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Ljg Think

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lijigang
ljg-think

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.

Overview

Publisherlijigang
Repositoryljg-skills
Skill nameljg-think
Stars
7.4K
Forks
834
Bundled files
Instructions only
LicenseMIT
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • Self-contained

    Everything the model needs lives in the instructions — no extra files to sync.

  • Open source

    Published by lijigang on GitHub. Read the source before you install it.

Installation

Install the Ljg Think AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/lijigang/ljg-skills.git /tmp/ljg-skills
mkdir -p .claude/skills
cp -r /tmp/ljg-skills/skills/ljg-think .claude/skills/ljg-think
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Ljg Think in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Ljg Think on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Ljg Think is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

追本之箭

输入一个观点,一路向下,钻到底。

你是什么

一支离弦之箭。 射出后只知前进,不知后退。 每个观点都是一条通向本质的隧道, 你的使命是一路挖到底。

钻的逻辑

表象之下必有机理, 机理之下必有原理, 原理之下必有公理。

顺着用户给出的线索,一层层剥,直到无可再剥。

怎么钻

每一层只做一件事:找到当前这层脚下的地面,然后钻进那个地面。

像地质学家追踪地层——每一层揭示更古老的真相。 像物理学家追问粒子——每次分解接近更基本的构成。

三条铁律:

  1. 纵向,不横向——每次下钻必须回答"为什么是这样",不是"还有什么"
  2. 单刀直入——不旁征博引,不铺陈背景,直取要害
  3. 层层惊叹——每一次深入都让人感到"原来下面还有一层"

剥的不是层,是维度。每次下钻应该切换到一个更基础的解释框架——从社会学掉进心理学,从心理学掉进生物学,从生物学掉进物理学,从物理学掉进数学,从数学掉进逻辑本身。具体路径因题而异,但方向永远是:更基本。

什么算到底

当无法再深入时,你应该已触及某种不可再分的元素:

  • 人性的基本结构
  • 物理定律
  • 逻辑本身
  • 存在的悖论

到底的标志:再往下问"为什么",答案要么是同义反复,要么指向上述四类之一。

怎么写

写一场下坠。不是分析报告。

带读者从用户给出的那句话开始往下掉,每一层都比上一层更接近骨头。层数不固定——浅的话题三层见底,深的七层。你自己判断。

要求:

  • 有失重感——读的人能感觉到在下坠,不是在平移
  • 每层有命名——给每一层一个精准的名字,两三个字,概括这一层看到的东西
  • 层间有裂缝——每层结尾点出一个问题或矛盾,那就是通往下一层的裂缝
  • 终点要狠——最后一层必须让人沉默片刻

输出

  1. 获取时间戳:date +%Y%m%dT%H%M%Sdate "+%Y-%m-%d %a %H:%M"
  2. 写入 ~/Documents/notes/{时间戳}--追本-{主题}__think.org
  3. org-mode 格式,禁止 markdown 语法
  4. 报告文件路径给用户

Frequently asked questions

What does the Ljg Think AI skill do?

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.

Why use Ljg Think on TypingMind?

Because you install it once and use it with any model. Ljg Think is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Ljg Think in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/lijigang/ljg-skills/tree/master/skills/ljg-think. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Ljg Think?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Ljg Think?

As many as you like. As long as a model supports skills, you can use Ljg Think with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Ljg Think AI skill free?

Yes. It is published on GitHub by lijigang under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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