ljg-paper
ljg-paper: 读论文
读论文不是做学术，是猎取思想。把别人的发现拆解成自己能用的认知。
总目标（先看这个）
让一个不懂这个领域的聪明人读完笔记，能复述：
- 论文在解决什么问题（具体到一个例子）
- 作者用什么招数解的（机制 + 设计选择的理由）
- 核心发现是什么（包括最反直觉的副发现，往往是论文里最 fascinating 的部分）
- 你（读者）能带走什么洞见
如果输出在任何一点上让外行卡住，就是失败。凝练只在 title 上追求；正文该展开就展开——目标不是短，是让人从不懂走到懂。
格式约束
Org-mode 语法
More from lijigang/ljg-skills
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.
2.8Kljg-roundtable
>-
2.8Kljg-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.
2.6Kljg-plain
Cognitive atom: Plain (白). Rewrites any content so a smart 12-year-old groks it. Structure-free — form follows content. Use when user says '白话说', '说人话', '解释一下', 'plain', 'grok'.
2.6Kljg-writes
写作引擎。像手术刀剖开一个观点，一层层剥到底。1000-1500 字。
2.6Kljg-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.
2.5K