How to install ljg-skill-map
npx skills add https://github.com/lijigang/ljg-skills --skill ljg-skill-mapFull instructions (SKILL.md)
Source of truth, from lijigang/ljg-skills.
name: ljg-skill-map description: "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." user_invocable: true version: "1.0.0"
ljg-skill-map: 技能地图
扫描 ~/.claude/skills/ 下所有已安装技能，生成一目了然的可视化地图。
执行
1. 扫描
运行 scripts/scan.sh，获取所有技能的 JSON 数据（name, version, invocable, desc）。
2. 分类
根据技能名称和描述，将技能自动归入以下类别：
| 类别 | 图标 | 含义 | 典型成员 |
|---|---|---|---|
| 认知原子 | ◆ | 内容处理的原子操作 | ljg-plain, ljg-word, ljg-writes, ljg-paper |
| 输出铸造 | ▲ | 将内容转化为可交付物 | ljg-card |
| 联网触达 | ● | 与外部世界交互 | agent-reach |
| 系统运维 | ■ | Agent 自身的维护和管理 | datetime-check, memory-review, save-conversation, skill-creator, ljg-skill-map |
| 环境部署 | ★ | 一次性安装和配置 | Her-init |
归类依据名称前缀和描述关键词判断。遇到新技能无法归类时，放入「未分类」。
3. 渲染
用 ASCII 方框图呈现，格式如下：
╔══════════════════════════════════════════════════════════╗
║ SKILL MAP · {N} skills installed ║
╠══════════════════════════════════════════════════════════╣
║ ║
║ ◆ 认知原子 ║
║ +-----------------+----------------------------------+ ║
║ | ljg-plain v4.0 | 白 — 好问题+类比让人 grok | ║
║ | ljg-word v1.0 | 英文单词深度拆解 | ║
║ | ljg-writes v4.0 | 写作引擎 | ║
║ | ljg-paper v2.0 | 论文阅读与分析 | ║
║ +-----------------+----------------------------------+ ║
║ ║
║ ▲ 输出铸造 ║
║ +-----------------+----------------------------------+ ║
║ | ljg-card v1.5 | 铸 — 内容转 PNG 可视化 | ║
║ +-----------------+----------------------------------+ ║
║ ║
║ ... ║
╚══════════════════════════════════════════════════════════╝
规则：
- 每个类别一个区块，类别图标 + 中文名做标题
- 技能名左对齐，版本号紧跟（无版本显示
-） - 描述截断到一行，保留核心语义
- user_invocable 为 true 的技能名后加
/标记（表示可直接/技能名调用） - 底部统计行：总数、可调用数、分类数
4. 输出
直接在对话中渲染 ASCII 地图。不生成文件，不写入磁盘。
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.