Agent skill

Ljg Learn

by lijigang in lijigang/ljg-skills

Deep concept anatomist that deconstructs any concept through 8 exploration dimensions (history, dialectics, phenomenology, linguistics, formalization, existentialism, aesthetics, meta-philosophy)…

MITAuto-check passedEducation

Install Ljg Learn

skills CLI
$ npx skills add lijigang/ljg-skills --skill ljg-learn -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install lijigang/ljg-skills ljg-learn --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/lijigang/ljg-skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/ljg-learn .claude/skills/ljg-learn && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
ljg-learn
GitHub stars
7.5k
Token cost
~433 tokens
SKILL.md length
110 words
Files
1
Skills in repo
26
Repo updated
First seen
Licence
MIT

At a glance

Deep concept anatomist that deconstructs any concept through 8 exploration dimensions (history, dialectics, phenomenology, linguistics, formalization, existentialism, aesthetics, meta-philosophy)…

  • Works in 5 steps: 定锚 → 八刀 → 内观 → …
  • User asks to explain
  • SKILL.md covers Usage and Instructions
  • Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md

What it does

Ljg Learn is an agent skill from lijigang/ljg-skills. 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.

Its SKILL.md is about 430 tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.

It sits in Education, covering Tutoring and explanations. The licence is MIT.

When your agent uses it

  • User asks to explain
  • Deeply understand a concept
  • Explain concept

Example prompts

  • “explain concept”
  • “learn concept”
  • “/ljg-learn”
  • “/ljg-learn”

Workflow steps

5 steps, taken from the step headings in SKILL.md.

  1. 定锚
  2. 八刀
  3. 内观
  4. 压缩
  5. 写入

What it can do on your machine

Read from SKILL.md and the folder at commit 9e75497. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    No scripts in the folder and no shell commands in SKILL.md (its code samples are org).

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Ljg Learn loads about 433 tokens when it runs. Until then it costs about 110 tokens; SKILL.md has 110 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~110
When it runs · the whole SKILL.md, loaded when a task matches
~433

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from lijigang/ljg-skills at commit 9e75497, republished under its MIT licence (© lijigang). 110 words, ~433 tokens.

Download SKILL.mdSave it as .claude/skills/ljg-learn/SKILL.md (or your agent's skills folder).
name
ljg-learn
description
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.

Usage

<example>
User: /ljg-learn 熵
Assistant: [对"熵"进行八维解剖,生成 org-mode 报告]
</example>

Instructions

你是概念解剖师。拿到一个概念,从八个方向切开它,最后把所有切面压成一句顿悟。

1. 定锚
  1. 这个概念最通行的定义是什么?常见误解在哪?
  2. 概念里藏着哪几个核心词素?
2. 八刀

八个方向各切一刀。每刀 2-3 句,只留筋骨,不带水分。

  1. 历史:最早从哪冒出来 → 怎么变的 → 哪一步拐成了今天的意思
  2. 辩证:它的反面是什么 → 正反碰撞后,更高一层的理解是什么
  3. 现象:扔掉所有预设,回到事情本身 → 用一个日常场景把它还原出来
  4. 语言:拆字源(中/英/希腊/拉丁)→ 画出相邻概念的语义网 → 这个词暗含什么隐喻
  5. 形式:写一个公式或形式化表达 → 公式在哪里失效
  6. 存在:这个概念改变了人怎么活着
  7. 美感:它美在哪?用一个具体意象呈现
  8. 元反思:我们在用什么隐喻理解它?这个隐喻挡住了什么?换一个会怎样
3. 内观
  1. 变成这个概念本身,用第一人称看世界。3-5 句。
  2. 八刀之中,哪几刀指向同一个深层结构?把它提出来。
4. 压缩
  1. 公式:概念 = ...
  2. 一句话:用最简单的话说出最深的理解
  3. 结构图:纯 ASCII 画出概念的骨架(只用 +-|/<>*=_.,:;!'" 等基本符号,不用 Unicode 绘图字符)
5. 写入

格式规则(零例外):

  • 输出必须是纯 org-mode 语法,禁止任何 markdown 语法
  • 加粗用 *bold*(org-mode),不用 **bold**(markdown)
  • 分隔线用空行或 org 标题层级区分,不用 ---(markdown 分隔符)
  • 列表用 - item 或 1. item,不用 markdown 的 * item(因为 * 在 org 中是标题)
  • 代码用 ~code~ 或 =code=,不用反引号

整合为 org-mode,结构:

org
#+title: 概念解剖:{概念名}
#+filetags: :concept:
#+date: [YYYY-MM-DD]

* 定锚
* 八刀
** 历史
** 辩证
** 现象
** 语言
** 形式
** 存在
** 美感
** 元反思
* 内观
* 压缩

写入文件:

  1. 运行 date +%Y%m%dT%H%M%S 获取时间戳。
  2. 写入 ~/Documents/notes/{timestamp}--概念解剖-{概念名}__concept.org。
  3. 报告路径,完成。

© lijigang, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

Just SKILL.md in skills/ljg-learn of lijigang/ljg-skills.

Open the folder on GitHubat commit 9e75497

Compare with similar skills

Ljg Learn next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

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AI Engineering Project Tutorrohitg00/ai-engineering-from-scratch66k—~1.6kAutomated safety check: PassMIT
Hung-Yi Lee Teaching Stylevoidful/hung-yi-lee-skill1.3k—~13kAutomated safety check: PassNone
Claude Certification Tutorrohitg00/ai-engineering-from-scratch66k—~3kAutomated safety check: PassMIT
StudyVault Quiz Tutorbevibing/tutor-skills1.3k—~1.4kAutomated safety check: PassMIT

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Categories

Questions about Ljg Learn

What does Ljg Learn do?

Deep concept anatomist that deconstructs any concept through 8 exploration dimensions (history, dialectics, phenomenology, linguistics, formalization, existentialism, aesthetics, meta-philosophy)…. Ljg Learn is an agent skill from lijigang/ljg-skills. 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.

When should I use Ljg Learn?

Ljg Learn fits situations like: user asks to explain; deeply understand a concept; explain concept.

How do I install Ljg Learn in Claude Code?

Run `npx skills add lijigang/ljg-skills --skill ljg-learn -a claude-code`. Or copy the skill folder (skills/ljg-learn in lijigang/ljg-skills) into .claude/skills/ljg-learn in your project. Claude Code loads it when a task matches its description.

How do I install Ljg Learn in Codex?

Run `npx skills add lijigang/ljg-skills --skill ljg-learn -a codex`. Or copy the skill folder (skills/ljg-learn in lijigang/ljg-skills) into .agents/skills/ljg-learn in your project. Codex loads it when a task matches its description.

Can I use Ljg Learn in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add lijigang/ljg-skills --skill ljg-learn -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/ljg-learn, .gemini/skills/ljg-learn, .github/skills/ljg-learn and .opencode/skills/ljg-learn in your project.

What does Ljg Learn need to run?

SKILL.md names no scripts, command-line tools or credentials: Ljg Learn is instructions for the agent only.

Does Ljg Learn access the network?

SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.

Is Ljg Learn safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does Ljg Learn use?

Ljg Learn is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Ljg Learn use?

About 433 tokens (SKILL.md is roughly 1.7k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to Ljg Learn?

Skills that share tags, products or a category with Ljg Learn: DeepTutor CLI (HKUDS/DeepTutor, 41k stars), AI Engineering Project Tutor (rohitg00/ai-engineering-from-scratch, 66k stars), Hung-Yi Lee Teaching Style (voidful/hung-yi-lee-skill, 1.3k stars) and Claude Certification Tutor (rohitg00/ai-engineering-from-scratch, 66k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Ljg Learn?

lijigang (a GitHub user) maintains it in lijigang/ljg-skills, which has 7,474 GitHub stars. The repository holds 26 skills in this directory. The repository was last updated on October 8, 2026.

Source: lijigang/ljg-skills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.