefer 

…（中间省略 51057 字）…

ton More Options
				23 text 10  / 11

The focused UI element is 0 AXWebArea 从「回答」到「执行」 - Slidev, URL: localhost:3032/10

10:50:10写入 current-summary-redesign

{
  "path": "current-summary-redesign",
  "text": "[编码数据]"
}

10:50:20new_context

{}

A new context window will start without summarizing conversation history.

10:50:28读取 current-summary-redesign

{
  "path": "current-summary-redesign"
}

10:50:39查看第二讲总结页的实际画面

{
  "code": "await summaryTab.getScreenshot();",
  "title": "查看第二讲总结页的实际画面"
}

Wall time: 0.1030 seconds
Output:
[图片]

text(await tools.exec_command({cmd:"rg -n '课堂总结|lesson02-summary|workbench|<svg|<text|course-conclusion' slides/02.md | tail -65","max_output_tokens":6500}));
text(await tools.exec_command({cmd:"rg -n 'svg|text\\s*\\{|font-size|course-conclusion' slides/style.css slides/styles* slides/AGENTS.md","max_output_tokens":4500}));

Script completed
Wall time 0.1 seconds
Output:

{"chunk_id":"b8d9ed","wall_time_seconds":0.000004208,"exit_code":0,"original_token_count":821,"output":"89:title: 课堂总结\n93:# 4 课堂总结 <span>— 一项工作交给 Agent 之后</span>\n95:<svg class=\"absolute inset-0 w-full h-full\" viewBox=\"0 0 1280 720\" role=\"img\" aria-label=\"从任务与材料到待检查产物的工作台全景：Agent 内部由模型请求工具执行，结果反馈构成 Agent Loop；人确定范围、补充关键判断并检查采用。\" font-family=\"PingFang SC, sans-serif\">\n100:<text x=\"70\" y

…（中间省略 8862 字）…

e 500ms; }\nslides/styles/index.css:258:.lesson-research-task--docked { transform: translateY(0); font-size: 19px; }\n"}

实际预览发现，图中文字被页面样式异常放大了。我先修正字号和底部留白，再检查整张图的阅读顺序。

干了 1 分钟，8 步

运行 2 条命令，其他操作 6 次

10:51:04定位图中文字异常放大的原因

{
  "code": "nodeRepl.write(await summaryTab.playwright.evaluate(() => Array.from(document.querySelectorAll('svg[aria-label^=\"从任务\"] text')).slice(0,8).map(e=>({text:e.textContent,attr:e.getAttribute('font-size'),style:e.getAttribute('style'),computed:getComputedStyle(e).fontSize,box:e.getBoundingClientRect().toJSON()}))));",
  "title": "定位图中文字异常放大的原因"
}

Wall time: 0.0375 seconds
Output:
[
  {
    attr: '22',
    box: {
      bottom: 436.3929748535156,
      height: 30.653900146484375,
      left: 17.4453125,
      right: 192.8953094482422,
      top: 405.7390747070313,
      width: 175.4499969482422,
      x: 17.4453125,
      y: 405.7390747070313
    },
    computed: '88px',
    style: null,
    text: '你确定目标与范围'
  },
  {
    attr: '28',
    box: {
      bottom: 436.3929748535156,
      height: 

…（中间省略 2190 字）…

 x: -0.7476562261581421,
      y: 466.2992248535156
    },
    computed: '92px',
    style: null,
    text: '相关材料'
  }
]

10:51:12运行 sed -n '85,195p' slides/02.md

text(await tools.exec_command({cmd:"sed -n '85,195p' slides/02.md","max_output_tokens":8000}));

Script completed
Wall time 0.1 seconds
Output:

{"chunk_id":"fd4200","wall_time_seconds":0.00000375,"exit_code":0,"original_token_count":2415,"output":"---\n\n---\nlayout: default\ntitle: 课堂总结\nclicks: 0\n---\n\n# 4 课堂总结 <span>— 一项工作交给 Agent 之后</span>\n\n<svg class=\"absolute inset-0 w-full h-full\" viewBox=\"0 0 1280 720\" role=\"img\" aria-label=\"从任务与材料到待检查产物的工作台全景：Agent 内部由模型请求工具执行，结果反馈构成 Agent Loop；人确定范围、补充关键判断并检查采用。\" font-family=\"PingFang

…（中间省略 8308 字）…

留给人\n</div>\n\n<div class=\"mt-5 text-base opacity-50\">\n感谢聆听！欢迎提问和讨论\n</div>\n\n<!--\n这一讲，我们看见模型接上工具以后，可以连续推进一项工作。\n"}

10:51:30思考：**Checking screenshot options**
Checking screenshot options

10:51:34运行 python3 - <<'PY'

text(await tools.exec_command({cmd:"python3 - <<'PY'\nfrom pathlib import Path\nimport re\np=Path('slides/02.md')\ns=p.read_text()\na=s.index('<svg class=\"absolute inset-0 w-full h-full\" viewBox=\"0 0 1280 720\" role=\"img\" aria-label=\"从任务')\nb=s.index('</svg>',a)\ns=s[:a]+re.sub(r'font-size=\"(\\d+)\"',r'style=\"font-size:\\1px\"',s[a:b])+s[b:]\ns=s.replace('top:631px','top:615px')\np.write_text(s)\nPY","max_output_tokens":800}));

Script completed
Wall time 0.1 seconds
Output:

{"chunk_id":"e8dd9c","wall_time_seconds":0.000002416,"exit_code":0,"original_token_count":0,"output":""}

10:51:40核查修正后的总结页

{
  "code": "await summaryTab.getScreenshot();",
  "title": "核查修正后的总结页"
}

Wall time: 0.1089 seconds
Output:
[图片]

10:51:46查找可用的幻灯片预览窗口

{
  "code": "await cua.getState();",
  "title": "查找可用的幻灯片预览窗口"
}

Wall time: 0.1877 seconds
Output:
{"apps":[{"displayName":"Google Chrome","id":"com.google.Chrome","isRunning":true,"lastUsedDate":810432000,"useCount":21087},{"displayName":"Obsidian","id":"md.obsidian","isRunning":true,"lastUsedDate":810432000,"useCount":7550},{"displayName":"WeChat","id":"com.tencent.xinWeChat","isRunning":true,"lastUsedDate":810432000,"useCount":4514},{"displayName":"ChatGPT","id":"com.openai.codex","isRunning":true,"lastUsed

…（中间省略 4239 字）…

TabId":"7f372652-3224-47ae-ab53-036853bedcea","title":"AI 是这么说的 - Slidev","url":"http://localhost:3030/15?clicks=5"}]}]}

10:51:54打开独立的总结页检查视图

{
  "code": "let summaryCheck = await cua.createBrowserTab('iab', 'http://localhost:3032/10', {visible:false});",
  "title": "打开独立的总结页检查视图"
}

Wall time: 0.3966 seconds
Output:
Browser tab: 4, Title: "ä»Žã€Œå›žç”ã€åˆ°ã€Œæ‰§è¡Œã€ - Slidev", URL: "http://localhost:3032/10".
0 AXWebArea ä»Žã€Œå›žç”ã€åˆ°ã€Œæ‰§è¡Œã€ - Slidev, URL: localhost:3032/10

The focused UI element is 0 AXWebArea ä»Žã€Œå›žç”ã€åˆ°ã€Œæ‰§è¡Œã€ - Slidev, URL: localhost:3032/10

10:52:01检查完整尺寸下的图示与字号

{
  "code": "await summaryCheck.getScreenshot();",
  "title": "检查完整尺寸下的图示与字号"
}

Wall time: 0.3193 seconds
Output:
[图片]

10:52:09list_items

{
  "role": "user",
  "recent_first": true,
  "limit": 5,
  "max_chars_per_item": 2200,
  "window_id": "01a07650-bb5a-7400-8307-92529c8ed200"
}

现在画面正常了：左侧用任务夹表示输入，中间电脑里的芯片、工具箱和回路对应几个核心概念，右侧用待检查的文档承接结果。人的判断也落在图中三个具体位置，最后再核对构建和翻页衔接。

干了不到 1 分钟，5 步

运行 4 条命令，其他操作 3 次

10:52:33运行 pnpm run slides:build slides/02.md --out /tmp/ai-literacy-02-summary-workbench > /tmp/ai-literacy-02-summary-workben…

const results = await Promise.allSettled([
tools.exec_command({cmd:"pnpm run slides:build slides/02.md --out /tmp/ai-literacy-02-summary-workbench > /tmp/ai-literacy-02-summary-workbench.log 2>&1","yield_time_ms":1000,"max_output_tokens":1200}),
tools.exec_command({cmd:"git diff --check -- slides/02.md 'course/课程内容/02 - 从「回答」到「执行」.md'","max_output_tokens":800}),
tools.exec_command({cmd:"python3 - <<'PY'\nfrom pathlib import Path\nr=Path('course/课

…（中间省略 245 字）…

堂总结');print(t[a:a+3600])\nPY","max_output_tokens":2500})
]); for(let i=0;i<results.length;i++) text({i,...results[i]});

Script completed
Wall time 1.2 seconds
Output:

{"i":0,"status":"fulfilled","value":{"chunk_id":"1375ca","wall_time_seconds":1.00043075,"session_id":5698,"original_token_count":0,"output":""}}
{"i":1,"status":"fulfilled","value":{"chunk_id":"c84bd0","wall_time_seconds":0.0000025,"exit_code":0,"original_token_count":0,"output":""}}
{"i":2,"status":"fulfilled","value":{"chunk_id":"a9d070","wall_time_seconds":0.000001458,"exit_code":0,"original_toke

…（中间省略 1630 字）…

PPT 画面\n> 使用已有 `end` 布局与浅色背景，以「Q&A」为标题，显示上述收束句与「感谢聆听！欢迎提问和讨论」。初始即最终状态，不设 Click，不追加新概念或下一讲预定目录。本页承接课堂总结，留出提问与讨论时间。\n\n"}}

10:52:42确认总结页之后进入 Q&A

{
  "code": "await summaryCheck.pressKey('ArrowRight'); await summaryCheck.getAXState();",
  "title": "确认总结页之后进入 Q&A"
}

Wall time: 0.3040 seconds
Output:
Browser tab: 4, Title: "从「回答」到「执行」 - Slidev", URL: "http://localhost:3032/11".
1 AXWebArea 从「回答」到「执行」 - Slidev, URL: localhost:3032/11
	2 container app
		3 container slide-container
			4 container slide-content
				5 container slideshow
					6 container
						7 heading 4 课堂总结 — 一项工作交给 Agent 之后, Value: 1
							8 text 4 课堂总结  — 一项工作交给 Agent 之后
						9 container 从任务与材料到待检查产物的工作台全景：Agent 内部由模型请求工具执行，结果反馈构成 Agent Loo

…（中间省略 796 字）…

ton More Options
				34 text 11  / 11

The focused UI element is 1 AXWebArea 从「回答」到「执行」 - Slidev, URL: localhost:3032/11

10:52:51核对总结页的字号与画布边界

{
  "code": "await summaryCheck.pressKey('ArrowLeft'); nodeRepl.write(await summaryCheck.playwright.evaluate(() => {const s=document.querySelector('svg[aria-label^=\"从任务\"]');return {textSizes:Array.from(s.querySelectorAll('text')).map(e=>({text:e.textContent,size:getComputedStyle(e).fontSize})),overflow:Array.from(s.querySelectorAll('text')).filter(e=>{const b=e.getBBox();return b.x<0||b.y<0||b.x+b.width>1280||b.y+b.height>720}).map(e=>e.textContent)};}));",
  "title": "核对总结页的字号与画布边界"
}

Wall time: 0.0771 seconds
Output:
TypeError: e.getBBox is not a function
    at <anonymous>:2686:286
    at Array.filter (<anonymous>)
    at __playwrightEvaluate (<anonymous>:2686:265)
    at <anonymous>:2687:14
    at runUserScript (<anonymous>:2688:10)
    at <anonymous>:2692:10
    at <anonymous>:2693:3

10:53:00检查文字是否超出画面

{
  "code": "nodeRepl.write(await summaryCheck.playwright.evaluate(() => {const s=document.querySelector('svg[aria-label^=\"从任务\"]');const a=s.getBoundingClientRect();return {fontSizes:[...new Set(Array.from(s.querySelectorAll('text')).map(e=>getComputedStyle(e).fontSize))],overflow:Array.from(s.querySelectorAll('text')).filter(e=>{const b=e.getBoundingClientRect();return b.left<a.left||b.top<a.top||b.right>a.right||b.bottom>a.bottom}).map(e=>e.textContent)};}));",
  "title": "检查文字是否超出画面"
}

Wall time: 0.0319 seconds
Output:
{
  fontSizes: [
    '22px', '28px',
    '19px', '23px',
    '24px', '20px',
    '18px', '17px',
    '21px'
  ],
  overflow: []
}

10:53:06运行 tail -4 /tmp/ai-literacy-02-summary-workbench.log

text(await tools.write_stdin({session_id:5698,chars:"","yield_time_ms":1000,"max_output_tokens":1000}));
text(await tools.exec_command({cmd:"tail -4 /tmp/ai-literacy-02-summary-workbench.log","max_output_tokens":500}));

Script completed
Wall time 0.1 seconds
Output:

{"chunk_id":"4c1efe","wall_time_seconds":8.75e-7,"exit_code":0,"original_token_count":0,"output":""}
{"chunk_id":"3982be","wall_time_seconds":0.0000045,"exit_code":0,"original_token_count":122,"output":"../../../../../tmp/ai-literacy-02-summary-workbench/assets/slidev/shortcuts-DD25Hd1C.js                                         65.02 kB │ gzip: 23.33 kB\n../../../../../tmp/ai-literacy-02-summary-wo

…（中间省略 166 字）…

ets/modules/vue-FxgGn04Y.js                                             258.67 kB │ gzip: 96.71 kB\n✓ built in 1.50s\n"}

已做成工作台图示版：任务夹 → Agent 电脑工作台 → 待检查文档。

模型、工具、工具调用和 Agent Loop 都贴着对应图形呈现；人的判断落在确定范围、回答关键疑问、检查结果三个位置。

已检查实际画面与翻页，第二讲构建通过，讲稿已同步。
11:00
有点太花哨了，能不能简洁一点，概念的部分应该与上一讲一致的
我先对照上一讲的概念区。这版把图画得太重了，简化时会减少装饰，让概念的列法和定义表达与上一讲保持一致。

干了不到 1 分钟，2 步

运行 5 条命令

11:00:25运行 rg -n '课堂总结|概念|4.3|summary' slides/01.md slides/pages/01/4.3.md slides/AGENTS.md 等 2 条命令

const r=await Promise.allSettled([
tools.exec_command({cmd:"rg -n '课堂总结|概念|4.3|summary' slides/01.md slides/pages/01/4.3.md slides/AGENTS.md","max_output_tokens":2500}),
tools.exec_command({cmd:"sed -n '85,175p' slides/02.md","max_output_tokens":6500})
]);for(let i=0;i<r.length;i++)text({i,...r[i]});

Script completed
Wall time 0.1 seconds
Output:

{"i":0,"status":"fulfilled","value":{"chunk_id":"5ba60d","wall_time_seconds":0.000003292,"exit_code":0,"original_token_count":728,"output":"slides/01.md:135:src: ./pages/01/4.3.md\nslides/pages/01/4.3.md:6:# 4.3「AI 是这么说的」不是论据 <span>— 信源要自己核对，结论要自己推导</span>\nslides/pages/01/4.3.md:13:<strong class=\"text-[#5D8493]\">AI 输出</strong><span class=\"text-xs text-[#8E999F]\">候选线索</span>\nslides/pages/01/4.3

…（中间省略 10771 字）…

工作。能继续执行不保证结果正确，有限授权也不能代替判断。\n概念与边界沿用 2.2、3.1—3.3，不加入新定义或产品事实；电脑是教学工作环境的示意，不代表任何产品默认权限或全部内部实现。本页静态展示，之后进入 Q&A。\n-->\n"}}

11:00:36运行 sed -n '65,103p' slides/pages/01/4.3.md 等 3 条命令

const r=await Promise.allSettled([
tools.exec_command({cmd:"sed -n '65,103p' slides/pages/01/4.3.md","max_output_tokens":3000}),
tools.exec_command({cmd:"cat slides/AGENTS.md","max_output_tokens":4200}),
tools.exec_command({cmd:"sed -n '1,130p' scripts/sync-course.sh","max_output_tokens":2000})
]);r.forEach((v,i)=>text({i,...v}));

Script completed
Wall time 0.1 seconds
Output:

{"i":0,"status":"fulfilled","value":{"chunk_id":"1d1f54","wall_time_seconds":0.000003458,"exit_code":0,"original_token_count":826,"output":"<div v-click=\"5\" class=\"lesson-reveal-step absolute bottom-[176px] left-0 right-0 border-t border-gray-300 pt-3 text-center\">\n<span class=\"text-lg\">不是「AI 得出了结论」，而是</span>\n<strong class=\"ml-2 text-xl text-[#5D8493]\">「我核对了信源，并据此得出结论」</strong>\n</div>\n\n

…（中间省略 5034 字）…

nfi\n\nmkdir -p \"$target_dir\"\n/usr/bin/rsync -a --delete --exclude '.DS_Store' \"$source_dir/\" \"$target_dir/\"\n"}}

11:01:01思考：**Simplifying the top diagram**
Simplifying the top diagram

上一讲的概念区是固定的三行：小图标、概念名称、一句定义。我会直接沿用这个格式；上方只保留“任务 → Agent → 待检查结果”的简图，去掉电脑、键盘和内部连线。

干了 2 分钟，7 步

运行 6 条命令，其他操作 3 次

11:01:04运行 sed -n '1,15p' slides/pages/01/4.3.md && rg -n '^##|^###' slides/DESIGN.md

text(await tools.exec_command({cmd:"sed -n '1,15p' slides/pages/01/4.3.md && rg -n '^##|^###' slides/DESIGN.md","max_output_tokens":1800}));

Script completed
Wall time 0.1 seconds
Output:

{"chunk_id":"67b0da","wall_time_seconds":0.000009333,"exit_code":0,"original_token_count":383,"output":"---\nlayout: default\ntitle: AI 是这么说的不是论据\n---\n\n# 4.3「AI 是这么说的」不是论据 <span>— 信源要自己核对，结论要自己推导</span>\n\n<div class=\"abs-tr\"><span class=\"bg-[#FB8F68]/15 text-[#C85F3C]\">重点</span></div>\n\n<section class=\"relative mx-auto mt-3 h-[500px] w-[1120px]\">\n<div class=\"absolute left-0 top-[16px] h-

…（中间省略 680 字）…

:### 先读题，再展开\n162:### 状态说明\n174:## 6. 字体、色彩与固定页面元素\n188:### 来源与脚注\n199:### 结论区\n208:## 7. 第一讲的参考页面\n223:## 8. 逐页评审标准\n"}

11:01:51运行 python3 - <<'PY'

text(await tools.exec_command({cmd:"python3 - <<'PY'\nfrom pathlib import Path\np=Path('~/Library/Mobile Documents/iCloud~md~obsidian/Documents/Note/Areas/大模型(LLM)/AI 通识课程/课程内容/02 - 从「回答」到「执行」.md')\ns=p.read_text(); a=s.index('> [!note] PPT 画面',s.index('## 4 课堂总结')); b=s.index('\\n## 结束与讨论',a)\ns=s[:a]+'''> [!note] PPT 画面\n> 上方用「任务 → Agent → 待检查结果」的简图回顾整讲。任务纸写出目标与要求，中间的循环箭头表示 Agent 接着读取、处理与保存材料，右侧文档标为「待检查」。不绘制电脑、键盘或内部实现，不把概念定义塞进主图。\n>\n> 人的作用紧贴对应

…（中间省略 534 字）…

brary/Mobile Documents/iCloud~md~obsidian/Documents/Note/Areas/大模型(LLM)/AI 通识课程/' course/","max_output_tokens":1000}));

Script completed
Wall time 0.1 seconds
Output:

{"chunk_id":"f99be3","wall_time_seconds":0.000002209,"exit_code":0,"original_token_count":35,"output":">f.st.... 课�\\#213�\\#206\\#205容/02 - �\\#216�\\#200\\#214�\\#233\\#236�\\#255\\#224�\\#200\\#215�\\#210��\\#200\\#214�\\#211��\\#214�\\#200\\#215.md\n"}

11:02:54运行 ./scripts/sync-course.sh 等 2 条命令

text(await tools.exec_command({cmd:"./scripts/sync-course.sh","max_output_tokens":500}));
text(await tools.exec_command({cmd:"python3 - <<'PY'\nfrom pathlib import Path\np=Path('slides/02.md');s=p.read_text();a=s.index('# 4 课堂总结');b=s.index('\\n---\\nlayout: end',a)\ns=s[:a]+'''# 4 课堂总结 <span>— 一项工作交给 Agent 之后</span>\n\n<svg class=\"absolute inset-0 w-full h-full\" viewBox=\"0 0 1280 720\" role=\"img\" aria-label=\"任务交给 Agent，由它接着读取、处理和保存材料，留下待检查

…（中间省略 4477 字）…

动作和反馈接起来。\n本页沿用已讲定义与边界，不新增案例、术语或证据。全部内容静态呈现，之后进入 Q&A。\n-->\n''' +s[b:];p.write_text(s)\nPY","max_output_tokens":500}));

Script completed
Wall time 0.2 seconds
Output:

{"chunk_id":"f26f36","wall_time_seconds":0.000003291,"exit_code":0,"original_token_count":0,"output":""}
{"chunk_id":"7d430c","wall_time_seconds":0.000003042,"exit_code":0,"original_token_count":0,"output":""}

11:03:00查看简化后的总结页与统一概念区

{
  "code": "await summaryCheck.getScreenshot();",
  "title": "查看简化后的总结页与统一概念区"
}

Wall time: 0.0108 seconds
Output:
Tab 4 is not part of browser session 01a070cb-d51c-7163-aca2-3f2ce0f0931c

11:03:09打开简洁版总结页预览

{
  "code": "let simpleSummary = await cua.createBrowserTab('iab', 'http://localhost:3032/10', {visible:false});",
  "title": "打开简洁版总结页预览"
}

Wall time: 0.4895 seconds
Output:
Browser tab: 5, Title: "ä»Žã€Œå›žç”ã€åˆ°ã€Œæ‰§è¡Œã€ - Slidev", URL: "http://localhost:3032/10".
0 AXWebArea ä»Žã€Œå›žç”ã€åˆ°ã€Œæ‰§è¡Œã€ - Slidev, URL: localhost:3032/10

The focused UI element is 0 AXWebArea ä»Žã€Œå›žç”ã€åˆ°ã€Œæ‰§è¡Œã€ - Slidev, URL: localhost:3032/10

11:03:21运行 pnpm run slides:build slides/02.md --out /tmp/ai-literacy-02-summary-simple > /tmp/ai-literacy-02-summary-simple.log…

const r=await Promise.allSettled([
tools.exec_command({cmd:"pnpm run slides:build slides/02.md --out /tmp/ai-literacy-02-summary-simple > /tmp/ai-literacy-02-summary-simple.log 2>&1","yield_time_ms":1000,"max_output_tokens":500}),
tools.exec_command({cmd:"git diff --check -- slides/02.md 'course/课程内容/02 - 从「回答」到「执行」.md'","max_output_tokens":500})
]);r.forEach((v,i)=>text({i,...v}));

Script completed
Wall time 1.2 seconds
Output:

{"i":0,"status":"fulfilled","value":{"chunk_id":"e3ff51","wall_time_seconds":1.002084833,"session_id":30382,"original_token_count":0,"output":""}}
{"i":1,"status":"fulfilled","value":{"chunk_id":"ec0b88","wall_time_seconds":0.000002458,"exit_code":0,"original_token_count":0,"output":""}}

11:03:31检查图示留白和概念行的实际排版

{
  "code": "await simpleSummary.getScreenshot();",
  "title": "检查图示留白和概念行的实际排版"
}

Wall time: 0.1577 seconds
Output:
[图片]

简洁版已完成：上方只留下任务、Agent 和结果三个对象；下方恢复为与上一讲相同的三行概念区。实际预览中，图示与定义已经分开，文字没有挤压或溢出。

干了不到 1 分钟，3 步

运行 2 条命令，其他操作 2 次

11:03:46检查简化后的总结页翻页衔接

{
  "code": "await simpleSummary.pressKey('ArrowRight'); await simpleSummary.getAXState();",
  "title": "检查简化后的总结页翻页衔接"
}

Wall time: 0.3124 seconds
Output:
Browser tab: 5, Title: "从「回答」到「执行」 - Slidev", URL: "http://localhost:3032/11".
1 AXWebArea 从「回答」到「执行」 - Slidev, URL: localhost:3032/11
	2 container app
		3 container slide-container
			4 container slide-content
				5 container slideshow
					6 container
						7 heading 4 课堂总结 — 一项工作交给 Agent 之后, Value: 1
							8 text 4 课堂总结  — 一项工作交给 Agent 之后
						9 container 任务交给 Agent，由它接着读取、处理和保存材料，留下待检查的工作结果；人确定范围、回答关键疑问并检查采

…（中间省略 1096 字）…

ton More Options
				46 text 11  / 11

The focused UI element is 1 AXWebArea 从「回答」到「执行」 - Slidev, URL: localhost:3032/11

11:03:54回到课堂总结页

{
  "code": "await simpleSummary.pressKey('ArrowLeft');",
  "title": "回到课堂总结页"
}

Wall time: 0.1159 seconds
Output:

11:04:05运行 tail -1 /tmp/ai-literacy-02-summary-simple.log 等 2 条命令

text(await tools.write_stdin({session_id:30382,chars:"","yield_time_ms":1000,"max_output_tokens":500}));
text(await tools.exec_command({cmd:"tail -1 /tmp/ai-literacy-02-summary-simple.log","max_output_tokens":200}));
text(await tools.exec_command({cmd:"python3 - <<'PY'\nfrom pathlib import Path\ns=Path('~/Library/Mobile Documents/iCloud~md~obsidian/Documents/Note/Areas/大模型(LLM)/AI 通识课程/课程内容/02 - 从「回答」到「执行」.md')\nr=Path('course/课程内容/02 - 从「回答」到「执行」.md')\nprint('source/mirror match:',s.read_bytes()==r.read_bytes())\nPY","max_output_tokens":200}));

Script completed
Wall time 0.1 seconds
Output:

{"chunk_id":"dfb617","wall_time_seconds":6.66e-7,"exit_code":0,"original_token_count":0,"output":""}
{"chunk_id":"0b23f0","wall_time_seconds":0.00000275,"exit_code":0,"original_token_count":5,"output":"✓ built in 1.65s\n"}
{"chunk_id":"da4b5f","wall_time_seconds":0.0000025,"exit_code":0,"original_token_count":7,"output":"source/mirror match: True\n"}

已简化这页：
- 上方只保留“任务 → Agent → 待检查结果”。
- 下方沿用上一讲的概念区：小图标、名称、一句定义，字号和配色一致。
已同步讲稿，实际画面与构建检查通过。
OK，提交到 MR 上吧
我会核对这次总结页的改动和当前 MR，提交后推送到对应分支。
11:05

干了不到 1 分钟，1 步

运行 3 条命令

11:05:19运行 git status --short && git branch --show-current && git remote -v 等 3 条命令

const r=await Promise.allSettled([
tools.exec_command({cmd:"git status --short && git branch --show-current && git remote -v","max_output_tokens":2000}),
tools.exec_command({cmd:"git diff --stat && git diff -- slides/02.md 'course/课程内容/02 - 从「回答」到「执行」.md'","max_output_tokens":9500}),
tools.exec_command({cmd:"glab mr view --output json","max_output_tokens":1500})
]);r.forEach((v,i)=>text({i,...v}));

Script completed
Wall time 1.6 seconds
Output:

{"i":0,"status":"fulfilled","value":{"chunk_id":"e951f1","wall_time_seconds":0.000002333,"exit_code":0,"original_token_count":259,"output":" M \"course/\\347\\264\\240\\346\\235\\220\\344\\270\\216\\350\\215\\211\\347\\250\\277/02-\\347\\254\\254\\344\\272\\214\\350\\256\\262\\346\\234\\252\\351\\207\\207\\347\\224\\250\\347\\264\\240\\346\\235\\220.md\"\n D \"course/\\347\\264\\240\\346\\235\\220\\

…（中间省略 14518 字）…

,\"rebase_in_progress\":false,\"diverged_commits_count\":0,\"first_contribution\":false,\"work_in_progress\":false}\n"}}

这次会提交总结页和对应讲稿，第三讲及草稿区的改动保留在本地。我也会用 codex-pr-body 更新 MR 描述，补上总结页和已通过的检查。

干了 1 分钟，7 步

运行 11 条命令，运行 1 段代码

11:05:33运行 cat ~/.codex/skills/codex-pr-body/SKILL.md 等 3 条命令

const r=await Promise.allSettled([
tools.exec_command({cmd:"cat ~/.codex/skills/codex-pr-body/SKILL.md","max_output_tokens":3200}),
tools.exec_command({cmd:"glab mr view 12 --output json > /tmp/ai-literacy-mr12.json\npython3 - <<'PY'\nimport json\nj=json.load(open('/tmp/ai-literacy-mr12.json'))\nprint(j['description'])\nPY","max_output_tokens":2500}),
tools.exec_command({cmd:"git log -1 --format='%h %s' && git config --get branch.feat/lesson-02-a

…（中间省略 36 字）…

ig --get branch.feat/lesson-02-authoring-workflow.merge","max_output_tokens":500})
]);r.forEach((v,i)=>text({i,...v}));

Script completed
Wall time 0.7 seconds
Output:

{"i":0,"status":"fulfilled","value":{"chunk_id":"9c6dcd","wall_time_seconds":0.000003125,"exit_code":0,"original_token_count":1112,"output":"---\nname: codex-pr-body\ndescription: Update the title and body of one or more pull requests.\n---\n\n## Determining the PR(s)\n\nWhen this skill is invoked, the PR(s) to update may be specified explicitly, but in the common case, the PR(s) to update will be i

…（中间省略 5560 字）…

f12c605 docs(course): separate research from slide production\ngitlab\nrefs/heads/feat/lesson-02-authoring-workflow\n"}}

11:05:49运行 python3 - <<'PY' 等 2 条命令

text(await tools.exec_command({cmd:"python3 - <<'PY'\nfrom pathlib import Path\np=Path('~/Library/Mobile Documents/iCloud~md~obsidian/Documents/Note/Areas/大模型(LLM)/AI 通识课程/课程内容/02 - 从「回答」到「执行」.md')\ns=p.read_text().replace('status: 七页正文、两页过渡、课堂总结与 Q&A 已制作；新增总结页待审阅','status: 七页正文、两页过渡、课堂总结与 Q&A 已制作')\np.write_text(s)\nPY\n/usr/bin/rsync -ani --delete --exclude '.DS_Store' '~/Library/Mobile Documents/iCloud~md~obsidian/Documents/Note/Areas/大模型(LLM)

…（中间省略 36 字）…

ns":500}));
text(await tools.exec_command({cmd:"glab api --help | rg -n -A2 'input|method'","max_output_tokens":800}));

Script completed
Wall time 0.2 seconds
Output:

{"chunk_id":"9d0266","wall_time_seconds":0.000002708,"exit_code":0,"original_token_count":35,"output":">f.st.... 课�\\#213�\\#206\\#205容/02 - �\\#216�\\#200\\#214�\\#233\\#236�\\#255\\#224�\\#200\\#215�\\#210��\\#200\\#214�\\#211��\\#214�\\#200\\#215.md\n"}
{"chunk_id":"38aa4b","wall_time_seconds":0.00000275,"exit_code":0,"original_token_count":933,"output":"Warning: truncated output (original token 

…（中间省略 3186 字）…

utput as: json, ndjson. (json)\n167-    --paginate      Make additional HTTP requests to fetch all pages of results.\n"}

11:05:57运行 ./scripts/sync-course.sh && git diff --check -- slides/02.md 'course/课程内容/02 - 从「回答」到「执行」.md' && git add -- slides/0…

text(await tools.exec_command({cmd:"./scripts/sync-course.sh && git diff --check -- slides/02.md 'course/课程内容/02 - 从「回答」到「执行」.md' && git add -- slides/02.md 'course/课程内容/02 - 从「回答」到「执行」.md' && git diff --cached --stat && git commit -m 'feat(slides): add lesson 2 recap and concept summary'","yield_time_ms":1000,"max_output_tokens":1500}));

Script completed
Wall time 0.3 seconds
Output:

{"chunk_id":"ed93d4","wall_time_seconds":0.086283417,"exit_code":0,"original_token_count":88,"output":" ...200\\214\\346\\211\\247\\350\\241\\214\\343\\200\\215.md\" | 38 +++++++++++-\n slides/02.md                                       | 67 ++++++++++++++++++++++\n 2 files changed, 102 insertions(+), 3 deletions(-)\n[feat/lesson-02-authoring-workflow 4465a30] feat(slides): add lesson 2 recap and concept summary\n 2 files changed, 102 insertions(+), 3 deletions(-)\n"}

11:06:14运行 git push gitlab HEAD:feat/lesson-02-authoring-workflow 等 2 条命令

text(await tools.exec_command({cmd:"git push gitlab HEAD:feat/lesson-02-authoring-workflow","yield_time_ms":1000,"max_output_tokens":1500}));
text(await tools.exec_command({cmd:"python3 - <<'PY'\nfrom pathlib import Path\nimport json\nj=json.loads(Path('/tmp/ai-literacy-mr12.json').read_text())\ns=j['description']\ns=s.replace('共七页正文、两页章节过渡和一页 Q&A。结束页以', '共七页正文、两页章节过渡、一页课堂总结和一页 Q&A。课堂总结用「任务 → Agent → 待检查结果」回顾工作推进与人的关键判断，概念区沿用第一讲的小图标、名称和一句定义格式，集中列

…（中间省略 346 字）…

escription':s},ensure_ascii=False))\nprint('MR description prepared; title retained.')\nPY","max_output_tokens":500}));

Script completed
Wall time 1.3 seconds
Output:

{"chunk_id":"78375a","wall_time_seconds":1.002238833,"session_id":84611,"original_token_count":0,"output":""}
{"chunk_id":"33b22e","wall_time_seconds":0.000004416,"exit_code":0,"original_token_count":11,"output":"MR description prepared; title retained.\n"}

11:06:19运行代码

text(await tools.write_stdin({session_id:84611,chars:"","yield_time_ms":1000,"max_output_tokens":1000}));

Script completed
Wall time 0.0 seconds
Output:

{"chunk_id":"38a96b","wall_time_seconds":0.000001708,"exit_code":0,"original_token_count":78,"output":"remote: \nremote: View merge request for feat/lesson-02-authoring-workflow:        \nremote:   https://git.sunricher.top/smart/ai-agent/ai-literacy-series/-/merge_requests/12        \nremote: \nTo git.sunricher.top:smart/ai-agent/ai-literacy-series.git\n   f12c605..4465a30  HEAD -> feat/lesson-02-authoring-workflow\n"}

11:06:30运行 glab api projects/339/merge_requests/12 --method PUT --input /tmp/ai-literacy-mr12-update.json > /tmp/ai-literacy-mr…

text(await tools.exec_command({cmd:"glab api projects/339/merge_requests/12 --method PUT --input /tmp/ai-literacy-mr12-update.json > /tmp/ai-literacy-mr12-updated.json\npython3 - <<'PY'\nimport json\nj=json.load(open('/tmp/ai-literacy-mr12-updated.json'))\ne=json.load(open('/tmp/ai-literacy-mr12-update.json'))\nprint(json.dumps({'url':j['web_url'],'sha':j['sha'],'state':j['state'],'description_matches':j['description']==e['description']},ensure_ascii=False))\nPY","max_output_tokens":500}));
text(await tools.exec_command({cmd:"git status --short","max_output_tokens":800}));

Script completed
Wall time 0.4 seconds
Output:

{"chunk_id":"2d3eb8","wall_time_seconds":0.203561,"exit_code":1,"original_token_count":27,"output":"glab: HTTP 415\nTraceback (most recent call last):\n  File \"<stdin>\", line 4, in <module>\nKeyError: 'web_url'\n"}
{"chunk_id":"de9f17","wall_time_seconds":0.000004417,"exit_code":0,"original_token_count":94,"output":" M \"course/\\347\\264\\240\\346\\235\\220\\344\\270\\216\\350\\215\\211\\347\\250

…（中间省略 260 字）…

\\347\\250\\213\\345\\206\\205\\345\\256\\271/03 - \\344\\270\\200\\346\\227\\245\\351\\241\\276\\351\\227\\256.md\"\n"}

11:06:40运行 glab api projects/339/merge_requests/12 --method PUT --header 'Content-Type: application/json' --input /tmp/ai-liter…

text(await tools.exec_command({cmd:"glab api projects/339/merge_requests/12 --method PUT --header 'Content-Type: application/json' --input /tmp/ai-literacy-mr12-update.json > /tmp/ai-literacy-mr12-updated.json\npython3 - <<'PY'\nimport json\nj=json.load(open('/tmp/ai-literacy-mr12-updated.json'))\ne=json.load(open('/tmp/ai-literacy-mr12-update.json'))\nprint(json.dumps({'url':j['web_url'],'sha':j['sha'],'state':j['state'],'description_matches':j['description']==e['description']},ensure_ascii=False))\nPY","max_output_tokens":500}));

Script completed
Wall time 1.4 seconds
Output:

{"chunk_id":"2b5fcb","wall_time_seconds":1.187141583,"exit_code":0,"original_token_count":48,"output":"{\"url\": \"https://git.sunricher.top/smart/ai-agent/ai-literacy-series/-/merge_requests/12\", \"sha\": \"4465a30762c63cb439d92f8a7a00019c3ef4499e\", \"state\": \"opened\", \"description_matches\": true}\n"}

已提交并推送到 MR !12，提交为 4465a30。

MR 描述已更新；本次仅包含总结页与对应讲稿，尚未合并。
MR 我已经合并了，发不到 cloudflare 吧
我理解你是要把合并后的版本发布到 Cloudflare。我先确认主分支和现有发布流程，再执行发布并检查线上第二讲。

干了不到 1 分钟，3 步

运行 7 条命令

11:09:52运行 rg -n 'Cloudflare|cloudflare|部署|发布|wrangler' ~/.codex/memories/MEMORY.md 等 3 条命令

const r=await Promise.allSettled([
tools.exec_command({cmd:"rg -n 'Cloudflare|cloudflare|部署|发布|wrangler' ~/.codex/memories/MEMORY.md","max_output_tokens":2200}),
tools.exec_command({cmd:"git status --short && rg -n 'Cloudflare|cloudflare|deploy|wrangler|pages' README.md package.json .gitlab-ci.yml .github/workflows scripts --glob '!*.lock'","max_output_tokens":4500}),
tools.exec_command({cmd:"glab mr view 12 --output json > /tmp/ai-literacy-mr12-

…（中间省略 175 字）…

t','target_branch','web_url']},ensure_ascii=False))\nPY","max_output_tokens":500})
]);r.forEach((v,i)=>text({i,...v}));

Script completed
Wall time 1.4 seconds
Output:

{"i":0,"status":"fulfilled","value":{"chunk_id":"ead749","wall_time_seconds":0.00000225,"exit_code":0,"original_token_count":199,"output":"46:- rollout_summaries/2026-09-03T02-40-21-soa2-obsidian_slidev_multideck_cloudflare_pages_deployment.md (cwd=~/code/ai-literacy-series, rollout_path=~/.codex/sessions/2026/09/03/rollout-2026-09-03T10-40-21-01a06523-8486-7653-ac0d-33a73e0e124e.jsonl, updated_at=2

…（中间省略 1977 字）…

anch\": \"main\", \"web_url\": \"https://git.sunricher.top/smart/ai-agent/ai-literacy-series/-/merge_requests/12\"}\n"}}

11:10:08运行 sed -n '28,58p' README.md && cat package.json && cat scripts/build-slides.mjs && cat .gitlab-ci.yml 等 3 条命令

const r=await Promise.allSettled([
tools.exec_command({cmd:"sed -n '28,58p' README.md && cat package.json && cat scripts/build-slides.mjs && cat .gitlab-ci.yml","max_output_tokens":3500}),
tools.exec_command({cmd:"sed -n '185,210p' ~/.codex/memories/MEMORY.md && cat ~/.codex/memories/rollout_summaries/2026-09-03T02-40-21-soa2-obsidian_slidev_multideck_cloudflare_pages_deployment.md","max_output_tokens":4000}),
tools.exec_command({cmd:"git fetch g

…（中间省略 193 字）…

assword|environments/i.test(x.name+" "+x.description)).map(x=>({name:x.name,description:x.description.slice(0,180)})));

Script completed
Wall time 1.2 seconds
Output:

{"i":0,"status":"fulfilled","value":{"chunk_id":"8f727a","wall_time_seconds":0.000003,"exit_code":0,"original_token_count":1053,"output":"\n首次使用时运行 `pnpm install`。\n\n```bash\npnpm slides slides/01.md\npnpm run slides:build slides/01.md\n```\n\n将 `01` 替换为当前讲次。设计依据与评审标准见 [幻灯片设计指南](slides/DESIGN.md)，逐页制作与验证规则见 [slides/AGENTS.md](slides/AGENTS.md)。\n\n## 全量验证与发布\n\n只在一批课件准备交付时运行：\n\n```bash\npnpm run s

…（中间省略 16094 字）…

ts. You can list, create, and rename Environments, read and update environment variables, and create and list local ."}]

11:10:23运行 cat wrangler.jsonc && pnpm exec wrangler whoami > /tmp/ai-literacy-cloudflare-auth.log 2>&1

text(await tools.write_stdin({session_id:52768,chars:"","yield_time_ms":1000,"max_output_tokens":800}));
text(await tools.exec_command({cmd:"cat wrangler.jsonc && pnpm exec wrangler whoami > /tmp/ai-literacy-cloudflare-auth.log 2>&1","yield_time_ms":1000,"max_output_tokens":500}));

Script completed
Wall time 1.2 seconds
Output:

{"chunk_id":"86f465","wall_time_seconds":0.000001958,"exit_code":0,"original_token_count":53,"output":"From git.sunricher.top:smart/ai-agent/ai-literacy-series\n * branch            main       -> FETCH_HEAD\n2a13e284e155aab9af409399fe66fabc0dd5c1dd Merge branch 'feat/lesson-02-authoring-workflow' into 'main'\n  main\n"}
{"chunk_id":"3704bd","wall_time_seconds":1.0011885,"session_id":98064,"original_

…（中间省略 100 字）…

e\": \"ai-literacy-series\",\n  \"compatibility_date\": \"2026-09-03\",\n  \"pages_build_output_dir\": \"./dist\"\n}\n"}

11:10
MR 已合并，主分支包含刚确认的总结页。现有 GitLab 流程只做检查，发布需要单独执行；我会从合并后的版本构建，避免把本地尚未提交的第三讲改动带到线上。

干了 3 分钟，6 步

运行 12 条命令

11:10:38运行 git worktree add --detach /tmp/ai-literacy-deploy-2a13e28 2a13e284e155aab9af409399fe66fabc0dd5c1dd && ln -s ~

text(await tools.exec_command({cmd:"git worktree add --detach /tmp/ai-literacy-deploy-2a13e28 2a13e284e155aab9af409399fe66fabc0dd5c1dd && ln -s ~/code/ai-literacy-series/node_modules /tmp/ai-literacy-deploy-2a13e28/node_modules","yield_time_ms":1000,"max_output_tokens":600}));
text(await tools.write_stdin({session_id:98064,chars:"","yield_time_ms":1000,"max_output_tokens":300}));
text(await tools.exec_command({cmd:"python3 - <<'PY'\nfrom pathlib 

…（中间省略 98 字）…

med:', 'You are logged in' in s)\nprint('Authentication error present:', 'ERROR' in s)\nPY","max_output_tokens":300}));

Script completed
Wall time 1.5 seconds
Output:

{"chunk_id":"a3bd2a","wall_time_seconds":0.000002125,"exit_code":0,"original_token_count":32,"output":"Preparing worktree (detached HEAD 2a13e28)\nHEAD is now at 2a13e28 Merge branch 'feat/lesson-02-authoring-workflow' into 'main'\n"}
{"chunk_id":"dbf2b7","wall_time_seconds":1.3328926669999999,"exit_code":1,"original_token_count":0,"output":""}
{"chunk_id":"1d458c","wall_time_seconds":0.000002458,"exit_code":0,"original_token_count":16,"output":"OAuth login confirmed: False\nAuthentication error present: True\n"}

11:11:05运行 rg -n -A6 -B2 'ERROR|Error|error|keyring|login' /tmp/ai-literacy-cloudflare-auth.log 等 2 条命令

text(await tools.exec_command({cmd:"rg -n -A6 -B2 'ERROR|Error|error|keyring|login' /tmp/ai-literacy-cloudflare-auth.log","max_output_tokens":1500}));
text(await tools.exec_command({cmd:"pnpm run slides:build:all > /tmp/ai-literacy-deploy-build.log 2>&1","workdir":"/tmp/ai-literacy-deploy-2a13e28","yield_time_ms":1000,"max_output_tokens":600}));

Script completed
Wall time 0.7 seconds
Output:

{"chunk_id":"1ee7ac","wall_time_seconds":0.000005042,"exit_code":0,"original_token_count":84,"output":"15-\n16-\n17:\u001b[31m✘ \u001b[41;31m[\u001b[41;97mERROR\u001b[41;31m]\u001b[0m \u001b[1mfetch failed\u001b[0m\n18-\n19-\n20-\u001b[32mIf you think this is a bug then please create an issue at https://github.com/cloudflare/workers-sdk/issues/new/choose\u001b[0m\n21-🪵  Logs were written to \"~/Lib

…（中间省略 59 字）…

4_059.log\"\n"}
{"chunk_id":"8e6139","wall_time_seconds":0.414263667,"exit_code":1,"original_token_count":0,"output":""}

11:11:16运行 tail -24 /tmp/ai-literacy-deploy-build.log 等 3 条命令

const r=await Promise.allSettled([
tools.exec_command({cmd:"tail -24 /tmp/ai-literacy-deploy-build.log","max_output_tokens":1800}),
tools.exec_command({cmd:"python3 - <<'PY'\nimport os\nfrom pathlib import Path\ns=Path('/tmp/ai-literacy-cloudflare-auth.log').read_text()\nprint(s[:1800])\nfor k in ['HTTP_PROXY','HTTPS_PROXY','ALL_PROXY','http_proxy','https_proxy','all_proxy']:\n print(k, 'set' if os.environ.get(k) else 'unset')\nPY","max_output_to

…（中间省略 64 字）…

ps://api.cloudflare.com/client/v4/","yield_time_ms":1000,"max_output_tokens":600})
]);r.forEach((v,i)=>text({i,...v}));

Script completed
Wall time 1.2 seconds
Output:

{"i":0,"status":"fulfilled","value":{"chunk_id":"e92204","wall_time_seconds":0.000004209,"exit_code":0,"original_token_count":381,"output":"[ERR_PNPM_UNSAFE_MODULES_DIR] Refusing to remove the modules directory at \"~/code/ai-literacy-series/node_modules\" because its resolved target is not a strict subdirectory of the project root at \"/private/tmp/ai-literacy-deploy-2a13e28\".\n[ERROR] Command fai

…（中间省略 2675 字）…

   0 --:--:-- --:--:-- --:--:--     0\r  0     0    0     0    0     0      0      0 --:--:--  0:00:01 --:--:--     0"}}

11:12:48运行 python3 - <<'PY' 等 2 条命令

text(await tools.exec_command({cmd:"python3 - <<'PY'\nfrom pathlib import Path\np=Path('/tmp/ai-literacy-deploy-2a13e28/node_modules')\nassert p.is_symlink()\np.unlink()\nPY\npnpm install --frozen-lockfile --offline > /tmp/ai-literacy-deploy-install.log 2>&1","workdir":"/tmp/ai-literacy-deploy-2a13e28","yield_time_ms":1000,"max_output_tokens":500}));
text(await tools.exec_command({cmd:"scutil --proxy","max_output_tokens":900}));

Script completed
Wall time 1.2 seconds
Output:

{"chunk_id":"d6f470","wall_time_seconds":1.001753459,"session_id":75562,"original_token_count":0,"output":""}
{"chunk_id":"165e9e","wall_time_seconds":0.000002916,"exit_code":0,"original_token_count":205,"output":"<dictionary> {\n  ExceptionsList : <array> {\n    0 : localhost\n    1 : *.local\n    2 : injections.adguard.org\n    3 : local.adguard.org\n    4 : captive.apple.com\n    5 : guzzoni.appl

…（中间省略 538 字）…

 : 6152\n  HTTPSProxy : 127.0.0.1\n  ProxyAutoConfigEnable : 0\n  ProxyAutoDiscoveryEnable : 0\n  SOCKSEnable : 0\n}\n"}

11:12:58运行 HTTPS_PROXY=http://127.0.0.1:6152 HTTP_PROXY=http://127.0.0.1:6152 pnpm exec wrangler whoami > /tmp/ai-literacy-clou…

text(await tools.exec_command({cmd:"HTTPS_PROXY=http://127.0.0.1:6152 HTTP_PROXY=http://127.0.0.1:6152 pnpm exec wrangler whoami > /tmp/ai-literacy-cloudflare-auth-proxy.log 2>&1","yield_time_ms":1000,"max_output_tokens":500}));
text(await tools.write_stdin({session_id:75562,chars:"","yield_time_ms":1000,"max_output_tokens":600}));
text(await tools.write_stdin({session_id:63864,chars:"","yield_time_ms":1000,"max_output_tokens":800}));

Script completed
Wall time 1.2 seconds
Output:

{"chunk_id":"6f6784","wall_time_seconds":1.001157666,"session_id":58075,"original_token_count":0,"output":""}
{"chunk_id":"970d52","wall_time_seconds":0.000001417,"exit_code":0,"original_token_count":0,"output":""}
{"chunk_id":"e9114d","wall_time_seconds":0.0000015,"exit_code":0,"original_token_count":280,"output":"\r  0     0    0     0    0     0      0      0 --:--:--  0:00:02 --:--:--     0\r  0

…（中间省略 953 字）…

=/; Domain=api.cloudflare.com; Expires=Mon, 07 Sep 2026 03:41:18 GMT\r\n\r\n      0 --:--:--  0:00:02 --:--:--     0\n"}

11:13:07运行 pnpm run slides:build:all > /tmp/ai-literacy-deploy-build.log 2>&1 等 2 条命令

text(await tools.exec_command({cmd:"pnpm run slides:build:all > /tmp/ai-literacy-deploy-build.log 2>&1","workdir":"/tmp/ai-literacy-deploy-2a13e28","yield_time_ms":1000,"max_output_tokens":500}));
text(await tools.write_stdin({session_id:58075,chars:"","yield_time_ms":1000,"max_output_tokens":500}));
text(await tools.exec_command({cmd:"python3 - <<'PY'\nfrom pathlib import Path\ns=Path('/tmp/ai-literacy-cloudflare-auth-proxy.log').read_text()\nprint('OAuth login confirmed:', 'You are logged in' in s)\nprint('Authentication error present:', 'ERROR' in s)\nPY","max_output_tokens":300}));

Script completed
Wall time 2.2 seconds
Output:

{"chunk_id":"48044a","wall_time_seconds":1.00073675,"session_id":50313,"original_token_count":0,"output":""}
{"chunk_id":"f188f2","wall_time_seconds":1.006103125,"exit_code":0,"original_token_count":0,"output":""}
{"chunk_id":"476374","wall_time_seconds":0.000002375,"exit_code":0,"original_token_count":16,"output":"OAuth login confirmed: True\nAuthentication error present: False\n"}

发布工具刚才遇到了网络连接问题，接入本机现有代理后已恢复，Cloudflare 登录也已确认有效。现在正在构建两讲课件，完成后会上传并检查线上总结页。

干了 1 分钟，6 步

运行 8 条命令

11:13:23运行 python3 -m unittest discover -s tests > /tmp/ai-literacy-deploy-tests.log 2>&1 等 2 条命令

text(await tools.exec_command({cmd:"python3 -m unittest discover -s tests > /tmp/ai-literacy-deploy-tests.log 2>&1","workdir":"/tmp/ai-literacy-deploy-2a13e28","yield_time_ms":1000,"max_output_tokens":500}));
text(await tools.write_stdin({session_id:50313,chars:"","yield_time_ms":1000,"max_output_tokens":500}));
text(await tools.exec_command({cmd:"tail -3 /tmp/ai-literacy-deploy-build.log && tail -4 /tmp/ai-literacy-deploy-tests.log && git status --short","workdir":"/tmp/ai-literacy-deploy-2a13e28","max_output_tokens":500}));

Script completed
Wall time 0.2 seconds
Output:

{"chunk_id":"8cefaa","wall_time_seconds":0.000003042,"exit_code":1,"original_token_count":0,"output":""}
{"chunk_id":"478efb","wall_time_seconds":8.75e-7,"exit_code":0,"original_token_count":0,"output":""}
{"chunk_id":"cdc09e","wall_time_seconds":0.000002792,"exit_code":0,"original_token_count":149,"output":"../dist/02/assets/index-C2EIJhMr.js                                                   144.77

…（中间省略 389 字）…

tError('Start directory is not importable: %r' % start_dir)\nImportError: Start directory is not importable: 'tests'\n"}

11:13:42运行 HTTPS_PROXY=http://127.0.0.1:6152 HTTP_PROXY=http://127.0.0.1:6152 pnpm exec wrangler pages deploy dist --project-na…

text(await tools.exec_command({cmd:"HTTPS_PROXY=http://127.0.0.1:6152 HTTP_PROXY=http://127.0.0.1:6152 pnpm exec wrangler pages deploy dist --project-name ai-literacy-series --branch main --commit-hash 2a13e284e155aab9af409399fe66fabc0dd5c1dd > /tmp/ai-literacy-cloudflare-deploy.log 2>&1","workdir":"/tmp/ai-literacy-deploy-2a13e28","yield_time_ms":1000,"max_output_tokens":500}));
text(await tools.exec_command({cmd:"nl -ba ~/.codex/memories/rollout_summaries/2026-09-03T02-40-21-soa2-obsidian_slidev_multideck_cloudflare_pages_deployment.md | sed -n '51,65p;85,99p'","max_output_tokens":1200}));

Script completed
Wall time 1.2 seconds
Output:

{"chunk_id":"ec8777","wall_time_seconds":1.001241166,"session_id":67458,"original_token_count":0,"output":""}
{"chunk_id":"e6a536","wall_time_seconds":0.000004125,"exit_code":0,"original_token_count":683,"output":"    51\t\n    52\tOutcome: success\n    53\t\n    54\tKey steps:\n    55\t- 新增 `scripts/build-slides.mjs`：自动发现 `slides/` 下匹配 `NN.md` 的讲次，分别构建到 `dist/NN`，设置 `/NN/` base，生成根课程目录。\n    56\t- 

…（中间省略 1446 字）…

v`、预览通配域名，以及未来的自定义域名；推荐具体邮箱白名单 + OTP，不能只配置“任何有效邮箱”的 One-time PIN。\n    99\t- 明确说明 Access 只能阻止未来访问，不能收回已被下载、截图或转发的副本。\n"}

11:13:49运行 tail -8 /tmp/ai-literacy-cloudflare-deploy.log

text(await tools.write_stdin({session_id:67458,chars:"","yield_time_ms":1000,"max_output_tokens":500}));
text(await tools.exec_command({cmd:"tail -8 /tmp/ai-literacy-cloudflare-deploy.log","max_output_tokens":700}));

Script completed
Wall time 5.1 seconds
Output:

{"chunk_id":"994633","wall_time_seconds":5.000794666,"session_id":67458,"original_token_count":0,"output":""}
{"chunk_id":"13f892","wall_time_seconds":0.000003875,"exit_code":0,"original_token_count":83,"output":"\u001b[33m▲ \u001b[43;33m[\u001b[43;30mWARNING\u001b[43;33m]\u001b[0m \u001b[1mProxy environment variables detected. We'll use your proxy for fetch requests.\u001b[0m\n\n\n\n ⛅️ wrangler 4.128.0 (update available 4.129.0)\n───────────────────────────────────────────────\n"}

11:14:04运行 tail -12 /tmp/ai-literacy-cloudflare-deploy.log

text(await tools.write_stdin({session_id:67458,chars:"","yield_time_ms":1000,"max_output_tokens":500}));
text(await tools.exec_command({cmd:"tail -12 /tmp/ai-literacy-cloudflare-deploy.log","max_output_tokens":1200}));

Script completed
Wall time 5.1 seconds
Output:

{"chunk_id":"4e16a4","wall_time_seconds":5.000559666,"session_id":67458,"original_token_count":0,"output":""}
{"chunk_id":"46325a","wall_time_seconds":0.000004125,"exit_code":0,"original_token_count":94,"output":"\u001b[33m▲ \u001b[43;33m[\u001b[43;30mWARNING\u001b[43;33m]\u001b[0m \u001b[1mProxy environment variables detected. We'll use your proxy for fetch requests.\u001b[0m\n\n\n\n ⛅️ wrangler 4.128.0 (update available 4.129.0)\n───────────────────────────────────────────────\nUploading... (50/181)\nUploading... (94/181)\n"}

11:14:16运行 tail -8 /tmp/ai-literacy-cloudflare-deploy.log

text(await tools.write_stdin({session_id:67458,chars:"","yield_time_ms":1000,"max_output_tokens":500}));
text(await tools.exec_command({cmd:"tail -8 /tmp/ai-literacy-cloudflare-deploy.log","max_output_tokens":1000}));

Script completed
Wall time 5.1 seconds
Output:

{"chunk_id":"f93f91","wall_time_seconds":5.001444833,"session_id":67458,"original_token_count":0,"output":""}
{"chunk_id":"d35e3b","wall_time_seconds":0.000004792,"exit_code":0,"original_token_count":94,"output":"\u001b[33m▲ \u001b[43;33m[\u001b[43;30mWARNING\u001b[43;33m]\u001b[0m \u001b[1mProxy environment variables detected. We'll use your proxy for fetch requests.\u001b[0m\n\n\n\n ⛅️ wrangler 4.128.0 (update available 4.129.0)\n───────────────────────────────────────────────\nUploading... (50/181)\nUploading... (94/181)\n"}

11:14:25运行 tail -8 /tmp/ai-literacy-cloudflare-deploy.log

text(await tools.write_stdin({session_id:67458,chars:"","yield_time_ms":10000,"max_output_tokens":500}));
text(await tools.exec_command({cmd:"tail -8 /tmp/ai-literacy-cloudflare-deploy.log","max_output_tokens":1000}));

Script completed
Wall time 10.1 seconds
Output:

{"chunk_id":"8a4c01","wall_time_seconds":10.000489209,"session_id":67458,"original_token_count":0,"output":""}
{"chunk_id":"32d9d1","wall_time_seconds":0.000005291,"exit_code":0,"original_token_count":66,"output":"\n\n\n ⛅️ wrangler 4.128.0 (update available 4.129.0)\n───────────────────────────────────────────────\nUploading... (50/181)\nUploading... (94/181)\nUploading... (137/181)\n"}

两讲构建已通过，文件正在上传。另发现一个独立的 CI 配置问题：它仍引用已不存在的 tests/ 目录；这不影响本次静态课件发布，但后续需要修正。

干了 1 分钟，9 步

运行 2 条命令，运行 1 段代码，其他操作 6 次

11:14:44运行 tail -10 /tmp/ai-literacy-cloudflare-deploy.log

text(await tools.write_stdin({session_id:67458,chars:"","yield_time_ms":10000,"max_output_tokens":500}));
text(await tools.exec_command({cmd:"tail -10 /tmp/ai-literacy-cloudflare-deploy.log","max_output_tokens":1000}));

Script completed
Wall time 6.3 seconds
Output:

{"chunk_id":"f39258","wall_time_seconds":6.257866041,"exit_code":0,"original_token_count":0,"output":""}
{"chunk_id":"d4e696","wall_time_seconds":0.000002958,"exit_code":0,"original_token_count":83,"output":"Uploading... (94/181)\nUploading... (137/181)\nUploading... (181/181)\n✨ Success! Uploaded 131 files (50 already uploaded) (50.35 sec)\n\n✨ Compiled Worker successfully\n✨ Uploading Worker bundle\n✨ Uploading _routes.json\n🌎 Deploying...\n✨ Deployment complete! Take a peek over at https://5ee216de.ai-literacy-series.pages.dev\n"}

11:14:56打开线上第二讲总结页进行验收

{
  "code": "let liveSummary = await cua.createBrowserTab('iab','https://ai-literacy-series.pages.dev/02/10',{visible:false});",
  "title": "打开线上第二讲总结页进行验收"
}

Wall time: 9.3059 seconds
Output:
Browser tab: 7, Title: "从「回答」到「执行」 - Slidev", URL: "https://ai-literacy-series.pages.dev/02/10".
0 AXWebArea 从「回答」到「执行」 - Slidev, URL: ai-literacy-series.pages.dev/02/10
	1 container app
		2 container slide-container
			3 container slide-content
				4 container
					5 heading 4 课堂总结 — 一项工作交给 Agent 之后, Value: 1
						6 text 4 课堂总结  — 一项工作交给 Agent 之后
					7 container 任务交给 Agent，由它接着读取、处理和保存材料，留下待检查的工作结果；人确定范围、回答关键疑

…（中间省略 746 字）…

				34 text 10  / 11

The focused UI element is 0 AXWebArea 从「回答」到「执行」 - Slidev, URL: ai-literacy-series.pages.dev/02/10

11:15:17运行 python3 - <<'PY'

text(await tools.exec_command({cmd:"python3 - <<'PY'\nfrom urllib.request import urlopen, build_opener, ProxyHandler\nfrom pathlib import Path\nimport re\nop=build_opener(ProxyHandler({'https':'http://127.0.0.1:6152'}))\nbase='https://ai-literacy-series.pages.dev'\nfor path in ['/', '/01/', '/01/15', '/02/', '/02/10', '/02/11']:\n with op.open(base+path,timeout=30) as r:\n  body=r.read().decode()\n  deck='01' if path.startswith('/01') else '02' i

…（中间省略 352 字）…

ext()\n  print(path, r.status, 'matches deployed build:',matched)\nPY","yield_time_ms":1000,"max_output_tokens":700}));

Script completed
Wall time 1.2 seconds
Output:

{"chunk_id":"462a67","wall_time_seconds":1.001274167,"session_id":82747,"original_token_count":0,"output":""}

11:15:22核对线上总结页的最终画面

{
  "code": "await liveSummary.getScreenshot();",
  "title": "核对线上总结页的最终画面"
}

Wall time: 0.1126 seconds
Output:
[图片]

11:15:34运行代码

text(await tools.write_stdin({session_id:82747,chars:"","yield_time_ms":1000,"max_output_tokens":700}));

Script completed
Wall time 0.0 seconds
Output:

{"chunk_id":"1a7bda","wall_time_seconds":0.00000225,"exit_code":1,"original_token_count":285,"output":"Traceback (most recent call last):\n  File \"<stdin>\", line 7, in <module>\n  File \"/opt/homebrew/Cellar/python@3.14/3.14.7/Frameworks/Python.framework/Versions/3.14/lib/python3.14/urllib/request.py\", line 493, in open\n    response = meth(req, response)\n  File \"/opt/homebrew/Cellar/python@3.1

…（中间省略 750 字）…

r_default\n    raise HTTPError(req.full_url, code, msg, hdrs, fp)\nurllib.error.HTTPError: HTTP Error 403: Forbidden\n"}

11:15:48确认线上构建版本与 Q&A 衔接

{
  "code": "nodeRepl.write(await liveSummary.playwright.evaluate(() => Array.from(document.querySelectorAll('script[src]')).map(e=>e.getAttribute('src')))); await liveSummary.pressKey('ArrowRight'); await liveSummary.getAXState();",
  "title": "确认线上构建版本与 Q&A 衔接"
}

Wall time: 0.3254 seconds
Output:
Browser tab: 7, Title: "从「回答」到「执行」 - Slidev", URL: "https://ai-literacy-series.pages.dev/02/11".
0 AXWebArea 从「回答」到「执行」 - Slidev, URL: ai-literacy-series.pages.dev/02/11
	1 container app
		2 container slide-container
			3 container slide-content
				35 container slideshow
					36 container
						37 heading 4 课堂总结 — 一项工作交给 Agent 之后, Value: 1
							38 text 4 课堂总结  — 一项工作交给 Agent 之后
						39 container 任务交给 Agent，由它

…（中间省略 953 字）…

I element is 0 AXWebArea 从「回答」到「执行」 - Slidev, URL: ai-literacy-series.pages.dev/02/11
[ '/02/assets/index-C2EIJhMr.js' ]

11:15:54核对线上课程目录

{
  "code": "let liveIndex = await cua.createBrowserTab('iab','https://ai-literacy-series.pages.dev/',{visible:false});",
  "title": "核对线上课程目录"
}

Wall time: 0.6832 seconds
Output:
Browser tab: 8, Title: "AI 通识课程", URL: "https://ai-literacy-series.pages.dev/".
0 AXWebArea AI 通识课程, URL: ai-literacy-series.pages.dev/
	1 heading AI 通识课程, Value: 1
		2 text AI 通识课程
	3 text 选择讲次进入 Slidev 幻灯片
	4 content list
		5 link Description: 01 AI 是这么说的, Value: ai-literacy-series.pages.dev/01/
		6 link Description: 02 从「回答」到「执行」, Value: ai-literacy-series.pages.dev/02/

The focused UI element is 0 AXWebArea AI 通识课程, URL: ai-literacy-series.pages.dev/

11:16:00确认第一讲入口仍正常

{
  "code": "await liveIndex.goto('https://ai-literacy-series.pages.dev/01/'); await liveIndex.getAXState();",
  "title": "确认第一讲入口仍正常"
}

Wall time: 1.5144 seconds
Output:
Browser tab: 8, Title: "AI 是这么说的 - Slidev", URL: "https://ai-literacy-series.pages.dev/01/".
1 AXWebArea AI 是这么说的 - Slidev, URL: ai-literacy-series.pages.dev/01/

The focused UI element is 1 AXWebArea AI 是这么说的 - Slidev, URL: ai-literacy-series.pages.dev/01/

11:16:06完成线上两讲入口与总结页检查

{
  "code": "await liveIndex.getAXState(); await liveSummary.pressKey('ArrowLeft');",
  "title": "完成线上两讲入口与总结页检查"
}

Wall time: 0.4211 seconds
Output:
Browser tab: 8, Title: "AI 是这么说的 - Slidev", URL: "https://ai-literacy-series.pages.dev/01/1".
1 AXWebArea AI 是这么说的 - Slidev, URL: ai-literacy-series.pages.dev/01/1
	2 container app
		3 container slide-container
			4 container slide-content
				5 container
					6 heading AI 是这么说的, Value: 1
						7 text AI 是这么说的
					8 heading 第一讲 · 怎样判断 AI 的回答是否可靠？, Value: 2
						9 text 第一讲 · 怎样判断 AI 的回答是否可靠？
					10 text 从回答来源，到

…（中间省略 359 字）…

ons
				23 text 1  / 16

The focused UI element is 1 AXWebArea AI 是这么说的 - Slidev, URL: ai-literacy-series.pages.dev/01/1

11:16
已发布到 Cloudflare，使用合并后的主分支版本 2a13e28。

查看线上第二讲总结页。两讲构建通过，课程目录、第一讲入口、总结页及 Q&A 已检查正常。

另发现 CI 仍引用已删除的 tests/ 目录，需要后续修正，不影响此次发布。

<oai-mem-citation>
<citation_entries>
MEMORY.md:208-208|note=[existing production site and deep links]
rollout_summaries/2026-09-03T02-40-21-soa2-obsidian_slidev_multideck_cloudflare_pages_deployment.md:85-90|note=[reuse authorized local OAuth]
</citation_entries>
<rollout_ids>
01a06523-8486-7653-ac0d-33a73e0e124e
</rollout_ids>
</oai-mem-citation>
我发现第二讲没有封面诶，也要补一下
我先检查第二讲入口和第一讲封面的结构，再补上与课程风格一致的封面。

干了不到 1 分钟，1 步

运行 2 条命令

11:17:26运行 git status --short && sed -n '1,55p' slides/02.md && sed -n '1,62p' slides/01.md 等 2 条命令

const r=await Promise.allSettled([
tools.exec_command({cmd:"git status --short && sed -n '1,55p' slides/02.md && sed -n '1,62p' slides/01.md","max_output_tokens":3400}),
tools.exec_command({cmd:"sed -n '1,48p' 'course/课程内容/02 - 从「回答」到「执行」.md' && sed -n '174,207p' slides/DESIGN.md","max_output_tokens":2500})
]);r.forEach((v,i)=>text({i,...v}));

Script completed
Wall time 0.1 seconds
Output:

{"i":0,"status":"fulfilled","value":{"chunk_id":"3e0add","wall_time_seconds":0.000003083,"exit_code":0,"original_token_count":792,"output":" M \"course/\\347\\264\\240\\346\\235\\220\\344\\270\\216\\350\\215\\211\\347\\250\\277/02-\\347\\254\\254\\344\\272\\214\\350\\256\\262\\346\\234\\252\\351\\207\\207\\347\\224\\250\\347\\264\\240\\346\\235\\220.md\"\n D \"course/\\347\\264\\240\\346\\235\\220\\

…（中间省略 5032 字）…

了套模板制造一大一小。\n- 长句优先利用可用宽度，保留自然中文，不截断、隐藏或删去关键条件。内容实在放不下时重新组织布局。\n- 随讲述出现且预留位置，不推动或覆盖仍需核对的材料、来源。阶段关系放在主图对应位置，不挤入结论。\n\n"}}

11:17:44思考：**Preparing cover metadata**
Preparing cover metadata

确认了：第二讲入口直接引用了 1.1，所以打开后就是正文。我会在前面补一页封面，沿用第一讲的居中版式，标题用「从『回答』到『执行』」，副标题点出“Agent 怎样把工作继续做下去”。

干了 1 分钟，8 步

运行 5 条命令，其他操作 4 次

11:17:58运行 python3 - <<'PY'

text(await tools.exec_command({cmd:"python3 - <<'PY'\nfrom pathlib import Path\np=Path('~/Library/Mobile Documents/iCloud~md~obsidian/Documents/Note/Areas/大模型(LLM)/AI 通识课程/课程内容/02 - 从「回答」到「执行」.md')\ns=p.read_text().replace('status: 七页正文、两页过渡、课堂总结与 Q&A 已制作','status: 封面、七页正文、两页过渡、课堂总结与 Q&A 已制作')\na=s.index('## 1 AI 开始接手一项工作')\ns=s[:a]+'''## 封面\n\n# 从「回答」到「执行」\n\n**第二讲 · Agent 怎样把工作继续做下去？**\n\n从工作方式的变化，到 Agent 原理与控制取舍\n\n> [!note] PPT 画面\n> 沿用第一讲的 `

…（中间省略 287 字）…

ibrary/Mobile Documents/iCloud~md~obsidian/Documents/Note/Areas/大模型(LLM)/AI 通识课程/' course/","max_output_tokens":500}));

Script completed
Wall time 0.1 seconds
Output:

{"chunk_id":"bf6586","wall_time_seconds":0.000003791,"exit_code":0,"original_token_count":47,"output":".d..t.... ./\n.d..t.... 课�\\#213�\\#206\\#205容/\n>f.st.... 课�\\#213�\\#206\\#205容/02 - �\\#216�\\#200\\#214�\\#233\\#236�\\#255\\#224�\\#200\\#215�\\#210��\\#200\\#214�\\#211��\\#214�\\#200\\#215.md\n"}

11:18:22运行 python3 - <<'PY' 等 2 条命令

text(await tools.exec_command({cmd:"python3 - <<'PY'\nfrom pathlib import Path\np=Path('~/Library/Mobile Documents/iCloud~md~obsidian/Documents/Note/Areas/大模型(LLM)/AI 通识课程/课程内容/02 - 从「回答」到「执行」.md')\ns=p.read_text().replace('## 封面\\n\\n# 从「回答」到「执行」','## 封面\\n\\n**从「回答」到「执行」**')\np.write_text(s)\nPY\n./scripts/sync-course.sh\npython3 - <<'PY'\nfrom pathlib import Path\np=Path('slides/02.md');s=p.read_text()\ns=s.replace('title: 从「回答」到「执行」\\naspectR

…（中间省略 568 字）…

 --out /tmp/ai-literacy-02-cover > /tmp/ai-literacy-02-cover.log 2>&1","yield_time_ms":1000,"max_output_tokens":500}));

Script completed
Wall time 1.3 seconds
Output:

{"chunk_id":"24907c","wall_time_seconds":0.0000025,"exit_code":0,"original_token_count":0,"output":""}
{"chunk_id":"130e44","wall_time_seconds":1.001657792,"session_id":14964,"original_token_count":0,"output":""}

11:18:30预览第二讲新增封面

{
  "code": "let coverCheck = await cua.createBrowserTab('iab','http://localhost:3032/1',{visible:false});",
  "title": "预览第二讲新增封面"
}

Wall time: 0.4989 seconds
Output:
Browser tab: 9, Title: "从「回答」到「执行」 - Slidev", URL: "http://localhost:3032/1".
0 AXWebArea 从「回答」到「执行」 - Slidev, URL: localhost:3032/1

The focused UI element is 0 AXWebArea 从「回答」到「执行」 - Slidev, URL: localhost:3032/1

11:18:38运行 git diff --check -- slides/02.md 'course/课程内容/02 - 从「回答」到「执行」.md' && git diff --stat -- slides/02.md 'course/课程内容/02…

text(await tools.exec_command({cmd:"git diff --check -- slides/02.md 'course/课程内容/02 - 从「回答」到「执行」.md' && git diff --stat -- slides/02.md 'course/课程内容/02 - 从「回答」到「执行」.md'","max_output_tokens":500}));

Script completed
Wall time 0.1 seconds
Output:

{"chunk_id":"ec1ed5","wall_time_seconds":0.000002542,"exit_code":0,"original_token_count":52,"output":" ...43\\200\\214\\346\\211\\247\\350\\241\\214\\343\\200\\215.md\" | 15 ++++++++++++++-\n slides/02.md                                          | 19 +++++++++++++++++++\n 2 files changed, 33 insertions(+), 1 deletion(-)\n"}

11:18:43检查封面标题、副标题和留白

{
  "code": "await coverCheck.getScreenshot();",
  "title": "检查封面标题、副标题和留白"
}

Wall time: 0.3944 seconds
Output:
[图片]

11:18:57对照第一讲封面的实际样式

{
  "code": "let firstCover = await cua.createBrowserTab('iab','http://localhost:3030/1',{visible:false});",
  "title": "对照第一讲封面的实际样式"
}

Wall time: 0.4064 seconds
Output:
Browser tab: 10, Title: "AI æ˜¯è¿™ä¹ˆè¯´çš„ - Slidev", URL: "http://localhost:3030/1".
0 AXWebArea AI æ˜¯è¿™ä¹ˆè¯´çš„ - Slidev, URL: localhost:3030/1

The focused UI element is 0 AXWebArea AI æ˜¯è¿™ä¹ˆè¯´çš„ - Slidev, URL: localhost:3030/1

11:19:07运行 sed -n '1,88p' slides/styles/index.css && rg -n 'background|cover|defaultCover' node_modules/@slidev/theme-seriph/la…

text(await tools.exec_command({cmd:"sed -n '1,88p' slides/styles/index.css && rg -n 'background|cover|defaultCover' node_modules/@slidev/theme-seriph/layouts/cover.vue node_modules/@slidev/theme-seriph/styles/*.css node_modules/@slidev/theme-seriph/setup/*","max_output_tokens":2000}));
text(await tools.write_stdin({session_id:14964,chars:"","yield_time_ms":1000,"max_output_tokens":300}));

Script completed
Wall time 0.1 seconds
Output:

{"chunk_id":"fa8177","wall_time_seconds":0.0000035,"exit_code":1,"original_token_count":500,"output":":root {\n  --course-ink: #4e5f6c;\n  --course-ink-strong: #354552;\n  --course-muted: #8e999f;\n  --course-faint: #aeb5b9;\n  --course-rule: #e0e4e6;\n  --course-title: #5d8493;\n  --course-accent: #fb8f68;\n  --course-accent-soft: #fff4ef;\n  --course-text-heading: 20px;\n  --course-text-emphasis: 

…（中间省略 1776 字）…

iph/setup/*\n"}
{"chunk_id":"9d13f1","wall_time_seconds":0.000001125,"exit_code":0,"original_token_count":0,"output":""}

11:19:14核对封面一致性及进入正文的顺序

{
  "code": "await firstCover.getScreenshot(); await coverCheck.pressKey('ArrowRight'); await coverCheck.getAXState();",
  "title": "核对封面一致性及进入正文的顺序"
}

Wall time: 0.6498 seconds
Output:
Browser tab: 9, Title: "从「回答」到「执行」 - Slidev", URL: "http://localhost:3032/2".
0 AXWebArea 从「回答」到「执行」 - Slidev, URL: localhost:3032/2
	1 container app
		2 container slide-container
			3 container slide-content
				4 container slideshow
					5 container
						6 heading 从「回答」到「执行」, Value: 1
							7 text 从「回答」到「执行」
						8 heading 第二讲 · Agent 怎样把工作继续做下去？, Value: 2
							9 text 第二讲 · Agent 怎样把工作继续做下去？
						10 text 

…（中间省略 1016 字）…

 More Options
				40 text 2  / 12

The focused UI element is 0 AXWebArea 从「回答」到「执行」 - Slidev, URL: localhost:3032/2
[图片]

封面已补上，版式与第一讲一致，翻页后进入原来的 1.1。第二讲现在共 12 页，原有页面顺延；正在完成最后的同步核对。

干了不到 1 分钟，2 步

运行 1 条命令，其他操作 1 次

11:19:27回到第二讲封面

{
  "code": "await coverCheck.pressKey('ArrowLeft');",
  "title": "回到第二讲封面"
}

Wall time: 0.0856 seconds
Output:

11:19:39运行 tail -1 /tmp/ai-literacy-02-cover.log

text(await tools.exec_command({cmd:"tail -1 /tmp/ai-literacy-02-cover.log\npython3 - <<'PY'\nfrom pathlib import Path\ns=Path('~/Library/Mobile Documents/iCloud~md~obsidian/Documents/Note/Areas/大模型(LLM)/AI 通识课程/课程内容/02 - 从「回答」到「执行」.md')\nr=Path('course/课程内容/02 - 从「回答」到「执行」.md')\nprint('source/mirror match:',s.read_bytes()==r.read_bytes())\nPY","max_output_tokens":300}));

Script completed
Wall time 0.1 seconds
Output:

{"chunk_id":"274ecb","wall_time_seconds":0.000002041,"exit_code":0,"original_token_count":12,"output":"✓ built in 1.48s\nsource/mirror match: True\n"}

已补上第二讲封面，沿用第一讲版式：
- 标题：从「回答」到「执行」
- 副标题：第二讲 · Agent 怎样把工作继续做下去？
现共 12 页，讲稿已同步，构建和翻页检查通过。封面尚未提交或发布。
11:23
可以啊，直接 push 到 main 并更新 cloudflare page 吧
我会把封面改动提交到 main 并推送，再更新 Cloudflare，最后检查线上封面和正文衔接。

干了 1 分钟，6 步

运行 7 条命令

11:24:17运行 git status --short && git branch --show-current && git diff --stat && git diff -- slides/02.md 'course/课程内容/02 - 从「回…

const r=await Promise.allSettled([
tools.exec_command({cmd:"git status --short && git branch --show-current && git diff --stat && git diff -- slides/02.md 'course/课程内容/02 - 从「回答」到「执行」.md'","max_output_tokens":3000}),
tools.exec_command({cmd:"git fetch gitlab main && git log -1 gitlab/main --format='%H %s'","yield_time_ms":1000,"max_output_tokens":500})
]);r.forEach((v,i)=>text({i,...v}));

Script completed
Wall time 1.2 seconds
Output:

{"i":0,"status":"fulfilled","value":{"chunk_id":"33c591","wall_time_seconds":0.000003,"exit_code":0,"original_token_count":1071,"output":" M \"course/\\347\\264\\240\\346\\235\\220\\344\\270\\216\\350\\215\\211\\347\\250\\277/02-\\347\\254\\254\\344\\272\\214\\350\\256\\262\\346\\234\\252\\351\\207\\207\\347\\224\\250\\347\\264\\240\\346\\235\\220.md\"\n D \"course/\\347\\264\\240\\346\\235\\220\\34

…（中间省略 3334 字）…

d","value":{"chunk_id":"104795","wall_time_seconds":1.00157075,"session_id":82831,"original_token_count":0,"output":""}}

11:24:44思考：**Applying changes to clean worktree**
Applying changes to clean worktree

11:24:46运行 git diff --stat HEAD gitlab/main && git -C /tmp/ai-literacy-deploy-2a13e28 status --short

text(await tools.write_stdin({session_id:82831,chars:"","yield_time_ms":1000,"max_output_tokens":500}));
text(await tools.exec_command({cmd:"git diff --stat HEAD gitlab/main && git -C /tmp/ai-literacy-deploy-2a13e28 status --short","max_output_tokens":500}));

Script completed
Wall time 0.1 seconds
Output:

{"chunk_id":"3f21d6","wall_time_seconds":0.00000175,"exit_code":0,"original_token_count":52,"output":"From git.sunricher.top:smart/ai-agent/ai-literacy-series\n * branch            main       -> FETCH_HEAD\n2a13e284e155aab9af409399fe66fabc0dd5c1dd Merge branch 'feat/lesson-02-authoring-workflow' into 'main'\n"}
{"chunk_id":"77e61c","wall_time_seconds":0.00000375,"exit_code":0,"original_token_count":0,"output":""}

11:24:54运行 git merge --ff-only gitlab/main && git diff --check -- slides/02.md 'course/课程内容/02 - 从「回答」到「执行」.md' && git add -- s…

text(await tools.exec_command({cmd:"git merge --ff-only gitlab/main && git diff --check -- slides/02.md 'course/课程内容/02 - 从「回答」到「执行」.md' && git add -- slides/02.md 'course/课程内容/02 - 从「回答」到「执行」.md' && git commit -m 'feat(slides): add lesson 2 cover' && git push gitlab HEAD:main","yield_time_ms":1000,"max_output_tokens":1000}));

Script completed
Wall time 0.1 seconds
Output:

{"chunk_id":"374269","wall_time_seconds":0.00000475,"exit_code":128,"original_token_count":67,"output":"hint: Diverging branches can't be fast-forwarded, you need to either:\nhint:\nhint: \tgit merge --no-ff\nhint:\nhint: or:\nhint:\nhint: \tgit rebase\nhint:\nhint: Disable this message with \"git config set advice.diverging false\"\nfatal: Not possible to fast-forward, aborting.\n"}

11:25:06运行 git log -5 --format='%h %p %s' HEAD && git log -4 --format='%h %p %s' gitlab/main && git status --short

text(await tools.exec_command({cmd:"git log -5 --format='%h %p %s' HEAD && git log -4 --format='%h %p %s' gitlab/main && git status --short","max_output_tokens":1400}));

Script completed
Wall time 0.1 seconds
Output:

{"chunk_id":"ea4b41","wall_time_seconds":0.000002792,"exit_code":0,"original_token_count":309,"output":"4465a30 f12c605 feat(slides): add lesson 2 recap and concept summary\nf12c605 b00735e docs(course): separate research from slide production\nb00735e b9b71aa chore(course): remove completed research and optimization plan\nb9b71aa a4402ac chore(course): simplify lecture indexes and remove obsolete m

…（中间省略 961 字）…

\\347\\250\\213\\345\\206\\205\\345\\256\\271/03 - \\344\\270\\200\\346\\227\\245\\351\\241\\276\\351\\227\\256.md\"\n"}

11:25:27思考：**Switching to detached main**
Switching to detached main

11:25:29运行 git merge-base --is-ancestor main gitlab/main && git fetch . refs/remotes/gitlab/main:refs/heads/main && git switch …

text(await tools.exec_command({cmd:"git merge-base --is-ancestor main gitlab/main && git fetch . refs/remotes/gitlab/main:refs/heads/main && git switch main && git diff --check -- slides/02.md 'course/课程内容/02 - 从「回答」到「执行」.md' && git add -- slides/02.md 'course/课程内容/02 - 从「回答」到「执行」.md' && git commit -m 'feat(slides): add lesson 2 cover' && git push gitlab main","yield_time_ms":1000,"max_output_tokens":1600}));

Script completed
Wall time 1.2 seconds
Output:

{"chunk_id":"482187","wall_time_seconds":1.002019708,"session_id":70322,"original_token_count":169,"output":"From .\n   1d0b938..2a13e28  gitlab/main -> main\nSwitched to branch 'main'\nM\t\"course/\\347\\264\\240\\346\\235\\220\\344\\270\\216\\350\\215\\211\\347\\250\\277/02-\\347\\254\\254\\344\\272\\214\\350\\256\\262\\346\\234\\252\\351\\207\\207\\347\\224\\250\\347\\264\\240\\346\\235\\220.md\"

…（中间省略 380 字）…

h 'gitlab/main'.\n[main 7339c21] feat(slides): add lesson 2 cover\n 2 files changed, 33 insertions(+), 1 deletion(-)\n"}

11:25:42运行 git status --short && git rev-parse HEAD && git -C /tmp/ai-literacy-deploy-2a13e28 status --short

text(await tools.write_stdin({session_id:70322,chars:"","yield_time_ms":1000,"max_output_tokens":700}));
text(await tools.exec_command({cmd:"git status --short && git rev-parse HEAD && git -C /tmp/ai-literacy-deploy-2a13e28 status --short","max_output_tokens":700}));

Script completed
Wall time 0.1 seconds
Output:

{"chunk_id":"57f93b","wall_time_seconds":0.000001625,"exit_code":0,"original_token_count":24,"output":"To git.sunricher.top:smart/ai-agent/ai-literacy-series.git\n   2a13e28..7339c21  main -> main\n"}
{"chunk_id":"6dfaad","wall_time_seconds":0.000002833,"exit_code":0,"original_token_count":104,"output":" M \"course/\\347\\264\\240\\346\\235\\220\\344\\270\\216\\350\\215\\211\\347\\250\\277/02-\\347\

…（中间省略 287 字）…

271/03 - \\344\\270\\200\\346\\227\\245\\351\\241\\276\\351\\227\\256.md\"\n7339c2161d6a5f67052ff1d37f350daf96bdf738\n"}

封面已推送到 main，提交为 7339c21。现在从这个版本更新 Cloudflare，本地第三讲和草稿区的未提交改动已保留。

干了 1 分钟，8 步

运行 4 条命令，其他操作 4 次

11:25:55运行 git switch --detach 7339c2161d6a5f67052ff1d37f350daf96bdf738 && HTTPS_PROXY=http://127.0.0.1:6152 HTTP_PROXY=http://…

text(await tools.exec_command({cmd:"git switch --detach 7339c2161d6a5f67052ff1d37f350daf96bdf738 && HTTPS_PROXY=http://127.0.0.1:6152 HTTP_PROXY=http://127.0.0.1:6152 pnpm run slides:deploy > /tmp/ai-literacy-cloudflare-cover-deploy.log 2>&1","workdir":"/tmp/ai-literacy-deploy-2a13e28","yield_time_ms":1000,"max_output_tokens":500}));

Script completed
Wall time 1.2 seconds
Output:

{"chunk_id":"03128a","wall_time_seconds":1.001775709,"session_id":65345,"original_token_count":38,"output":"Previous HEAD position was 2a13e28 Merge branch 'feat/lesson-02-authoring-workflow' into 'main'\nHEAD is now at 7339c21 feat(slides): add lesson 2 cover\n"}

11:26:06运行 tail -8 /tmp/ai-literacy-cloudflare-cover-deploy.log

text(await tools.write_stdin({session_id:65345,chars:"","yield_time_ms":10000,"max_output_tokens":500}));
text(await tools.exec_command({cmd:"tail -8 /tmp/ai-literacy-cloudflare-cover-deploy.log","max_output_tokens":1000}));

Script completed
Wall time 10.1 seconds
Output:

{"chunk_id":"f336bd","wall_time_seconds":10.001903041,"session_id":65345,"original_token_count":0,"output":""}
{"chunk_id":"5c64f9","wall_time_seconds":0.000005083,"exit_code":0,"original_token_count":67,"output":"\n\n\n ⛅️ wrangler 4.128.0 (update available 4.129.0)\n───────────────────────────────────────────────\nUploading... (150/182)\nUploading... (161/182)\nUploading... (172/182)\n"}

11:26:21运行 tail -9 /tmp/ai-literacy-cloudflare-cover-deploy.log

text(await tools.write_stdin({session_id:65345,chars:"","yield_time_ms":10000,"max_output_tokens":500}));
text(await tools.exec_command({cmd:"tail -9 /tmp/ai-literacy-cloudflare-cover-deploy.log","max_output_tokens":900}));

Script completed
Wall time 10.1 seconds
Output:

{"chunk_id":"1dc95c","wall_time_seconds":10.00160175,"session_id":65345,"original_token_count":0,"output":""}
{"chunk_id":"85f3ac","wall_time_seconds":0.000006,"exit_code":0,"original_token_count":61,"output":"Uploading... (161/182)\nUploading... (172/182)\nUploading... (182/182)\n✨ Success! Uploaded 32 files (150 already uploaded) (8.24 sec)\n\n✨ Compiled Worker successfully\n✨ Uploading Worker bundle\n✨ Uploading _routes.json\n🌎 Deploying...\n"}

11:26:36运行 tail -3 /tmp/ai-literacy-cloudflare-cover-deploy.log

text(await tools.write_stdin({session_id:65345,chars:"","yield_time_ms":10000,"max_output_tokens":500}));
text(await tools.exec_command({cmd:"tail -3 /tmp/ai-literacy-cloudflare-cover-deploy.log","max_output_tokens":500}));

Script completed
Wall time 0.1 seconds
Output:

{"chunk_id":"453045","wall_time_seconds":0.000001666,"exit_code":0,"original_token_count":0,"output":""}
{"chunk_id":"655fcb","wall_time_seconds":0.000009333,"exit_code":0,"original_token_count":34,"output":"✨ Uploading _routes.json\n🌎 Deploying...\n✨ Deployment complete! Take a peek over at https://5bcc17db.ai-literacy-series.pages.dev\n"}

11:26:42检查线上第二讲的新封面

{
  "code": "let publishedCover = await cua.createBrowserTab('iab','https://ai-literacy-series.pages.dev/02/1',{visible:false});",
  "title": "检查线上第二讲的新封面"
}

Wall time: 4.7504 seconds
Output:
Browser tab: 12, Title: "从「回答」到「执行」 - Slidev", URL: "https://ai-literacy-series.pages.dev/02/1".
0 AXWebArea 从「回答」到「执行」 - Slidev, URL: ai-literacy-series.pages.dev/02/1

The focused UI element is 0 AXWebArea 从「回答」到「执行」 - Slidev, URL: ai-literacy-series.pages.dev/02/1

11:26:53核对正式站点封面的实际画面

{
  "code": "await publishedCover.getScreenshot();",
  "title": "核对正式站点封面的实际画面"
}

Wall time: 0.3188 seconds
Output:
[图片]

11:27:05确认线上封面后进入第一张正文

{
  "code": "await publishedCover.pressKey('ArrowRight'); await publishedCover.getAXState();",
  "title": "确认线上封面后进入第一张正文"
}

Wall time: 0.2826 seconds
Output:
Browser tab: 12, Title: "从「回答」到「执行」 - Slidev", URL: "https://ai-literacy-series.pages.dev/02/2".
0 AXWebArea 从「回答」到「执行」 - Slidev, URL: ai-literacy-series.pages.dev/02/2
	1 container app
		2 container slide-container
			3 container slide-content
				4 container slideshow
					5 container
						6 heading 从「回答」到「执行」, Value: 1
							7 text 从「回答」到「执行」
						8 heading 第二讲 · Agent 怎样把工作继续做下去？, Value: 2
							9 text 第二

…（中间省略 829 字）…

s
				34 text 2  / 12

The focused UI element is 0 AXWebArea 从「回答」到「执行」 - Slidev, URL: ai-literacy-series.pages.dev/02/2

11:27:14返回线上封面

{
  "code": "await publishedCover.pressKey('ArrowLeft');",
  "title": "返回线上封面"
}

Wall time: 0.0815 seconds
Output:

已推送到 main（7339c21）并更新 Cloudflare。

查看线上第二讲封面。两讲构建通过，线上封面及进入正文的翻页已确认正常。
11:47
我们也更新一下七个阶段的第二个阶段？
我先定位“七个阶段”的第二阶段，核对现有内容与第二讲目前的完成状态，再更新对应部分。

干了 2 分钟，6 步

运行 8 条命令

11:47:32运行 rg -n '七个阶段|七阶段|第二阶段|阶段二|阶段 2|阶段2' course README.md plans .agents --glob '*.md'

text(await tools.exec_command({cmd:"rg -n '七个阶段|七阶段|第二阶段|阶段二|阶段 2|阶段2' course README.md plans .agents --glob '*.md'","max_output_tokens":2200}));

Script completed
Wall time 0.1 seconds
Output:

{"chunk_id":"97422b","wall_time_seconds":0.000004375,"exit_code":2,"original_token_count":1116,"output":"rg: plans: No such file or directory (os error 2)\ncourse/课程大纲.md:18:七阶段描述人和 Agent 的分工怎样逐步变化。它是课程的内部骨架，不是对人的能力排名；同一个人在不同任务上可能处于不同阶段。\ncourse/课程大纲.md:20:![工作中使用大模型与 Agent 的七个阶段](https://image.niracler.com/2026/08/71e07a9a1ea761bf5a7b87410ecb48e7.png)\ncourse/课程大纲.md:45:| 02 | 阶段 2：Agent 进入工作区 | **

…（中间省略 1513 字）…

程要建立哪些能力，学生的问题决定从哪里进入。** Tutorial 负责让学习实际发生，Diátaxis 则把理解、应用和查询需要分开承载。课程目标、课堂活动和验收方式还需要互相对齐，避免承诺一种变化，课堂却只练习另一件事。[^5]\n"}

11:47:42运行 sed -n '1,75p' course/课程大纲.md && sed -n '1,75p' course/课程设计/00-课程设计索引.md 等 2 条命令

const r=await Promise.allSettled([
tools.exec_command({cmd:"sed -n '1,75p' course/课程大纲.md && sed -n '1,75p' course/课程设计/00-课程设计索引.md","max_output_tokens":3500}),
tools.exec_command({cmd:"rg -n '七阶段|七个阶段' ~/.codex/memories/MEMORY.md && rg --files '~/Library/Mobile Documents/iCloud~md~obsidian/Documents/Note/Areas/大模型(LLM)' | rg '七|阶段'","max_output_tokens":1600})
]);r.forEach((v,i)=>text({i,...v}));

Script completed
Wall time 0.1 seconds
Output:

{"i":0,"status":"fulfilled","value":{"chunk_id":"a4eeeb","wall_time_seconds":0.000001833,"exit_code":0,"original_token_count":1934,"output":"---\naliases:\ntags:\ndate: 2026-08-18\nmodified: 2026-09-06\ntype: reference\n---\n本文定义面向公司混合职能同事的九讲 AI 通识课程。它规定课程要把学员带到哪里、九讲如何递进，以及所有讲次共同遵守的内容边界。每讲的具体内容以 `课程内容/` 中的对应讲稿为准；这些决定背后的设计理由见 [[01-为什么这样设计课程]]。\n\n## 1 课程概览\n\n1. **目标受众**：公司内产品、运营、销售、市场、职能和管理等混合岗位，不假设

…（中间省略 3224 字）…

ulfilled","value":{"chunk_id":"b78154","wall_time_seconds":0.000003,"exit_code":1,"original_token_count":0,"output":""}}

11:47:50运行 rg --files '~/Library/Mobile Documents/iCloud~md~obsidian/Documents/Note' | rg '七|阶段'

text(await tools.exec_command({cmd:"rg --files '~/Library/Mobile Documents/iCloud~md~obsidian/Documents/Note' | rg '七|阶段'","max_output_tokens":2200}));

Script completed
Wall time 0.1 seconds
Output:

{"chunk_id":"d58c8b","wall_time_seconds":0.000003375,"exit_code":0,"original_token_count":233,"output":"~/Library/Mobile Documents/iCloud~md~obsidian/Documents/Note/Areas/学习(Learn)/高效能人士的七个习惯课后分享 - 要事第一与行动力（企微版）.md\n~/Library/Mobile Documents/iCloud~md~obsidian/Documents/Note/Areas/学习(Learn)/高效能人士的七个习惯课后分享 - 要事第一与行动力.md\n~/Library/Mobile Documents/iCloud~md~obsidian/Documents/Note/Areas/大模型(LLM)/AI 

…（中间省略 207 字）…

从入门到精通共经历了几个阶段.md\n~/Library/Mobile Documents/iCloud~md~obsidian/Documents/Note/Areas/生活(Life)/《高效能人士的七个习惯》读后感什么的.md\n"}

11:48:02运行 rg -n '^#|阶段|Agent 进入' '~/Library/Mobile Documents/iCloud~md~obsidian/Documents/Note/Areas/大模型(LLM)/使用…

text(await tools.exec_command({cmd:"rg -n '^#|阶段|Agent 进入' '~/Library/Mobile Documents/iCloud~md~obsidian/Documents/Note/Areas/大模型(LLM)/使用 AI 开发从入门到精通共经历了几个阶段.md' '~/Library/Mobile Documents/iCloud~md~obsidian/Documents/Note/Areas/大模型(LLM)/AI 编程阶段-v2026.03.10.md'","max_output_tokens":2200}));
text(await tools.exec_command({cmd:"rg --files assets | rg 'stage|phase|阶段|七|ai'","max_output_tokens":800}));

Script completed
Wall time 0.1 seconds
Output:

{"chunk_id":"2c52cd","wall_time_seconds":0.000005042,"exit_code":0,"original_token_count":3248,"output":"Warning: truncated output (original token count: 3248)\nTotal output lines: 62\n\n~/Library/Mobile Documents/iCloud~md~obsidian/Documents/Note/Areas/大模型(LLM)/AI 编程阶段-v2026.03.10.md:8:# AI 编程阶段\n~/Library/Mobile Documents/iCloud~md~obsidian/Documents/Note/Areas/大模型(LLM)/AI 编程阶段-v2026.03.10.md:10:#

…（中间省略 5713 字）…

econds":0.000002834,"exit_code":0,"original_token_count":12,"output":"assets/diagrams/ai-general-stages-mindmap.html\n"}

text(await tools.exec_command({cmd:"rg -n '阶段.?2|Agent 进入|工具调用|const stages|const data|stage-2' assets/diagrams/ai-general-stages-mindmap.html","max_output_tokens":1800}));

Script completed
Wall time 0.1 seconds
Output:

{"chunk_id":"355006","wall_time_seconds":0.000004875,"exit_code":0,"original_token_count":18,"output":"474:    const stages = [\n493:        title: \"Agent 进入工作区\",\n"}

11:48:52运行 sed -n '452,548p' assets/diagrams/ai-general-stages-mindmap.html && rg -n 'title>|七|阶段|export|png' assets/diagrams/a…

text(await tools.exec_command({cmd:"sed -n '452,548p' assets/diagrams/ai-general-stages-mindmap.html && rg -n 'title>|七|阶段|export|png' assets/diagrams/ai-general-stages-mindmap.html | head -20","max_output_tokens":2600}));

Script completed
Wall time 0.1 seconds
Output:

{"chunk_id":"1a9a44","wall_time_seconds":0.000003834,"exit_code":0,"original_token_count":1572,"output":"        id: \"prompt\",\n        title: \"从判断回答，到检查执行\",\n        english: \"先判断回答能否采用，再检查执行过程和真实结果 · 1—2\",\n        className: \"prompt\",\n        stages: [\"1\", \"2\"]\n      },\n      {\n        id: \"context\",\n        title: \"能做一次，不等于下次还能做好\",\n        english: \"Context、知识、工具和 Workflow

…（中间省略 3860 字）…

>\n587:        eureka: \"Multi-Agent 可能提高并行处理能力，但可靠性仍需验证。在将它视为成熟阶段前，需要确认 Orchestration（编排）和 Handoff（交接）的协调成本是否可控。\",\n"}

11:49:18思考：**Checking phase two labels**
Checking phase two labels
11:49:25思考：**Checking phase two labels** **我更新第二阶段标签**
Checking phase two labels

我更新第二阶段标签

找到了：七阶段图里的第二阶段还以“读取本地文件、检查执行计划”为主，和现在第二讲的重点不一致。

我会把它更新为“Agent 接手一项工作”：突出工具调用与 Agent Loop，以及人对目标、范围和结果的判断；Workspace 的详细解释留给第三阶段。文案按 tech-doc-style-chinese 规范整理。

干了 2 分钟，4 步

运行 6 条命令

11:49:32运行 cat ~/.agents/skills/tech-doc-style-chinese/SKILL.md 等 2 条命令

text(await tools.exec_command({cmd:"cat ~/.agents/skills/tech-doc-style-chinese/SKILL.md","max_output_tokens":3500}));
text(await tools.exec_command({cmd:"rg -n 'ai-general-stages-mindmap|71e07a9a1ea761bf5a7b87410ecb48e7|Agent 进入工作区' course assets --glob '*.md' --glob '*.html'","max_output_tokens":1500}));

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{"chunk_id":"62dcbc","wall_time_seconds":0.000003,"exit_code":0,"original_token_count":1867,"output":"---\nname: tech-doc-style-chinese\ndescription: 在撰写、改写、校对或审阅中文技术文档、产品文案、界面文案、Markdown 文档、API 说明、操作手册、故障排查或运维文档时使用。采用克制、准确、可扫读的中文技术写作风格；保留原文事实、限制和机器可读内容；按任务读取术语排版、API 状态文案、项目覆盖或受控中文技术写作参考。\n---\n\n# 中文技术文档与产品文案规范\n\n<!-- 作者：Fenng（GitHub：@Fenng） -->\n\n## 适用范围\n\n将本 Skill 用于中文技术内容的撰写、改写、校对和审阅，包括：\n\n-

…（中间省略 3337 字）…

与两页过渡已制作；结束页待审阅，确认状态见当前讲稿与单页任务 |\nassets/diagrams/ai-general-stages-mindmap.html:493:        title: \"Agent 进入工作区\",\n"}

11:49:49思考：**Updating graph links**
Updating graph links

11:49:52运行 sed -n '595,665p' assets/diagrams/ai-general-stages-mindmap.html && rg -n 'width:|height:|grid-template|stage-card' …

text(await tools.exec_command({cmd:"sed -n '595,665p' assets/diagrams/ai-general-stages-mindmap.html && rg -n 'width:|height:|grid-template|stage-card' assets/diagrams/ai-general-stages-mindmap.html | head -28 && node -e \"for (const m of ['playwright','playwright-chromium','@playwright/test']) {try {console.log(m,import.meta.resolve(m))}catch{}}\"","max_output_tokens":2300}));

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{"chunk_id":"51e8ee","wall_time_seconds":0.000004042,"exit_code":0,"original_token_count":1034,"output":"        phase: \"agent\",\n        hypothesis: true\n      }\n    ];\n\n    const phases = layers;\n    const branches = document.getElementById(\"branches\");\n    const mindmap = document.getElementById(\"mindmap\");\n    const stageById = new Map(stages.map(stage => [stage.id, stage]));\n\n   

…（中间省略 3891 字）…

t: 100%; }\n340:      min-height: 100%;\n355:      line-height: 1.5;\n362:      width: 14px;\n363:      height: 2px;\n"}

11:50:15思考：**Locating browser dependencies**
Locating browser dependencies
11:50:34思考：**Locating browser dependencies** **核对阶段文案与大纲图更新范围**
Locating browser dependencies

核对阶段文案与大纲图更新范围

11:50:39运行 python3 - <<'PY' 等 2 条命令

text(await tools.exec_command({cmd:"python3 - <<'PY'\nfrom pathlib import Path\np=Path('~/Library/Mobile Documents/iCloud~md~obsidian/Documents/Note/Areas/大模型(LLM)/AI 通识课程/课程大纲.md')\ns=p.read_text().replace('modified: 2026-09-06','modified: 2026-09-07',1)\ns=s.replace('阶段 2：Agent 进入工作区','阶段 2：Agent 接手一项工作')\ns=s.replace('七页正文与两页过渡已制作；结束页待审阅，确认状态见当前讲稿与单页任务','封面、七页正文、两页过渡、课堂总结与 Q&A 已制作并发布')\np.write_text(s)\nPY\n/usr/bin/rsync -ani --delete --exclu

…（中间省略 134 字）…

}));
text(await tools.exec_command({cmd:"ls node_modules/.pnpm | rg 'playwright|puppeteer'","max_output_tokens":800}));

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{"chunk_id":"79d4aa","wall_time_seconds":0.000002916,"exit_code":0,"original_token_count":20,"output":".d..t.... ./\n>f.st.... 课�\\#213大纲.md\n.d..t.... 课�\\#213�\\#206\\#205容/\n"}
{"chunk_id":"324bd4","wall_time_seconds":0.000003042,"exit_code":0,"original_token_count":13,"output":"playwright-chromium@1.62.1\nplaywright-core@1.62.1\n"}

11:51:03运行 ./scripts/sync-course.sh

text(await tools.exec_command({cmd:"./scripts/sync-course.sh\npython3 - <<'PY'\nfrom pathlib import Path\np=Path('assets/diagrams/ai-general-stages-mindmap.html');s=p.read_text();a=s.index('        id: \"2\",');b=s.index('        phase:',a)\ns=s[:a]+'''        id: \"2\",\n        title: \"Agent 接手一项工作\",\n        short: \"从逐步交接，到持续推进\",\n        role: \"由模型根据目标与反馈决定下一步、借助工具推进任务的整体系统\",\n        eureka: \"模型接上工具（Tool）后，可以请求执行动作，再根据结果继续判断。工具调用与 Age

…（中间省略 1060 字）…

('[data-stage-wrap=\"2\"]').innerText());\nawait browser.close();\nJS","yield_time_ms":1000,"max_output_tokens":800}));

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Output:

{"chunk_id":"c09768","wall_time_seconds":0.473556792,"exit_code":0,"original_token_count":164,"output":"2\nAgent 接手一项工作\n从逐步交接，到持续推进\n尤里卡　模型接上工具（Tool）后，可以请求执行动作，再根据结果继续判断。工具调用与 Agent Loop 让一项工作持续推进，减少人来回交接；行动能力扩大，也让判断偏差可能产生实际后果。\n能力证据　能说明 Agent、工具调用与 Agent Loop 的关系；交代目标和要求，限定材料与动作的范围，在关键疑问处补充判断，并检查结果是否可采用。\n典型误区　把能继续执行当成结果正确，认为开放的工具和操作范围越多越好，或用有限授权代替人的判断。\n"}

第二阶段的文字已更新，重点放在持续推进工作、保留关键判断和检查结果。我正在核对图中的排版，并同步大纲里的阶段名称、完成状态和配图。

干了 3 分钟，5 步

看 2 张图，运行 3 条命令，写 2 个文件

11:51:26运行 sed -n '46,61p' assets/diagrams/ai-general-stages-mindmap.html && sed -n '404,425p' assets/diagrams/ai-general-stage…

text(await tools.exec_command({cmd:"sed -n '46,61p' assets/diagrams/ai-general-stages-mindmap.html && sed -n '404,425p' assets/diagrams/ai-general-stages-mindmap.html && git diff --check -- assets/diagrams/ai-general-stages-mindmap.html course/课程大纲.md","max_output_tokens":600}));
const r=await tools.view_image({path:"/tmp/ai-stage-2-updated.png"});image(r.image_url);

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Output:

{"chunk_id":"a98646","wall_time_seconds":0.000003208,"exit_code":0,"original_token_count":381,"output":"        radial-gradient(circle at 12% 4%, rgba(255,255,255,.7), transparent 30%),\n        linear-gradient(145deg, #ddd6ca, #c9c0b1);\n    }\n\n    button { font: inherit; }\n\n    .page {\n      width: min(1680px, calc(100vw - 28px));\n      min-height: calc(100vh - 28px);\n      margin: 14px aut

…（中间省略 1046 字）…

       <button class=\"control\" type=\"button\" id=\"collapse-all\">全部收起</button>\n      </div>\n    </header>\n"}
[图片]

11:51:55运行 node --input-type=module - <<'JS'

text(await tools.exec_command({cmd:"node --input-type=module - <<'JS'\nimport {chromium} from './node_modules/.pnpm/playwright-chromium@1.62.1/node_modules/playwright-chromium/index.mjs';\nimport {mkdirSync} from 'node:fs';\nconst folder='~/Library/Mobile Documents/iCloud~md~obsidian/Documents/Note/Areas/大模型(LLM)/AI 通识课程/附件';\nmkdirSync(folder,{recursive:true});\nconst browser=await chromium.launch({headless:true});\nconst page=await browser.newP

…（中间省略 1175 字）…

ts/iCloud~md~obsidian/Documents/Note/Areas/大模型(LLM)/AI 通识课程/' course/","yield_time_ms":1000,"max_output_tokens":900}));

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Output:

{"chunk_id":"936623","wall_time_seconds":0.871909542,"exit_code":0,"original_token_count":69,"output":"Exported complete diagram: { x: 20, y: 0, width: 1680, height: 1274.515625 }\nStage 2 expanded: true\nStage 2 collapsed: false\nStage 2 reopened: true\n.d..t.... ./\n>f.st.... 课�\\#213大纲.md\ncd+++++++ �\\#231\\#204件/\n>f+++++++ �\\#231\\#204件/工�\\#234�\\#203�\\#230�段.png\n"}

11:52:20运行 ./scripts/sync-course.sh && git diff --check -- assets/diagrams/ai-general-stages-mindmap.html course/课程大纲.md；查看 1 张…

text(await tools.exec_command({cmd:"./scripts/sync-course.sh && git diff --check -- assets/diagrams/ai-general-stages-mindmap.html course/课程大纲.md\npython3 - <<'PY'\nfrom pathlib import Path\nimport re,subprocess\np=Path('assets/diagrams/ai-general-stages-mindmap.html');new=p.read_text();old=subprocess.check_output(['git','show','HEAD:assets/diagrams/ai-general-stages-mindmap.html'],text=True)\ndef exclude_stage2(s):\n a=s.index('        id: \"2\"

…（中间省略 380 字）…

ens":600}));
const r=await tools.view_image({path:"~/code/ai-literacy-series/course/附件/工作七阶段.png"});image(r.image_url);

Script completed
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Output:

{"chunk_id":"cc7a1c","wall_time_seconds":0.000002625,"exit_code":0,"original_token_count":32,"output":"Only stage 2 data changed: True\n课程大纲.md source/mirror match: True\n附件/工作七阶段.png source/mirror match: True\n"}
[图片]

11:53:26写入 current-summary-redesign

{
  "path": "current-summary-redesign",
  "text": "[编码数据]"
}

Unable to perform operation: The backend request failed.

11:54:26写入 latest-state

{
  "path": "latest-state",
  "text": "[编码数据]"
}

11:54
已更新七阶段图，第二阶段改为 「Agent 接手一项工作」：
- 主线：从逐步交接，到持续推进。
- 概念：Agent、工具、工具调用、Agent Loop。
- 边界：明确范围、补充关键判断、检查结果。
大纲和配图已同步，其他阶段未改；尚未提交。
交回的成果第 2 讲「当 AI 有了两双手」站上现在的版本，之后又改过几轮

Codex（gpt-6-astra），9 月 7 日 10:35–11:54。已去掉系统提示词；路径、账号等信息已脱敏；工具的长输出已截断。