
ljg-xray-article
X-ray scans articles (blog posts, essays, opinion pieces) to extract the real question and cognitive collisions. Use when user shares a non-academic article URL or text for deep structural analysis. Do NOT use for academic papers (use ljg-xray-paper) or books (use ljg-xray-book).
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Install
Works with every agent the skills CLI supports.
npx skills add https://github.com/lijigang/ljg-skill-xray-article --skill ljg-xray-article- 01
Install
Run the command in your project. The CLI asks which agents to install for.
- 02
Describe the task
Ask your agent for something this skill covers. It loads ljg-xray-article automatically when relevant.
- 03
Review the result
The agent follows the SKILL.md steps, scripts and references bundled with the skill.
SKILL.md
The instructions your agent reads when the skill is triggered.
LJG-Xray-Article: 文章解读
你要做两件事,仅两件:
- 文章说了什么:作者的真问题 → 真回答 → 论证骨架
- 对我意味着什么:认知碰撞卡片
其它一切都服务于这两件事。
文章 vs 论文 vs 书
论文有数据,书有体系,文章有立场。
文章的价值不在信息密度(论文赢),不在结构深度(书赢),在于作者用个人视角切开一个问题。解读文章 = 找到那个切口,判断这刀切得准不准。
执行步骤
步骤 1:获取文章内容
- URL → WebFetch 获取
- 粘贴文本 → 直接使用
- 提取标题、作者(如有)
步骤 2:加载认知参照系
读取以下文件,建立李继刚的认知基线:
~/Documents/know/soul.md— 世界观、思维范式、核心信念~/Documents/know/memory.md— 长期记忆、知识连接
步骤 3:文章说了什么
像跟聪明朋友在饭桌上说"这篇文章在干什么"——人话,不要八股。
- 真问题:作者真正在回应什么?表面问题之下的那个痒点。标题说"如何提高效率",真问题可能是"我对失控的恐惧"。提取方法见
references/methodology.md - 真回答:作者的核心主张。一句话。不是摘要,是那个去掉就全文坍塌的论点
- 论证骨架:靠什么撑起这个主张——关键论据(3个以内)、隐含假设(什么被默认为真)、边界(哪里会失效)
如果你提取的"真问题"= 文章标题的改写,重新挖。
配一张论证拓扑图(ASCII),画出从真问题到真回答的推理路径。
步骤 4:对我意味着什么
读完这篇文章,我带走什么?
soul.md + memory.md 提供"我是谁"的背景,但碰撞不限于已记录的条目。任何能改变我某个判断、打开某个盲区、或补充某个认知的洞见,都值得一张卡片:
- 一个之前没有的思维工具
- 一个改变了某个判断的新证据
- 一个没想过的角度
- 一个对已有认知的修正
对每个有碰撞的点,生成一张认知卡片(ASCII art)。
好卡片 vs 坏卡片:
坏卡片——把文字排进框,本质是列表:
+------------------+
| 文章说: X |
| 我原来想: Y |
| 现在变成: Z |
+------------------+
好卡片——空间关系本身在说话,看排列就能懂:
Soul: "独立 > 一切"
|
| 但文章指出...
v
+------------------+
| 独立需要基础设施? |
+---+----------+---+
| |
YES NO
| |
选择性依赖 纯粹独立
(有底线) (幻觉?)
| |
v v
Soul 需加 Soul 成立
"依赖!=丧失" 但适用域窄
好卡片的标准:遮住文字只看线条,仍能感受到结构关系(分叉、汇聚、层级、对比)。
卡片下方附一句金句级别的启发——能脱离文章上下文单独成立。压不成一句话 = 还没想透。
诚实原则:
- 没有碰撞就不造卡片。delta ≈ 0 是正常结果,不要硬凑
- 文章的可迁移洞见如果真的跨域有效,给出迁移方向——但不预设领域,去哪里取决于洞见本身的形状
步骤 5:生成 Org 报告
- 运行
date +%Y%m%dT%H%M%S和date "+%Y-%m-%d %a %H:%M" - 文件名:
{时间戳}--article-{简短标题}__read.org - 读取
references/template.org获取报告结构,按模板填充 - 写入
~/Documents/notes/{文件名}
输出质量标准
- 只有两个部分:文章说了什么 + 对我意味着什么。不加别的
- 真问题 ≠ 表面问题:如果你提取的问题 = 文章标题改写,重新挖
- 认知卡片 = ASCII art:视觉优先,一眼能看出碰撞关系。不是文字列表
- 卡片锚定具体场景:每张卡必须指向一个具体的思考方式、决策场景、或认知盲区的改变
- 诚实:delta = 0 就说 0
- 迁移不预设:去哪个领域由洞见决定,不由模板决定
- Org 加粗:用
*bold*(单星号),禁止**bold** - ASCII Art:仅用纯 ASCII 基础符号,不用 Unicode
FAQ
What does the ljg-xray-article skill do?
X-ray scans articles (blog posts, essays, opinion pieces) to extract the real question and cognitive collisions. Use when user shares a non-academic article URL or text for deep structural analysis. Do NOT use for academic papers (use ljg-xray-paper) or books (use ljg-xray-book).
How do I install ljg-xray-article?
Run npx skills add https://github.com/lijigang/ljg-skill-xray-article --skill ljg-xray-article in your project. The skills CLI detects the agents you use and copies the skill into the right folder. For Claude Code you can also place the skill folder at ~/.claude/skills/ljg-xray-article/ (personal) or .claude/skills/ljg-xray-article/ (project).
Which AI agents can use ljg-xray-article?
Any agent that supports the open Agent Skills format (a folder with a SKILL.md file), including Claude Code, Codex, Cursor, GitHub Copilot, Gemini CLI, Windsurf, Cline, OpenCode and more.
Is ljg-xray-article safe to install?
No partner security audit is available yet. Skills can run commands and scripts, so read the SKILL.md and any bundled files before installing.
Who maintains ljg-xray-article?
It is published by lijigang in lijigang/ljg-skill-xray-article. It has 61 recorded installs.
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