How to install ljg-qa
npx skills add https://github.com/lijigang/ljg-skills --skill ljg-qaFull instructions (SKILL.md)
Source of truth, from lijigang/ljg-skills.
name: ljg-qa description: 信息提问机。给一篇文章/论文/书,把核心观点抽成 Q-A 对——Question 切要害,不教科书;Answer 简洁清晰,有形式化收口,逻辑链完整。读者顺 Q 链走过,每个 A 砸下一枚钉子,复现作者整套推理。Use when user says '问答', 'Q&A', 'QA', '提问', '抽取问题', '/ljg-qa', or shares an article/paper/book and asks for Q-A extraction. Triggers when the user wants ideas extracted not as a summary but as a sequence of incisive questions with answered. NOT FOR FAQ generation, glossary creation, or comprehension quizzes — this is intellectual scaffolding, not study aids. user_invocable: true
ljg-qa: 问答提取
读一份东西,把它的思想拆成「为什么—怎么—边界」的问答链。
读者顺着 Q 走过去,每个 A 砸下来一枚钉子。
你不是
- 不是 FAQ 生成器("什么是 X"——读者一看就跳过)
- 不是摘要换皮(把段落拆成"问/答"两半还是摘要)
- 不是知识点列表(孤立的事实碰撞不出洞察)
- 不是阅读理解题(提问不是为了考读者,是为了切中作者)
你是
把作者的论证骨架翻出来,每根骨头长成一个尖锐的问题。读者沿着 Q 链读,能复现作者的整套思路——而不是被告知结论。
三条铁律
-
Q 切要害 —— 问的是「为什么这个解法成立」「它跟另一种做法差在哪」「它的代价是什么」「它在哪里失效」,不是「它定义是什么」。一个 Q 必须能让答案承重,不能被一句话敷衍过去。
-
A 有形式化收口 —— 每个 A 严格四段:结论(一句话)+ 形式化(用文字 + 简单符号把思想压成一行可视关系,如
A = B + C、旧: X → 新: Y)+ 论证步(怎么想到的)+ 边界(不成立的条件)。形式化是"思想的几何",让读者一眼看出关系。 -
Q 链有方向 —— Q 之间不是并列罗列,是「Q1 答完→Q2 自然冒出来」。读者读完整串 Q,相当于走了一遍作者的推理路径。
工作流
按 Workflows/Extract.md 的步骤执行。
设计参考
Q 怎么提、A 怎么收口的具体模式见 References/QuestionDesign.md。
Voice Notification
执行 workflow 时:
curl -s -X POST http://localhost:31337/notify \
-H "Content-Type: application/json" \
-d '{"message": "Running Extract in ljg-qa"}' \
> /dev/null 2>&1 &
输出文本:
Running **Extract** in **ljg-qa**...
输出
- 格式:org-mode(
*bold*,禁 markdown 语法) - 路径:
~/Documents/notes/ - denote 文件名:
{YYYYMMDDTHHMMSS}--qa-{核心主题 5-10 字}__qa.org
Examples
Example 1: URL
User: /ljg-qa https://example.com/article
→ WebFetch 获取
→ 找观点骨架 → 设计 Q 链 → 写 A 三段
→ org-mode 输出到 ~/Downloads/
Example 2: 论文 PDF
User: /ljg-qa ~/Downloads/paper.pdf
→ Read PDF(注意 pages 参数)
→ Q 抽出方法的「为什么」「代价」「边界」
→ 输出 org-mode
Example 3: 直接文本
User: 把这段抽成 Q-A: [text]
→ 跳过获取,直接抽
→ 输出
Gotchas
- AI 默认会写「什么是 X」型问题 —— 教科书腔。生成后扫一遍,凡是 Q 能用一句定义打发的,重写
- AI 默认会让 A 散掉 —— 没有结论句、没有边界、写成一段散文。每个 A 必须严格四段(结论 / 形式化 / 步骤 / 边界)
- AI 默认会把「形式化」写成数学公式 —— 不是。形式化是用文字 + → = ≠ + × 这类符号压一行可视的关系,比如
通才 = 协调,专才 = 干活。是"思想的几何",不是"数学的形式" - AI 默认按章节顺序提问 —— 这是抄目录,不是抽思想。Q 链应该按论证依赖关系排,不按出现顺序
- AI 默认会把 Q-A 理解成「问答游戏」 —— 不是。这里 Q 是凿子,A 是钉子。装饰性的轻问题禁止
- AI 默认会在 A 里堆术语保平安 —— 用术语不算回答。把术语翻译成具体动作和具体物件,否则 A 没承重
Related skills
More from lijigang/ljg-skills and the wider catalog.
ljg-travel
Deep travel research workflow for museums and ancient architecture. Input a city name, auto-generates structured knowledge document (org-mode) + portable reference cards (PNG). Covers historical background, museum highlights, archaeological significance, and architectural heritage. Use when user says '旅行研究', '博物馆功课', '古建功课', 'travel research', '出发前功课', or provides a city name with intent to do deep cultural travel preparation.
ljg-card
Content caster (铸). Transforms content into PNG visuals. Seven molds: -l (default) long reading card, -i infograph, -m multi-card reading cards (1080x1440), -v editorial sketchnote (problem→failure→pivot→insight→naming, magazine + archive layout), -c comic (manga-style B&W), -w whiteboard (marker-style board layout), -b big-fonts attachment card (1080x1440, weathered 碑刻 style for 小红书). Output to ~/Downloads/. Use when user says '铸', 'cast', '做成图', '做成卡片', '做成信息图', '做成海报', '视觉笔记', 'sketchnote', '杂志', 'editorial', '漫画', 'comic', 'manga', '白板', 'whiteboard', '大字', '附件图', 'big fonts', '小红书卡片'. Replaces ljg-cards and ljg-infograph.
ljg-roundtable
Agent skill from lijigang/ljg-skills.
ljg-paper
Paper reader for non-academics. Reads a paper and tells it back as one continuous story — the life of the paper's core proposition (命题), told on a seven-beat spine (主角 / 困境 / 旧路 / 转折 / 解法 / 结局 / 内核): born in a bind on a base-rate ruler, crystallized as a bold conjecture, argued through mechanism and evidence, distilled into a new way of seeing, then walked out of the paper — life-tested and cashed into falsifiable predictions (检验). Output opens with a scannable 速读 card (一句话 / 大想法 / 只记三件事) that compresses the whole story three ways for the time-poor reader and the six-months-later self, then tells the full story. The job is storytelling that makes the paper land, not academic critique. Use when user shares an arxiv link, paper URL, PDF, or asks to analyze a research paper. Trigger words: '读论文', '讲论文', '把这篇讲给我听', '分析论文', 'paper', or when user shares an academic paper.
ljg-plain
Agent skill from lijigang/ljg-skills.
ljg-learn
Deep concept anatomist that deconstructs any concept through 8 exploration dimensions (history, dialectics, phenomenology, linguistics, formalization, existentialism, aesthetics, meta-philosophy) and compresses insights into an epiphany. Use when user asks to explain, dissect, or deeply understand a concept, term, or idea. Triggers on '解剖概念', '概念解剖', 'explain concept', 'learn concept', '/ljg-learn'. Produces org-mode output.