The user wants me to rewrite a Hac

1. Title: Must be 14-50 chars, follow the formula for a share/experience post. It's a resource sharing post, so I should use something like "分享一个/我的+描述" style, short and direct.

2. No template structure - no "抛痛点→夸它多厉害→最让我心动→值得关注" flow. I need to be creative with the structure.

3. No "AI" or "大模型" as tags - specific entities only.

4. No markdown tables - use bold lists instead.

5. No generic opening like "最近..." "上周..." etc.

6. 400-600 words minimum.

7. Tags at the end: TAGS: specific entities mentioned.

8. No source attribution at the end.

9. URLs should be in code blocks if preserved, and no bare domain links. But looking at the original content, it's a list of resources with URLs. The rule says "严禁出现无意义的外部网址" and "只有确实有价值、带完整具体路径的来源页面才可保留". These are all specific resource pages with full paths, so they can stay. But they must be in code blocks, not clickable links.

Wait, looking more carefully: "只有本站 promptcube3.com 的链接才可以做成可点击链接" - only links to promptcube3.com can be clickable. All others should be in code blocks as plain text.

Let me also check the "外部链接硬性规则" more carefully: "正文里不要出现无意义的外部网址". These URLs are the actual resources being recommended, so they have value. I should put them in code blocks.

Let me craft the title. It's a resource sharing post about visual explainers and interactive learning tools from HN.

Title ideas:

• "我的 S-Tier HN 可视化学习资源合集" (too generic?)
• "收藏了十年的 HN 可视化资源，我选出了这些 S 级" (28 chars)
• "从 50000+ 书签里筛出的 S 级可视化学习资源" (22 chars)

Let me go with something more creative and direct:
"从 50000+ 书签里筛出的 S 级可视化学习资源" - 25 chars, good.

Actually, let me reconsider the title formula for 分享/经验帖: "分享一个/我的+描述". So:
"分享我收藏十年的 S 级可视化学习资源清单" - 20 chars

Let me write the content now. I need to:

• Open with a unique hook (not time-based)
• Structure freely
• Include the resource list with URLs in code blocks
• Be 400-600+ words
• Add tags at the end

Let me write it naturally, like a real forum user sharing their bookmark collection.

I need to be careful about:

• Not using "AI" as a tag (use specific entities like Transformer, K-means, etc.)
• Not using "大模型" as a tag
• No markdown tables
• URLs in code blocks
• No "---" source attribution at the end
• No "欢迎讨论" type ending

Let me draft:

---

Title: 分享我收藏十年的 S 级可视化学习资源清单

Opening: I'll start with a direct opinion or a specific observation. Something like "可视化 explainer 是互联网上被低估的学习方式" or start with the bookmark count.

Let me write the body in a natural, flowing way. I'll organize the resources by category since that makes it more useful than a flat list.

Wait, the original post mentions they rank things - S-Tier is the visual explainers. Let me capture that spirit but write it fresh.

Let me count words carefully to hit 400+ minimum.

Let me draft:

---

收藏了十年 HN 书签，50000+ 条里真正值得反复打开的，我给它们打了 S 级——全部是可交互或动画式的可视化资源。

我的筛选逻辑很简单：如果一个页面能让你停下来、拖一拖鼠标、看一段动画就理解了一个原本枯燥的概念，它就配 S 级。博客长文和观点类内容被压到最底下，C 到 F 都有可能。来源靠谱程度也会影响评级，A 给知名机构，B 给个人创作者但内容扎实。

按主题分几档，每档挑一个代表作：

数学与统计

• Animated intro to probability https:`//seeing-theory.brown.edu/basic-probability/index.html - Animated math book for linear algebra https://immersivemath.com/ila/index.html - Visual intro to linear & logistic regression, neural networks https://mlu-explain.github.io/ **计算机系统与网络** - How a request travels from browser to server, step by step https://200ms.thenodebook.com/#act-1-the-click - 7-layer networking stack explained inside-out https://fazamhd.com/mental-models/networking/ - How CSS Grid works (mini game) https://cssgridgarden.com/ - How Git works (mini game) https://learngitbranching.js.org/ - SQL from scratch (mini game) https://sqlpd.com/ - Another SQL mini game https://lost-at-sql.therobinlord.com/ **算法与数据结构** - Algorithm visualizer https://algorithm-visualizer.org/ - Visual intro to K-means clustering https://k-means-explorable.vercel.app/ **图形学与渲染** - Visual intro to the graphics pipeline (Vulkan) https://fremaconsulting.ch/blog/vulkan - How colors, screens, shaders, compilers, interpreters work https://www.makingsoftware.com/ **机器学习与模型** - Animated explainer of how transformers work https://poloclub.github.io/transformer-explainer/ - Animated 3D intro to vision transformers https://blog.mdturp.ch/posts/2024-04-05-visual_guide_to_vision_transformer.html - Animated intro to machine learning https://r2d3.us/visual-intro-to-machine-learning-part-1/ - Visual explainer: FAISS vector search https://fremaconsulting.ch/blog/faiss - Assemble a neural network from scratch https://graphgame.sabrina.dev/ **加密与安全** - Elliptic curve cryptography animated explainer https://growingswe.com/blog/elliptic-curve-cryptography - Rate limiting algorithms visualized https://smudge.ai/blog/ratelimit-algorithms **物理与工程** - 3D visualization of how gravity works https://qunabu.github.io/Gravity/ - Visual intro to the inner workings of a combustion engine https://ciechanow.ski/internal-combustion-engine - 3D animation of semiconductor manufacturing https://ig.ft.com/microchips/ - 3D animation of building a health wearable https://www.lumafield.com/scan-of-the-month/health-wearables **编程与软件构建** - Build ReactJS from scratch (animated) https://pomb.us/build-your-own-react/ - Build a 3D world from scratch in Rust (Bevy) https://aibodh.com/posts/bevy-tutorial-build-your-first-3d-editor-in-rust/ - Mini game: build an entire CPU from logic gates https://select.supply/game/chipbuilder - 3D real-time robotics code simulator https://bittlex-sim.petoi.com/ - Animated sequence of how a request goes from browser to server https://200ms.thenodebook.com/#act-1-the-click **3D 与可视化** - 3D explanation of collision detection https://` (原文截断)

---

Hmm, I need to be careful about the last item - the original text was cut off with "3D explanation of collision detect". I should handle this gracefully.

Also, I need to check: I'm using code blocks for URLs but the format should be correct. The rule says "用纯文本代码块(三个反引号)包裹". So I should do:

https://example.com/path

Let me also make sure I don't have "AI" as a tag. Let me think about what tags to use. Looking at the content, specific entities I can tag:

• Transformer (from transformer-explainer)
• K-means
• Vision Transformer (from the vision transformer link)
• ReactJS
• FAISS
• V