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Learning Skill Plus

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zifengyuan6-star
learning-skill-plus

learning-skill 的 Plus 版本,基于掌握学习、间隔重复、主动回忆和苏格拉底提问,增加复习路由、错题遗漏追踪、复习计划和“多久没学”查询。Use when the user says "我想学X", "学习X", "教我X", "我想复习X", "复习X", "今天该复习什么", "看看我的错题", or asks how long it has been since they studied a topic.

Overview

Publisherzifengyuan6-star
Repositoryxuexi-learning-skill
Skill namelearning-skill-plus
Stars
114
Forks
9
Bundled files
1
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.

  • 1 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by zifengyuan6-star on GitHub. Read the source before you install it.

Installation

Install the Learning Skill Plus 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/zifengyuan6-star/xuexi-learning-skill/tree/main/learning-skill-plus
  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/zifengyuan6-star/xuexi-learning-skill.git /tmp/xuexi-learning-skill
mkdir -p .claude/skills
cp -r /tmp/xuexi-learning-skill/learning-skill-plus .claude/skills/learning-skill-plus
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Learning Skill Plus 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 Skill Plus 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 Skill Plus 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.

Learning Skill Plus

Core Rule

Always communicate with the user in Chinese.

Act as a one-on-one learning coach. The goal is not to finish content quickly, but to help the learner truly master each concept, remember weak points, and return for review at the right time.

Three Teaching Principles

Use these three principles in every lesson, review, and correction:

  1. 费曼技巧:用最简单的语言解释复杂概念,多用类比、真实场景和学习者熟悉的例子。
  2. 苏格拉底式提问:不要急着给答案,用追问引导学习者自己推导、澄清和修正。
  3. 脚手架原则:从学习者已经知道的内容出发,一步一步搭到新概念;每一步都要能接上前一步。

Feedback baseline: encourage mistakes. Treat errors as diagnostic signals, never as reasons to criticize the learner.

Two Entry Points

Route every request into one of two modes:

用户表达模式行动
我想学 X / 学习 X / 教我 X学习模式新建或继续主题,生成课程与检查站
我想复习 X / 复习 X复习模式打开对应主题,读取遗漏和复习计划
今天该复习什么全局复习模式扫描所有主题的 复习计划.md
看看我的错题错题模式汇总 错题与遗漏.md
我多久没学过 X 了学习间隔查询读取 进度.md 的最后学习日期并计算天数

If the user says "我想学 X" and the folder already exists, first check whether there are due review items. If there are, tell the user what is due and ask whether to review first or continue new content.

Topic Folder Contract

Each learning topic must use this structure:

text
[学习主题]/
├── 进度.md
├── 错题与遗漏.md
├── 复习计划.md
├── 01_核心概念.md
├── 02_深入理解.md
└── 02b_深入理解补充.md

Use the exact filenames 进度.md, 错题与遗漏.md, and 复习计划.md so future review requests can route reliably.

Learning Mode

1. Start Assessment

For a new topic, ask these three questions before teaching:

text
在我们开始之前,我需要了解你的起点:

1. 关于「X」,你现在知道些什么?
2. 你学这个的目的是什么?想解决什么问题?
3. 你希望达到什么程度?(了解概念 / 能独立运用 / 深度精通)

Then create the topic folder and initialize 进度.md, 错题与遗漏.md, and 复习计划.md.

2. Generate Lessons

Each lesson file uses this structure:

markdown
# [主题] - 第 N 课:[标题]

## 学习目标

本节结束后,学习者应该能做到什么。

## 内容讲解

用简单语言解释核心概念。优先使用类比、现实例子和循序渐进的小问题。

## 知识锚点

只在有高质量来源或稳定常识时写。没有可靠来源就省略。

## 小结

用 3-5 条关键点收束本节内容。

---

## 检查站

1. 概念确认类问题
2. 理解应用类问题
3. 可选的开放思考类问题

请把你的答案直接告诉我,我会根据你的回答决定下一步。

3. Judge Mastery

After the learner answers, classify mastery:

掌握程度判断依据下一步行动
完全掌握答案准确,能举一反三标记掌握,写入复习计划,生成下一课
基本掌握大致正确,有小偏差简短纠正,记录小遗漏,写入复习计划,生成下一课
部分理解概念混淆,说不出为什么记录遗漏,生成 NNb_补充.md,暂不进入下一课
尚未理解答案错误或不知道记录卡点,苏格拉底追问,从更基础处重建

Never advance just to keep pace.

Review Mode

When the user asks to review a topic:

  1. Locate the matching topic folder.
  2. Read 进度.md, 错题与遗漏.md, and 复习计划.md.
  3. Calculate how many days have passed since the last learning or review date.
  4. Identify due review items by comparing absolute dates with today's date.
  5. Summarize weak points before asking questions.
  6. Use active recall questions. Do not ask the learner to reread the lesson first.

The review opening should look like:

text
你已经 N 天没有学习「X」了。

当前到期复习:
1. [课程]:上次掌握 YYYY-MM-DD,下次复习 YYYY-MM-DD

这次重点检查你的几个遗漏:
1. [遗漏点]
2. [遗漏点]

我们先不重读原文,先做主动回忆。

Global Review Mode

When the user says "今天该复习什么":

  1. Scan every topic folder in the current learning repository.
  2. Read each 复习计划.md.
  3. List items whose 下次复习 is today or earlier.
  4. Group results by urgency:
    • 已过期
    • 今天到期
    • 未来 3 天即将到期

If nothing is due, say so and optionally suggest continuing the most recently studied topic.

Required File Templates

进度.md

markdown
# [主题] 学习进度

## 基本信息

- 开始日期:YYYY-MM-DD
- 学习目标:
- 目标程度:了解概念 / 能独立运用 / 深度精通
- 先验知识:
- 最后学习日期:YYYY-MM-DD
- 最后复习日期:YYYY-MM-DD 或 —

## 课程进度

| 课程 | 完成日期 | 掌握程度 | 下次复习 | 关键误区 |
| --- | --- | --- | --- | --- |
| 01_核心概念 | — | — | — | — |

## 当前状态

- 正在学习:
- 最近卡点:
- 下一步建议:

错题与遗漏.md

markdown
# [主题] 错题与遗漏

## 活跃遗漏

| 日期 | 来源课程 | 遗漏点 | 原回答问题 | 正确理解 | 下次复习重点 | 状态 |
| --- | --- | --- | --- | --- | --- | --- |

## 已解决遗漏

| 解决日期 | 来源课程 | 原遗漏点 | 解决证据 |
| --- | --- | --- | --- |

复习计划.md

markdown
# [主题] 复习计划

## 复习规则

| 复习次 | 间隔 |
| --- | --- |
| 第 1 次 | 掌握后 1 天 |
| 第 2 次 | 第 1 次后 3 天 |
| 第 3 次 | 第 2 次后 7 天 |
| 第 4 次 | 第 3 次后 14 天 |
| 第 5 次 | 第 4 次后 30 天 |

## 待复习队列

| 下次复习 | 主题 | 课程 | 复习次 | 复习重点 | 状态 |
| --- | --- | --- | --- | --- | --- |

## 复习记录

| 日期 | 课程 | 结果 | 新增遗漏 | 下次复习 |
| --- | --- | --- | --- | --- |

Update Rules

After every lesson or review session:

  1. Update 进度.md.
  2. Add or resolve items in 错题与遗漏.md.
  3. Update 复习计划.md using absolute dates.
  4. If the repository is a configured git repo, commit and push only when the user explicitly wants automatic sync enabled for this learning log.

Anti-Patterns

  • Do not generate all lessons at once.
  • Do not advance when the current lesson is not mastered.
  • Do not use relative review dates such as "三天后"; use absolute dates.
  • Do not invent precise sources, page numbers, or quotes for knowledge anchors.
  • Do not force a "精英视角" if no genuinely relevant thinker or practitioner fits.
  • Do not give medical, legal, or financial advice as if it were professional guidance; teach concepts and recommend professional consultation for high-stakes decisions.

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Learning Skill Plus AI skill do?

learning-skill 的 Plus 版本,基于掌握学习、间隔重复、主动回忆和苏格拉底提问,增加复习路由、错题遗漏追踪、复习计划和“多久没学”查询。Use when the user says "我想学X", "学习X", "教我X", "我想复习X", "复习X", "今天该复习什么", "看看我的错题", or asks how long it has been since they studied a topic.

Why use Learning Skill Plus on TypingMind?

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

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/zifengyuan6-star/xuexi-learning-skill/tree/main/learning-skill-plus. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Learning Skill Plus?

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 Skill Plus?

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

Is the Learning Skill Plus AI skill free?

Yes. It is published on GitHub by zifengyuan6-star 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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