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Project Learner

Community
cafe3310
project-learner

结构化交互式学习助手,当用户希望学习项目相关知识、特定代码文件或底层技术时使用此技能,它会将学习过程记录为持久化的 Markdown 日志

Overview

Publishercafe3310
Repositorypublic-agent-skills
Skill nameproject-learner
Stars
256
Forks
30
Bundled files
Instructions only
LicenseApache-2.0
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 cafe3310 on GitHub. Read the source before you install it.

Installation

Install the Project Learner 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/cafe3310/public-agent-skills/tree/main/skills_parked/project-learner
  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/cafe3310/public-agent-skills.git /tmp/public-agent-skills
mkdir -p .claude/skills
cp -r /tmp/public-agent-skills/skills_parked/project-learner .claude/skills/project-learner
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Project Learner 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 Project Learner 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 Project Learner 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.

Project Learner (项目学习助手)

此技能将 Agent 转化为一位专属的项目导师,不仅回答用户的问题,还将每一次的讲解自动整理、记录到学习日志中。

要求

如果用户要求继续之前的学习,找找是否有符合条件的学习记录,或问用户提供这样的学习日志文件,然后继续。不必创建已经存在的文件。

会话初始化

当用户开启一个新的学习主题时:

明确信息: 确认用户想要学习的内容,也了解用户已有的知识水平。

创建日志: 在 docs/ 目录下创建一个新的 Markdown 文件。

  • 日志命名规范: {YYYY-MM-DD-HH-mm}-learning-{topic}.md (使用 date 命令获取精确时间)。
  • 日志结构: 描述 1. 用户的诉求和背景知识 2. 本次学习任务的信息 3. 用户提出的额外诉求

2. 交互式教学

初始化完成之后,用户可能对项目整体架构发问,也可能咨询特定变更,甚至可能咨询和项目无关的知识。

Agent 要对用户的每个问题,分析-调研-讲解-记录。必要时,查询互联网做 Grounding。

在记录时,将讲解内容写到新的 Markdown 日志中:

  • 日志命名规范: {YYYY-MM-DD-HH-mm}-learning-{topic}-{this-turn-topic}.md

  • 日志结构:参考结构如下, > 部分是给 Agent 的内容生成参考。

    ```markdown
    
    ### 问题
    > 用户的具体问题
    ...
    
    ### 讲解
    > 刚才的讲解内容
    ...
    
    ### 涉及代码
    > 如果有,列出项目中的相关代码,让用户可以参考学习
    ...
    
    ### 核心知识点
    > 列出讲解了的概念,让用户可以扩展了解
    ...
    
    ```

如果用户提出了任何对整体教学的额外诉求,编辑添加到学习会话的初始化日志,并在后面的教学中遵循。

Frequently asked questions

What does the Project Learner AI skill do?

结构化交互式学习助手,当用户希望学习项目相关知识、特定代码文件或底层技术时使用此技能,它会将学习过程记录为持久化的 Markdown 日志

Why use Project Learner on TypingMind?

Because you install it once and use it with any model. Project Learner 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 Project Learner in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/cafe3310/public-agent-skills/tree/main/skills_parked/project-learner. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Project Learner?

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 Project Learner?

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

Is the Project Learner AI skill free?

Yes. It is published on GitHub by cafe3310 under the Apache-2.0 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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