為非學術人士設計的論文閱讀器。將論文轉化為一個連貫的故事——論文核心命題的生命歷程，以七拍敘事結構（主角/困境/舊路/轉折/解法/結局/內核）講述：誕生於基準規則的困境，結晶為大膽假設，通過機制與證據論證，提煉為全新視角，最終走出論文——經過現實檢驗並轉化為可證偽的預測。輸出以可掃讀的速讀卡（一句話/大想法/只記三件事）開頭，從三個維度壓縮整個故事，滿足時間有限的讀者和六個月後的自己，然後展開完整敘述。任務是講故事讓論文落地，而非學術評論。
這項技能專為將學術論文轉化為易於理解的敘事而設計，非常適合開發者、工程師或任何希望快速掌握論文精髓而不陷入專業術語的用戶。它採用獨特的七拍敘事結構——主角、困境、舊路、轉折、解法、結局、內核——將論文的核心理念作為一個有生命的故事來講述。輸出格式包含一個可掃讀的速讀卡，以一句話總結、大想法和只記三件事三個維度壓縮信息，滿足時間有限的閱讀者和未來回顧的需求。此技能廣泛支持arxiv鏈接、論文URL、PDF文件，並可通過'讀論文'、'講論文'或'share a paper'等觸發詞啟動。其背後的理念是：讓論文真正落地，而非進行學術批判，從而幫助非專業人士也能從中獲得洞見。
npx skills add https://github.com/lijigang/ljg-skills/tree/main/skills/ljg-paperInstalled? Explore more 研究與資料分析 skills: affaan-m/uspto-database, affaan-m/scholar-evaluation, affaan-m/literature-review · View all 6 →
專為非學術人士設計的論文閱讀器。它讀取一篇論文，並將其以一個連貫的故事形式回饋給你——論文的核心理念（命題）的生命歷程，以七拍敘事結構（主角/困境/舊路/轉折/解法/結局/內核）講述：誕生於基準規則的困境，結晶為大膽假設，透過機制與證據進行論證，最後提煉為全新的視角；接著走出論文之外——經過現實檢驗並轉化為可證偽的預測（檢驗）。輸出以可快速掃讀的速讀卡（一句話 / 大想法 / 只記三件事）開場，從三個維度壓縮整個故事，滿足時間有限的讀者以及六個月後的自己，然後再展開完整的故事。這項任務的核心是講故事，讓論文真正落地，而非進行學術批判。當用戶分享 arxiv 鏈結、論文網址、PDF，或要求分析某篇研究論文時使用。觸發詞：「讀論文」、「講論文」、「把這篇講給我聽」、「分析論文」、「paper」，或當用戶分享學術論文時。
This repo contains 19 individual skills — each has its own dedicated page.
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.
投资分析, 生成一份深度投资分析报告。不做传统投资分析——核心判断是项目是否是一台「秩序创造机器」。Use when user says '投资报告', '投资分析', '分析这个项目', '写投资报告', 'investment report', 'invest analysis', or provides entrepreneur conversation records wanting investment evaluation. Also trigger when user pastes or references meeting notes, pitch decks, or founder interviews and asks for analysis.
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.
Paper workflow: read papers + cast 取景框 library cards in one go. Takes one or more arxiv links, paper URLs, PDFs, or paper names. For each paper, runs ljg-paper (generates org analysis) then ljg-library (distills the paper's 取景框 into a 2050 library card PNG). Use when user says '论文流', 'paper flow', '读论文并做卡片', '论文卡片', or provides multiple papers wanting both analysis and cards.
论文倒读法：给一篇论文，递归找出它批判和改进的前序论文（最多5层），再找它之后的最新进展，从源头正向讲述问题演化史。以问题为轴，费曼式讲解每篇论文看到的问题和解法创新。Use when user shares a paper and wants to understand its intellectual lineage, citation chain, problem evolution, or says '倒读', '论文溯源', '论文脉络', 'paper river', 'paper connects', 'trace back', '这篇论文的来龙去脉', '论文演化'. Also trigger when user wants to understand how a research problem evolved across multiple papers.
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'.
演讲铸造器（Outline-Faithful）。基于 orgmode/markdown outline 层级 1:1 视觉化呈现——色块大字、ultra-bold 错位，原文不动只做美化。三档主题色 black/red/yellow（默认 black 或按 filetags 推断），可用 -r/-b/-y 显式覆盖；可用 --cyber 走黑底绿字 cyber-hacker 风。使用时用户会说：'讲这个'、'present'、'做成演讲'、'呈现一下'、'铸成演示'、'做个 slides'、'标语流'、'宣言体'、'slogan'、'manifesto'、'按 outline 美化'。输出单文件 HTML 到 ~/Downloads/。
把 ~/.claude/skills/ljg-* 里所有更新过的 skills 同步到 github repo (ljg-skills)，先推 master 分支（org-mode 输出风格），再切 md 分支（markdown 输出风格）做基础 markdown 化后推。Use when user says '/ljg-push', 'push skills', '推送 skills', '同步 skills', 'sync ljg', or whenever ljg-* skills get updated and need shipping. NOT FOR pushing non-ljg skills or arbitrary git repos.
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.
给一个领域，找出背后真正撑着它的几根独立的力。十几个现象砍到不可再少的生成器——砍完能把现象一个个生回来，才算数。Use when user says '降秩', '找秩', '秩是什么', '这个领域靠什么撑着', '背后是什么', or wants to decompose any domain to its irreducible generators.
Reading companion agent. Accompanies user through any text (books, articles, essays, papers, news) with translation, structural annotation, deep questioning, and cross-domain insights. Detects language, translates English to Chinese (faithfulness-expressiveness-elegance), guides reader to understand the author and encounter real questions. Use when user says '伴读', '陪我读', '读这篇', 'read with me', 'companion read', or shares a text/URL wanting guided reading.
Relationship analyst combining structural diagnostics (5-layer framework) with psychoanalytic depth (transference, unconscious patterns, resistance). Guides users through dialogue to "see" the real structure of their relationship issues. Use when user says "关系分析", "分析关系", "relationship", "人际关系", or describes a specific relationship problem they want to understand.
Structured roundtable discussion framework with a truth-seeking moderator who invites representative figures for dialectical debate on any topic. Use when user says "圆桌讨论", "圆桌", "roundtable", "辩论", or wants to explore a topic through multi-perspective structured debate.
Skill map viewer. Scans all installed skills and renders a visual overview — name, version, description, category at a glance. Use when user says 'skills', '技能', '技能地图', 'skill map', '我有哪些技能', '看看技能', '列出技能', 'list skills'. Also trigger when user asks what skills are available or installed.
追本之箭——纵向深钻思维工具。给一个观点、现象或问题，像箭一样一路向下钻到不可再分的本质。Use when user says '想透', '追本', '本质是什么', '为什么会这样', '深挖', '钻到底', 'think deep', 'drill down', or wants to trace any idea/phenomenon vertically to its irreducible root. Also trigger when user provides a statement and wants depth analysis, not breadth survey.
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.
Deep-dive English word mastery tool. Deconstructs a single English word into core semantics and epiphany. Use when user asks to explain/master a specific English word.
Word flow: deep-dive word analysis + infograph card in one go. Takes one or more English words, runs ljg-word (generates deep semantics analysis) then ljg-card -i (generates infograph PNG). Use when user says '词卡', 'word card', 'word flow', or provides English words wanting both analysis and visual card.
写作引擎。像手术刀剖开一个观点，一层层剥到底。1000-1500 字。
USPTO patent and trademark data workflow for official record lookup, PatentSearch queries, TSDR checks, assignment data, and reproducible IP research logs.
Structured scholarly-work evaluation for papers, proposals, literature reviews, methods sections, evidence quality, citation support, and research-writing feedback.
Systematic literature-review workflow for academic, biomedical, technical, and scientific topics, including search planning, source screening, synthesis, citation checks, and evidence logging.
The agent harness performance optimization system. Skills, instincts, memory, security, and research-first development for Claude Code, Codex, Opencode, Cursor and beyond.
Agent skill repository discovered by 10x-chat research.
Review backend code for quality, security, maintainability, and best practices based on established checklist rules. Use when the user requests a review, analysis, or improvement of backend files (e.g., `.py`) under the `api/` directory. Do NOT use for frontend files (e.g., `.tsx`, `.ts`, `.js`). Supports pending-change review, code snippets review, and file-focused review.