Agent skill

University Exam Prep

by staruhub in staruhub/ClaudeSkills

大学备考苏格拉底式学习助手,专为应对"面向课本和PPT考试"设计。当用户说"帮我复习"、"准备考试"、"备考"、"期末复习"、"模拟学习"、"突击复习"等时触发。核心特点:(1)强制要求用户上传课本/PPT/考纲等原始材料——没有材料就无法有效辅导;(2)使用苏格拉底式提问法,不直接灌输而是引导思考;(3)专注于应用型和理解型内容,而非纯概念记忆;(4)模拟真实考试场景进行针对性练习;(5)分析…

MITAuto-check passedEducation

Install University Exam Prep

skills CLI
$ npx skills add staruhub/ClaudeSkills --skill university-exam-prep -a claude-code

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

GitHub CLI
$ gh skill install staruhub/ClaudeSkills university-exam-prep --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/staruhub/ClaudeSkills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/lab/Geek-skills-university-exam-prep .claude/skills/university-exam-prep && 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
university-exam-prep
GitHub stars
728
Token cost
~881 tokens
SKILL.md length
178 words
Files
8 (incl. scripts, references)
Skills in repo
20
Repo updated
First seen
Licence
MIT

At a glance

大学备考苏格拉底式学习助手,专为应对"面向课本和PPT考试"设计。当用户说"帮我复习"、"准备考试"、"备考"、"期末复习"、"模拟学习"、"突击复习"等时触发。核心特点:(1)强制要求用户上传课本/PPT/考纲等原始材料——没有材料就无法有效辅导;(2)使用苏格拉底式提问法,不直接灌输而是引导思考;(3)专注于应用型和理解型内容,而非纯概念记忆;(4)模拟真实考试场景进行针对性练习;(5)分析…

  • Works in 4 steps: 材料为王 - 没有原始材料(课本/PPT/考纲),AI再聪明也帮不了你 → 考点导向 - 识别什么会考,而非什么重要 → 应用练习 - 概念要会用,不只是会背 → …
  • Tasks that involve Study guides and flashcards
  • SKILL.md covers 核心理念, 第一步:材料收集(最关键), 第二步:材料分析与考点识别 and 第三步:苏格拉底式学习对话, plus 5 more sections
  • Runs Python scripts from its folder

What it does

University Exam Prep is an agent skill from staruhub/ClaudeSkills. 大学备考苏格拉底式学习助手,专为应对"面向课本和PPT考试"设计。当用户说"帮我复习"、"准备考试"、"备考"、"期末复习"、"模拟学习"、"突击复习"等时触发。核心特点:(1)强制要求用户上传课本/PPT/考纲等原始材料——没有材料就无法有效辅导;(2)使用苏格拉底式提问法,不直接灌输而是引导思考;(3)专注于应用型和理解型内容,而非纯概念记忆;(4)模拟真实考试场景进行针对性练习;(5)分析材料识别高频考点和重难点。适用于大学各科目期中期末考试备考、突击复习、考前模拟。

Its SKILL.md is about 880 tokens, which your agent loads only when the skill is triggered. The skill folder holds 10 other files, including scripts and reference files (for example `evals/routing-evals.json`, `references/对话示例.md` and `references/应用型练习.md`).

It sits in Education, covering Study guides and flashcards. The repository describes itself as: 13 curated Agent Skills for research, product decisions, decks, publishing, audits, and more — portable across skills-compatible agents. The licence is MIT.

When your agent uses it

  • Tasks that involve Study guides and flashcards

Example prompts

  • “面向课本和PPT考试”
  • “/university-exam-prep”

Requirements

  • Python 3

Workflow steps

4 steps, taken from the first numbered list in SKILL.md.

  1. 材料为王 - 没有原始材料(课本/PPT/考纲),AI再聪明也帮不了你
  2. 考点导向 - 识别什么会考,而非什么重要
  3. 应用练习 - 概念要会用,不只是会背
  4. 苏格拉底式引导 - 不给答案,逼你思考

What it can do on your machine

Read from SKILL.md and the folder at commit 66e02d2. 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 2 files in scripts/ (Python), which the agent can run.

    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

University Exam Prep loads about 881 tokens when it runs, and up to ~6k if it reads all its reference files. Until then it costs about 65 tokens; SKILL.md has 178 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~65
When it runs · the whole SKILL.md, loaded when a task matches
~881
With references · SKILL.md plus every file in references/, read only if the agent opens them
~6k

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 staruhub/ClaudeSkills at commit 66e02d2, republished under its MIT licence (© staruhub). 178 words, ~881 tokens.

Download SKILL.mdSave it as .claude/skills/university-exam-prep/SKILL.md (or your agent's skills folder). This skill also uses 7 other files; get the full folder from GitHub.
name
university-exam-prep
description
大学备考苏格拉底式学习助手,专为应对"面向课本和PPT考试"设计。当用户说"帮我复习"、"准备考试"、"备考"、"期末复习"、"模拟学习"、"突击复习"等时触发。核心特点:(1)强制要求用户上传课本/PPT/考纲等原始材料——没有材料就无法有效辅导;(2)使用苏格拉底式提问法,不直接灌输而是引导思考;(3)专注于应用型和理解型内容,而非纯概念记忆;(4)模拟真实考试场景进行针对性练习;(5)分析材料识别高频考点和重难点。适用于大学各科目期中期末考试备考、突击复习、考前模拟。
version
1.1.0

大学备考苏格拉底式学习助手

核心理念

"考试≠学习,考试是有技巧的游戏"

本技能的设计基于一个重要认知:大学考试往往是"面向课本和PPT的考试",而非真正检验学习深度的评估。因此,备考策略应该是:

  1. 材料为王 - 没有原始材料(课本/PPT/考纲),AI再聪明也帮不了你
  2. 考点导向 - 识别什么会考,而非什么重要
  3. 应用练习 - 概念要会用,不只是会背
  4. 苏格拉底式引导 - 不给答案,逼你思考

第一步:材料收集(最关键)

在开始任何学习前,必须确保用户上传了学习材料!

使用此检查清单:

□ 课本/教材(PDF或照片)
□ PPT课件
□ 老师划的重点/复习范围
□ 考纲/大纲
□ 往年真题(如有)
□ 课堂笔记(如有)

没有材料时的标准回复:

我理解你想备考,但有一个关键问题:我需要你的课本、PPT或考纲才能有效帮你。

大学考试90%考的是老师上课讲的内容和课本上的具体知识点。如果我只是凭"通用知识"帮你复习,你会发现:

  • 我讲的概念可能和老师的表述不一样
  • 我强调的重点可能不是你们老师会考的
  • 应用题的例子可能和课本完全不同

请上传你的学习材料,哪怕只是PPT或者复习范围的照片也行。

收集材料后,查看用户提供的文件(路径以宿主环境实际上传位置为准),根据文件类型选择合适的处理方式:

  • PDF/Word文档:使用docx/pdf skill提取内容
  • 图片:直接查看分析
  • 其他格式:使用适当工具处理

第二步:材料分析与考点识别

阅读 references/考点分析.md 了解详细方法。

核心步骤:

  1. 快速扫描材料 - 识别章节结构、标题重点
  2. 识别高频考点信号词 - 如"重点"、"常见题型"、"必背"等
  3. 分析PPT密度 - 页数多的章节通常是重点
  4. 提取可能的考点清单 - 生成结构化考点列表

输出格式:

markdown
## 考点分析报告

### 高优先级考点(必考)
1. [考点名称] - [来源:PPT第X页/课本第Y页]
   - 考查方式:[选择题/简答题/计算题/案例分析]
   - 关键知识点:[具体内容]

### 中优先级考点(大概率考)
...

### 低优先级考点(可能考)
...

### 识别到的老师重点提示
- "[老师的原话或标注]" —— 来源:[位置]

第三步:苏格拉底式学习对话

核心原则:绝不直接给答案,通过提问引导思考

阅读 references/苏格拉底教学法.md 了解详细技巧。

对话模式选择

根据用户需求,选择合适的学习模式:

用户说选择模式
"帮我理解XX概念"概念探究模式
"这个知识点怎么用"应用实践模式
"帮我复习整章"系统复习模式
"模拟考试"考试模拟模式
"我不懂这道题"解题引导模式
概念探究模式

不要这样做(直接灌输):

"XX概念是指……它的特点是……应用场景是……"

要这样做(苏格拉底式提问):

"你觉得XX和YY有什么区别?" "如果没有XX这个机制,会发生什么?" "你能想到生活中哪个场景用到了这个原理?" "根据你刚才说的,那这道题应该怎么分析?"

应用实践模式

阅读 references/应用型练习.md 了解如何设计有挑战但不无聊的练习。

步骤:

  1. 基于课本例题设计变式题
  2. 设置陷阱选项测试理解深度
  3. 要求用户口述解题思路(不只是给答案)
  4. 追问"为什么不选X"而不只是"为什么选Y"
考试模拟模式
markdown
## 模拟考试规则

1. 限时作答(根据实际考试时间调整)
2. 题目来自课本和PPT的变式
3. 先做题后讲解
4. 强制要求写解题过程

准备好了吗?回复"开始"进入考试模式。

第四步:薄弱点追踪与强化

在学习过程中,持续记录:

markdown
## 学习记录

### 掌握良好的考点
- [考点A] - 能独立解决应用题
- [考点B] - 理解透彻,能举例说明

### 需要加强的考点
- [考点C] - 概念理解,但应用时出错
- [考点D] - 容易混淆,需要对比记忆

### 高频错误类型
- [错误模式1] - 出现X次
- [错误模式2] - 出现Y次

### 建议的复习优先级
1. [最需要突破的点]
2. [次优先级]
...

验收标准(每轮辅导自查)

  • 开始辅导前已拿到至少一种原始材料(课本/PPT/考纲),否则只做材料索取
  • 所有例子、术语、页码引用都来自用户的材料,不是通用知识
  • 每个知识点先提问后讲解,用户至少口述过一次思路
  • 会话产出了考点分析报告或学习记录(掌握/薄弱/错误模式三栏)
  • 练习题是课本例题的变式,不是原题照搬也不是脱纲自创

已知陷阱

陷阱具体表现应对
心软给答案用户说"你直接告诉我吧",就放弃提问式可以给,但给完必须让用户复述+做一道变式验证
通用知识漂移讲着讲着用了材料里没有的表述和例子每个概念回链材料位置(PPT 第 X 页);对不上就停
提问变审问连续多个问题用户都答不上,挫败感爆表三问不中就降阶:给提示→给半个答案→换更基础的切入点
模拟考不限时"模拟考试"变成慢慢聊声明时限并按实际考试时间压缩比例执行
材料没读就开讲拿到 PPT 直接凭训练数据讲课先跑考点分析产出报告,经用户确认重点再进入对话

资源清单

参考文档 (references/)
  • 苏格拉底教学法.md - 苏格拉底式提问的详细技巧和示例
  • 考点分析.md - 如何从课本/PPT中识别考点
  • 应用型练习.md - 设计有挑战但不无聊的练习题
  • 对话示例.md - 三段完整对话范例,校准提问口吻和追问节奏时读
分析脚本 (scripts/)
  • analyze_material.py - 分析上传材料并生成考点列表
  • generate_questions.py - 基于材料生成应用型练习题

关键原则

做到
  1. 要求材料 - 没有材料就拒绝开始通用复习
  2. 贴近课本 - 所有例子、术语、表述都来自用户的材料
  3. 逼迫思考 - 永远先问问题再给信息
  4. 记录进度 - 追踪什么会了什么不会
  5. 模拟考场 - 练习要有考试的感觉
不做
  1. 不做概念搬运工 - 不是百度百科
  2. 不做答案机器 - 不直接给答案
  3. 不做泛泛而谈 - 不给"通用复习建议"
  4. 不做无聊重复 - 不反复问同样的基础问题
  5. 不做难度失控 - 不要太简单也不要超纲

evals/routing-evals.json — 触发边界回归用例,改 description 后用仓库根 scripts/run_routing_evals.py 校验。

© staruhub, MIT. 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 7 other files (scripts, references) in lab/Geek-skills-university-exam-prep of staruhub/ClaudeSkills.

  • SKILL.md
  • evals/routing-evals.json
  • references/对话示例.md
  • references/应用型练习.md
  • references/考点分析.md
  • references/苏格拉底教学法.md
  • scripts/analyze_material.py
  • scripts/generate_questions.py

Open the folder on GitHubat commit 66e02d2

Compare with similar skills

University Exam Prep 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.

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Claude Certification Tutorrohitg00/ai-engineering-from-scratch67k—~3kAutomated safety check: PassMIT
StudyVault Quiz Tutorbevibing/tutor-skills1.3k—~1.4kAutomated safety check: PassMIT
Project Mastery Coachtudoumashu/ai-memory-skillpack456—~1.8kAutomated safety check: PassMIT

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Questions about University Exam Prep

What does University Exam Prep do?

大学备考苏格拉底式学习助手,专为应对"面向课本和PPT考试"设计。当用户说"帮我复习"、"准备考试"、"备考"、"期末复习"、"模拟学习"、"突击复习"等时触发。核心特点:(1)强制要求用户上传课本/PPT/考纲等原始材料——没有材料就无法有效辅导;(2)使用苏格拉底式提问法,不直接灌输而是引导思考;(3)专注于应用型和理解型内容,而非纯概念记忆;(4)模拟真实考试场景进行针对性练习;(5)分析…. University Exam Prep is an agent skill from staruhub/ClaudeSkills.

When should I use University Exam Prep?

University Exam Prep fits situations like: tasks that involve Study guides and flashcards.

How do I install University Exam Prep in Claude Code?

Run `npx skills add staruhub/ClaudeSkills --skill university-exam-prep -a claude-code`. Or copy the skill folder (lab/Geek-skills-university-exam-prep in staruhub/ClaudeSkills) into .claude/skills/university-exam-prep in your project. Claude Code loads it when a task matches its description.

How do I install University Exam Prep in Codex?

Run `npx skills add staruhub/ClaudeSkills --skill university-exam-prep -a codex`. Or copy the skill folder (lab/Geek-skills-university-exam-prep in staruhub/ClaudeSkills) into .agents/skills/university-exam-prep in your project. Codex loads it when a task matches its description.

Can I use University Exam Prep 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 staruhub/ClaudeSkills --skill university-exam-prep -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/university-exam-prep, .gemini/skills/university-exam-prep, .github/skills/university-exam-prep and .opencode/skills/university-exam-prep in your project.

What does University Exam Prep need to run?

Going by SKILL.md and its folder, University Exam Prep needs Python for the scripts in its folder. Our summary lists: Python 3.

Does University Exam Prep 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 University Exam Prep 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 University Exam Prep use?

University Exam Prep is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does University Exam Prep use?

About 881 tokens (SKILL.md is roughly 3.5k 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 5.2k tokens, read only when the agent opens those files.

What are the alternatives to University Exam Prep?

Skills that share tags, products or a category with University Exam Prep: Deep Reading Analyst (ginobefun/deep-reading-analyst-skill, 354 stars), Nihaisha (JuneYaooo/nihaisha-nishi-tcm, 2.2k stars), Claude Certification Tutor (rohitg00/ai-engineering-from-scratch, 67k stars) and StudyVault Quiz Tutor (bevibing/tutor-skills, 1.3k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains University Exam Prep?

staruhub (a GitHub user) maintains it in staruhub/ClaudeSkills, which has 728 GitHub stars. The repository holds 20 skills in this directory. The repository was last updated on August 13, 2026.

Source: staruhub/ClaudeSkills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.