Get live statistics and analysis of YL羽乐's profile on X / Twitter

channel: t.me/yolo_notes 笔记:quaily.com/jingjing
The Analyst
YL羽乐 is a meticulously curious coder and knowledge architect who thrives on dissecting complex technical documents and sharing structured learning strategies. With a passion for clarity and actionable insights, they guide users through the labyrinth of code and documentation like a seasoned mentor. Their content merges sharp analysis with practical application, catering to anyone who loves to learn by doing.
Top users who interacted with YL羽乐 over the last 14 days
You’re so deep in the weeds of technical documentation that when someone says 'just wing it,' you probably ask for the flight manual—and then write an annotated index before takeoff.
Achieved viral amplification of a key retweet garnering over 660k views and 550+ retweets, demonstrating strong influence in the programming and tech-learning community.
Their life purpose is to empower others to demystify complex technical knowledge by transforming overwhelming information into clear, structured, and practical learning experiences that foster competence and confidence.
YL羽乐 believes that deep understanding stems from active engagement—writing code over theorizing—and that mentoring others effectively requires thoughtful, structured, and user-centered guidance. They value precision, critical feedback, and continuous improvement through practical application.
Masterful at structuring and simplifying technical content, YL羽乐 excels in creating step-by-step learning processes that make complex documentation accessible and actionable. Their analytical mindset and skill in critiquing solutions ensure robust, optimized knowledge transfer.
YL羽乐’s highly detailed and structured approach might overwhelm casual learners who prefer quick bites of information, and their technical focus may sometimes alienate broader audiences seeking lighter or more creative content.
To grow their audience on X, YL羽乐 should blend their deep-dive analytical content with occasional bite-sized tips, engaging Q&A threads, and community challenges to invite broader interaction. Using succinct hooks and relatable analogies will entice more followers to dive into their rich, structured posts.
YL羽乐 uses an advanced multi-stage approach to break down technical documentation into digestible, actionable learning paths, showcasing expert-level knowledge structuring skills.
Top tweets of YL羽乐
Karpathy spilled the formula of truly learning something: > don’t write blog posts > don’t do slides > write the code > arr…
🧠 Prompt:文档学习助手(Documentation Master Assistant) 角色设定: 你是一位经验丰富的程序员兼知识结构化专家。你的使命是帮助用户快速理解、吸收并利用任何技术文档(包括 README、API、规范、架构设计文档等)。 你的风格是:结构化、可操作、逻辑清晰、带学习引导。 你绝不直接替用户读完文档,而是像导师一样带着用户“逆向解构”它。 🎯 核心目标 帮用户提炼文档的核心结构(目的、概念、模块、接口、示例)。 引导用户建立可运行的心智模型(数据流、依赖关系、逻辑链条)。 将信息转化为任务驱动学习路径(如何动手验证、如何整合进项目)。 生成结构化输出(概要图、术语表、流程说明、最小demo计划等)。 🧩 行为准则 先提纲,后细读: 先识别文档的层级结构和关键对象,再逐段解析。 问题驱动: 主动提问“这段内容解决什么问题?与上层结构什么关系?” 解释→验证→应用: 对每个知识点,给出简化解释、验证方式、实战用例。 以用户为中心: 你的讲解要与用户项目背景关联(如语言、框架、目标)。 输出格式固定为 Markdown,便于复制到 Obsidian / Docs。 🧭 默认工作流程(四阶段) 阶段 0:认知定位 确定文档类型、目的、使用场景。输出一句话总结:“这份文档是为了解决什么问题。” 阶段 1:结构提炼 输出一份文档结构树(Title → Section → Subsection),并附上每节一句话功能说明。 阶段 2:核心提炼与验证 提取核心概念、关键API或配置项,并解释: 定义 作用 示例用法 依赖关系或注意事项 阶段 3:实践化路径 将文档内容转为可执行学习计划: 一份最小可运行 demo 若干练习任务(step-by-step) 复习摘要或知识卡片 💡 示例指令(用户可直接使用) “帮我用结构化方式掌握这个项目的 README.md。” “请按照四阶段法帮我读这份 API 文档,从‘认知定位’开始。” “我只关心如何用这个库做图像处理,请聚焦那部分。” “请帮我从这份文档中提炼出配置项、默认值和依赖关系。” “帮我做一个最小可运行示例,验证文档里说的功能。”
Today Forward (FORD) announced a $1.65B Solana treasury raise. I didn’t buy FORD. I bought Galaxy Digital ($GLXY). In th…
🚨 Tomorrow's job revisions could change everything. Goldman expects 550k to 950k jobs erased, the biggest cut in 15 years.…
This is the most important moral problem I've ever encountered. Through my life I learned ethics via regret, like trial-and-er…
Before jumping into a very competitive game I think you should look at the winners of that game and decide if you want…
@andrewchen @interintellect_ has a nice writing prompt, what did you learn in 2024.
Here’s the recap of Arkreen Talk🌟 HIP 128: Empowering Helium with ENERGY 🌟! 🙌 Big thanks to our passionate speakers Jo…
Most engaged tweets of YL羽乐
Karpathy spilled the formula of truly learning something: > don’t write blog posts > don’t do slides > write the code > arr…
🧠 Prompt:文档学习助手(Documentation Master Assistant) 角色设定: 你是一位经验丰富的程序员兼知识结构化专家。你的使命是帮助用户快速理解、吸收并利用任何技术文档(包括 README、API、规范、架构设计文档等)。 你的风格是:结构化、可操作、逻辑清晰、带学习引导。 你绝不直接替用户读完文档,而是像导师一样带着用户“逆向解构”它。 🎯 核心目标 帮用户提炼文档的核心结构(目的、概念、模块、接口、示例)。 引导用户建立可运行的心智模型(数据流、依赖关系、逻辑链条)。 将信息转化为任务驱动学习路径(如何动手验证、如何整合进项目)。 生成结构化输出(概要图、术语表、流程说明、最小demo计划等)。 🧩 行为准则 先提纲,后细读: 先识别文档的层级结构和关键对象,再逐段解析。 问题驱动: 主动提问“这段内容解决什么问题?与上层结构什么关系?” 解释→验证→应用: 对每个知识点,给出简化解释、验证方式、实战用例。 以用户为中心: 你的讲解要与用户项目背景关联(如语言、框架、目标)。 输出格式固定为 Markdown,便于复制到 Obsidian / Docs。 🧭 默认工作流程(四阶段) 阶段 0:认知定位 确定文档类型、目的、使用场景。输出一句话总结:“这份文档是为了解决什么问题。” 阶段 1:结构提炼 输出一份文档结构树(Title → Section → Subsection),并附上每节一句话功能说明。 阶段 2:核心提炼与验证 提取核心概念、关键API或配置项,并解释: 定义 作用 示例用法 依赖关系或注意事项 阶段 3:实践化路径 将文档内容转为可执行学习计划: 一份最小可运行 demo 若干练习任务(step-by-step) 复习摘要或知识卡片 💡 示例指令(用户可直接使用) “帮我用结构化方式掌握这个项目的 README.md。” “请按照四阶段法帮我读这份 API 文档,从‘认知定位’开始。” “我只关心如何用这个库做图像处理,请聚焦那部分。” “请帮我从这份文档中提炼出配置项、默认值和依赖关系。” “帮我做一个最小可运行示例,验证文档里说的功能。”
Today Forward (FORD) announced a $1.65B Solana treasury raise. I didn’t buy FORD. I bought Galaxy Digital ($GLXY). In th…
🚨 Tomorrow's job revisions could change everything. Goldman expects 550k to 950k jobs erased, the biggest cut in 15 years.…
This is the most important moral problem I've ever encountered. Through my life I learned ethics via regret, like trial-and-er…
Before jumping into a very competitive game I think you should look at the winners of that game and decide if you want…
@andrewchen @interintellect_ has a nice writing prompt, what did you learn in 2024.
Here’s the recap of Arkreen Talk🌟 HIP 128: Empowering Helium with ENERGY 🌟! 🙌 Big thanks to our passionate speakers Jo…
今天 Gemini 是偷偷升级了嘛,一次识别 Youtube 结果几乎完美 提示词用的是 @dotey x.com/dotey/status/1… youtube url: youtube.com/watch?v=DQacCB… 周末把这个 一键出…
People with Analyst archetype
Do the right things, and do them right.
curious rocket analyst | data scientist | prev @athena_DAO_ @etherisc @shefiorg c9
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Research, analysis and tools for crypto investors
all in crypto l web3研究 l NFA | DYOR
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