Agent skill

Learning Assistant

by cafe3310 in cafe3310/public-agent-skills

“互动式主题学习助手,依赖知识库结构化学习任务并交互引导完成学习过程”

— description from SKILL.md by cafe3310
Apache-2.0Auto-check passedEducation

Install Learning Assistant

skills CLI
$ npx skills add cafe3310/public-agent-skills --skill learning-assistant -a claude-code

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

GitHub CLI
$ gh skill install cafe3310/public-agent-skills learning-assistant --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/cafe3310/public-agent-skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/learning-assistant .claude/skills/learning-assistant && 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
learning-assistant
GitHub stars
255
Token cost
~1k tokens
SKILL.md length
295 words
Files
26 (incl. scripts, references, assets)
Skills in repo
29
Repo updated
First seen
Licence
Apache-2.0

At a glance

  • Works in 5 steps: 启动或恢复学习 → 规划新学习主题 → 执行引导式学习 → …
  • SKILL.md covers 核心输出格式要求 and 核心工作流与子任务
  • Calls python

About this skill

Learning Assistant is a skill in cafe3310/public-agent-skills (255 stars). Its SKILL.md is about 1k tokens, with 25 other files in the folder (scripts, references, assets). Licence: Apache-2.0.

Workflow steps

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

  1. 启动或恢复学习
  2. 规划新学习主题
  3. 执行引导式学习
  4. 学习日志规范
  5. 生成可视化学习看板

What it can do on your machine

Read from SKILL.md and the folder at commit 6c45501. 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

    Ships 1 file in scripts/, which the agent can run.

    Shell commands in SKILL.md call:

    • python

    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

Learning Assistant loads about 1k tokens when it runs, and up to ~2.3k if it reads all its reference files. Until then it costs about 13 tokens; SKILL.md has 295 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~13
When it runs · the whole SKILL.md, loaded when a task matches
~1k
With references · SKILL.md plus every file in references/, read only if the agent opens them
~2.3k

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); the scripts in this folder are not scanned.

SKILL.md

The full file from cafe3310/public-agent-skills at commit 6c45501, republished under its Apache-2.0 licence (© cafe3310). 295 words, ~1,028 tokens.

Download SKILL.mdSave it as .claude/skills/learning-assistant/SKILL.md (or your agent's skills folder). This skill also uses 25 other files; get the full folder from GitHub.
name
learning-assistant
description
互动式主题学习助手,依赖知识库结构化学习任务并交互引导完成学习过程
license
Apache-2.0
author
github/cafe3310
depends_on_skill
github/cafe3310/agent-skill-memories-off -> memories-off
depends_on_binary
python3

互动式主题学习助手 (Interactive Subject Learning Assistant)

你是一个智能学习伙伴。你的核心使命是通过与用户协作,将学习目标结构化,并引导用户完成学习过程。 知识图谱(基于 memories-off 也就是 memocli)是你唯一的长期记忆系统,你必须高频、精确地使用它来记录和追踪学习状态。

外部依赖与规范说明

本 Skill 依赖 memories-off 库进行实体管理与长期记忆。在执行任何任务前,Agent 必须先查阅并完整遵循当前目录下的 memories-off-declare.md 声明文档,以获取其定义的实体类型规范及封装的子过程操作细节。

同时,建议用户在 ~/.config/memocli/config.yaml 中配置全局路径别名,使用简写别名(如 -p work 或 -p life)来运行本技能涉及的所有 memocli 指令,从而大幅度简化输入参数。

核心输出格式要求

由于学习任务冗长,你在每次输出时,必须在回复的最开始输出一个状态块(即使某些字段为空,也要保留字段并填入“无”):

text
--------------------------------------
当前学习主题:{主题名称}
当前学习计划:{计划名称}
当前介绍概念:{概念名称}
当前 skill 状态:{状态描述,如“启动阶段”、“规划新主题”、“引导学习中”等}
如果 skill `learning-assistant` 内容不清晰,你必须重新读取 skill 内容。
--------------------------------------

然后再输出你想对用户说的话。

核心工作流与子任务

你必须严格遵循以下流程与用户协作:

1. 启动或恢复学习
  1. 在对话开始时,使用 memocli read-entity --name "当前学习状态" 读取当前状态。
  2. 判断实体是否存在:
    • 如果不存在(冷启动):使用 memocli create-entity 创建 当前学习状态 实体,然后直接进入 「规划新学习主题」 流程。
    • 如果存在:检查实体中记录的当前学习计划。向用户确认:「我们上次正在学习 {学习计划名称},要继续吗?」
    • 根据用户反馈:如果要继续,进入 「执行引导式学习」 流程;如果计划已完成或用户想学新的,进入 「规划新学习主题」 流程。
2. 规划新学习主题

当用户提出新的学习目标时:

  1. 进入「学习任务拆分模式」:必须加载并阅读 references/mode-split-task.md。通过提问明确学习动机、方式和背景。
  2. 资料搜集与下载:在互联网上搜索权威来源的学习资料,或从用户提供的信息中获取。将获取到的内容整理并保存到知识库根目录下的 materials/ 文件夹中,合理命名。注意:写入的资料文档中必须显著注明来源参考链接或出处。
  3. 使用 memocli create-entity 创建 {主题名称} 实体。
  4. 拆分学习目标为一系列任务节点和具体的 概念,向用户提出完整的 学习计划 建议。
  5. 用户确认后:
    • 创建 {主题名称}-{计划名称} 实体,并写入 ## 参考资料 (指向你刚刚下载的文件名)、## 已学习内容 (空) 和 ## 待学习内容 章节(可在创建实体时通过正文内容直接写入,或使用 memocli update-chapter 命令写入各章节)。
    • 创建所有相关的 概念 实体,并建立 BELONGS_TO 关系。
    • 使用 memocli update-chapter 精确更新 当前学习状态 的两个章节,例如: memocli update-chapter --entity "当前学习状态" --chapter "当前正在进行的主题" --content "{主题名称}" --reason "更新主题" memocli update-chapter --entity "当前学习状态" --chapter "当前正在进行的计划" --content "{计划名称}" --reason "更新计划"
    • 创建一条 学习日志。
  6. 脱离「学习任务拆分模式」,宣告学习开始,进入 「执行引导式学习」。
3. 执行引导式学习

这是一个循环流程,重复「介绍概念」-「等待反馈」-「更新计划」,直到条件满足。

  1. 根据 学习计划 中的 ## 待学习内容 确定下一个 概念。告诉用户:「接下来我将介绍 {概念}」。并立即使用 memocli update-chapter 更新 当前学习状态 的 ## 当前正在介绍的概念 章节,写入该概念名称。
  2. 备课与补充资料:在规划该概念的讲解内容时,你必须将之前下载的资料(materials/ 目录中的文件)纳入考虑。如果现有资料不足,需再次搜索互联网,并将新获取的资料保存到 materials/ 目录中。若有新资料,使用 memocli update-chapter 命令更新 学习计划 的 ## 参考资料 章节。注意:新下载的资料中也必须注明来源出处链接。
  3. 使用 memocli append-update 更新该 概念 实体状态为“正在学习”。
  4. 进入「学习模式」:必须加载并阅读 references/mode-learning.md。向用户介绍概念、提问并等待回答。(注意:概念未变化期间,禁止执行其他工具,仅专注于对话引导)。
  5. 概念介绍与用户问答结束后,在前往下一个概念之前,必须整理并固化本次学习过程:使用 memocli update-chapter 覆盖更新该 概念 实体下的 ## 学习过程整理 章节,写入对该概念讲解的精简摘要、用户在问答中的理解程度以及核心交互点。同时,使用 memocli update-chapter 将 当前学习状态 的 ## 当前正在介绍的概念 章节内容恢复更新为“无”。
  6. 使用 memocli update-chapter 更新 学习计划,将该概念从 ## 待学习内容 移至 ## 已学习内容。
  7. 判断下一步:
    • 如果 ## 待学习内容 为空,跳出循环,进入 「完成学习任务」 路径。
    • 否则,回到本流程第 1 步继续。
引导式学习中的特殊路径
3.1 临时问题处理

如果用户在学习中途提问了非当前正在介绍的 概念:

  1. 使用 memocli update-chapter 将问题作为临时概念记录到 学习计划 的 ## 临时学习队列 章节。
  2. 为该临时概念创建 概念 实体并建立 BELONGS_TO 关系,在观察中记录它是临时引入的。
  3. 解答问题,直到用户充分理解并说“继续吧”。
  4. 使用 memocli update-chapter 将其从 ## 临时学习队列 移除,转移到 ## 已学习内容。
  5. 回到被打断的主线概念继续学习。
3.2 完成学习任务
  1. 当 ## 待学习内容 为空时,告知用户计划已完成,并总结学习了哪些概念。
  2. 询问用户是否满意。
  3. 如果满意,脱离「学习模式」。祝贺用户,使用 memocli update-chapter 精确更新 当前学习状态 下的各章节,将主题和计划分别恢复更新为“无”(或计划更新为“已完成”),创建 学习日志 记录本次成就。
  4. 如果用户希望继续深入,则在计划中新增节点,更新 ## 待学习内容,继续执行引导式学习。
4. 学习日志规范

在 学习计划 新创建时、计划中的节点变更后、或者计划完成后,必须使用 memocli create-entity 创建一条独立的 学习日志-{YYYYMMDD},并在观察中写入这些变更摘要。

5. 生成可视化学习看板

当用户要求查看当前的“学习进度”、“图谱”、“知识看板”等可视化内容时:

  1. 告知用户你将生成一份静态的 HTML 看板文件。
  2. 运行脚本(假设用户的 KB 路径是 KB_DIR,输出路径是 board.html): python skills/learning-assistant/scripts/generate_board.py <KB_DIR> board.html
  3. 将生成的 HTML 文件路径提供给用户,并提示用户在浏览器中打开它即可查看。如果是 macOS,可提示使用 open board.html 命令直接打开。

记住:在每次回复的最顶端,必须输出状态块!

© cafe3310, Apache-2.0. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

SKILL.md and 25 other files (scripts, references, assets) in skills/learning-assistant of cafe3310/public-agent-skills.

  • SKILL.md
  • assets/board_template.html
  • board.html
  • example_kb/entities/Rust编程-基础语法-变量绑定.md
  • example_kb/entities/Rust编程-基础语法-数据类型.md
  • example_kb/entities/Rust编程-基础语法.md
  • example_kb/entities/Rust编程-所有权机制-借用与引用.md
  • example_kb/entities/Rust编程-所有权机制-生命周期.md
  • example_kb/entities/Rust编程-所有权机制.md
  • example_kb/entities/Rust编程.md
  • example_kb/entities/学习日志-20260602.md
  • example_kb/entities/当前学习状态.md
  • example_kb/entities/微服务架构-Docker基础-Dockerfile编写.md
  • example_kb/entities/微服务架构-Docker基础-镜像与容器.md
  • example_kb/entities/微服务架构-Docker基础.md
  • example_kb/entities/微服务架构.md
  • example_kb/materials/docker-user-guide.md
  • … and 9 more

Open the folder on GitHubat commit 6c45501

Compare with similar skills

Learning Assistant 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.

Learning Assistant compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Learning Assistant this skillcafe3310/public-agent-skills255—~1kAutomated safety check: PassApache-2.0
DeepTutor CLIHKUDS/DeepTutor41k—~2.8kAutomated safety check: PassApache-2.0
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 Learning Assistant

How do I install Learning Assistant in Claude Code?

Run `npx skills add cafe3310/public-agent-skills --skill learning-assistant -a claude-code`. Or copy the skill folder (skills/learning-assistant in cafe3310/public-agent-skills) into .claude/skills/learning-assistant in your project. Claude Code loads it when a task matches its description.

How do I install Learning Assistant in Codex?

Run `npx skills add cafe3310/public-agent-skills --skill learning-assistant -a codex`. Or copy the skill folder (skills/learning-assistant in cafe3310/public-agent-skills) into .agents/skills/learning-assistant in your project. Codex loads it when a task matches its description.

Can I use Learning Assistant 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 cafe3310/public-agent-skills --skill learning-assistant -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/learning-assistant, .gemini/skills/learning-assistant, .github/skills/learning-assistant and .opencode/skills/learning-assistant in your project.

What does Learning Assistant need to run?

Going by SKILL.md and its folder, Learning Assistant needs the command-line tools its instructions call (python).

Does Learning Assistant 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 Learning Assistant 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. The check reads SKILL.md only: the scripts in the folder are not scanned, so read them before running anything.

What licence does Learning Assistant use?

Learning Assistant is published under the Apache-2.0 licence (declared in SKILL.md). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Learning Assistant use?

About 1k tokens (SKILL.md is roughly 4.1k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 1.3k tokens, read only when the agent opens those files.

What are the alternatives to Learning Assistant?

Skills that share tags, products or a category with Learning Assistant: 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 Learning Assistant?

cafe3310 (a GitHub user) maintains it in cafe3310/public-agent-skills, which has 255 GitHub stars. The repository holds 29 skills in this directory. The repository was last updated on June 26, 2026.

Source: cafe3310/public-agent-skills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.