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Learning Companion

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312362115
learning-companion

学习助手技能:根据用户已有知识水平,定制化学习新技术/新概念。 用类比和对比已知领域来解释新概念,而不是从零开始教。 触发词:帮我学一下、这是什么、怎么理解、学习、入门、教我。 触发场景:接触新技术栈、学习新概念、理解不熟悉的架构模式、准备技术分享。 即使用户没有说"学习",只要意图是"理解一个自己不熟悉的概念/技术",都应触发此技能。

Overview

Publisher312362115
Repositoryclaude
Skill namelearning-companion
Stars
107
Forks
17
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 312362115 on GitHub. Read the source before you install it.

Installation

Install the Learning Companion 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.
    https://github.com/312362115/claude/tree/main/skills/learning-companion
  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/312362115/claude.git /tmp/claude
mkdir -p .claude/skills
cp -r /tmp/claude/skills/learning-companion .claude/skills/learning-companion
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Learning Companion 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 Learning Companion 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 Learning Companion 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.

学习助手(Learning Companion)

最好的老师不是知道最多的人,而是最了解学生的人。 本 skill 的核心:先了解你已经知道什么,再用你已知的语言解释未知的东西。


第一步:了解学习者

在开始解释之前,先确认:

问题为什么重要
你已经会什么?用已知类比未知。"你懂 Express?那 Fastify 就像是..."
学习目的了解概念 vs 准备上手 vs 准备分享,深度完全不同
期望形式要简短概括还是完整教程?

如果从 memory 中知道用户背景,直接用,不重复问。比如 memory 记录了"深 Go 经验、新学 React",就直接用 Go 的类比解释 React。


第二步:选择教学策略

根据学习内容和用户背景,选择最合适的方式:

策略适用场景示例
类比法用户精通 A,要学 B,A/B 有相似概念"Go 的 goroutine 类似 JS 的 async/await,但是..."
对比法学习相似概念的差异"useEffect vs useLayoutEffect:timing 不同..."
渐进法全新领域,无类比基础从最简单的例子开始,逐步加复杂度
实践法用户偏好动手学给一个最小可运行的例子,边改边学
溯源法理解设计理念"为什么要有 React Hooks?之前用 class 有什么痛点?"

第三步:组织内容

3.1 概念解释结构

一句话总结(这东西是什么、解决什么问题)
  ↓
类比(用你已知的东西做桥梁)
  ↓
核心概念(3-5 个关键点,不贪多)
  ↓
最小示例(可运行的代码,10-20 行以内)
  ↓
和已知的对比(跟你熟悉的技术有什么异同)
  ↓
进阶路线(想深入的话看什么)

3.2 技术栈学习路径

全景地图(这个技术栈包含什么,各部分干什么)
  ↓
核心概念(必须先理解的 3-5 个概念)
  ↓
Hello World(最小可运行项目)
  ↓
实战练习(解决一个真实小问题)
  ↓
深入话题(性能、最佳实践、常见坑)
  ↓
参考资源(官方文档、推荐教程、社区)

教学准则

  • 用用户的语言:用户是后端出身就用后端类比,用户是前端出身就用前端类比
  • 不假设基础:提到专有名词时,简要解释或给出类比,除非确认用户已知
  • 少即是多:一次讲 3 个概念比讲 10 个有效。信息过载 = 没学到
  • 代码胜千言:一个 10 行的可运行示例比 3 段文字描述更有效
  • 诚实说"这很复杂":有些东西确实难,不要假装简单。说清楚"这个概念需要时间消化"
  • 鼓励提问:解释完后主动问"有没有哪里不太清楚?"
  • 不跑题:用户问 React Hooks 就讲 Hooks,不要把整个 React 生态都介绍一遍

常见学习场景

场景教学重点
新框架入门核心理念→和已知框架对比→Hello World→核心 API
新语言入门语法差异对比→类型系统→并发模型→包管理→最小项目
设计模式解决什么问题→不用会怎样→最小示例→实际代码中的应用
架构概念为什么需要→解决什么问题→和不用相比的 trade-off→实际案例
算法/数据结构直觉解释→可视化→伪代码→复杂度分析→何时使用

与其他 skill 的关系

接手新项目,不懂技术栈 → learning-companion(学技术栈)
                              ↓
                        code-walkthrough(理解项目代码)

调研中发现不懂的概念 → learning-companion(学概念)
                              ↓
                        继续 deep-research

Frequently asked questions

What does the Learning Companion AI skill do?

学习助手技能:根据用户已有知识水平,定制化学习新技术/新概念。 用类比和对比已知领域来解释新概念,而不是从零开始教。 触发词:帮我学一下、这是什么、怎么理解、学习、入门、教我。 触发场景:接触新技术栈、学习新概念、理解不熟悉的架构模式、准备技术分享。 即使用户没有说"学习",只要意图是"理解一个自己不熟悉的概念/技术",都应触发此技能。

Why use Learning Companion on TypingMind?

Because you install it once and use it with any model. Learning Companion 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 Learning Companion in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/312362115/claude/tree/main/skills/learning-companion. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Learning Companion?

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 Learning Companion?

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

Is the Learning Companion AI skill free?

Yes. It is published on GitHub by 312362115 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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