Agent skill

Exam Review

by ZeKaiNie in ZeKaiNie/universal-examprep-skill

考前复盘已记录错题与概念疑难:重做原题、复述疑难、更新已订正/已回顾/待回顾状态,并形成最后扫雷清单. An agent skill from ZeKaiNie/universal-examprep-skill.

MITAuto-check passedEducation

Install Exam Review

skills CLI
$ npx skills add ZeKaiNie/universal-examprep-skill --skill exam-review -a claude-code

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

GitHub CLI
$ gh skill install ZeKaiNie/universal-examprep-skill exam-review --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/ZeKaiNie/universal-examprep-skill.git skills-src && mkdir -p .claude/skills && cp -r skills-src/full/skills/exam-review .claude/skills/exam-review && 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
exam-review
GitHub stars
303
Token cost
~1.1k tokens
SKILL.md length
494 words
Files
1
Skills in repo
12
Repo updated
First seen
Licence
MIT

At a glance

考前复盘已记录错题与概念疑难:重做原题、复述疑难、更新已订正/已回顾/待回顾状态,并形成最后扫雷清单. An agent skill from ZeKaiNie/universal-examprep-skill.

  • Works in 5 steps: Replay recorded mistakes. Reload state… → Update mistakes. Correct replay → 已订正;… → Replay confusions. Reload confusion_log;… → …
  • Tasks that involve Study guides and flashcards
  • SKILL.md covers Purpose, Activation, Inputs and Workflow, plus 3 more sections
  • Calls python

What it does

Exam Review is an agent skill from ZeKaiNie/universal-examprep-skill. 考前复盘已记录错题与概念疑难:重做原题、复述疑难、更新已订正/已回顾/待回顾状态,并形成最后扫雷清单。 进入最终复习阶段或用户要求复盘、查漏补缺时使用。

Its SKILL.md is about 1.1k tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.

It sits in Education, covering Study guides and flashcards. The repository describes itself as: Exam Cram Coach · 跨会话记忆与讲义溯源防幻觉的极速备考教练 | AI exam-prep tutor for Claude Code, Cursor, Codex, Antigravity: teaches from slides with page citations, crops figures, quizzes with real…. The licence is MIT.

When your agent uses it

  • Tasks that involve Study guides and flashcards

Example prompts

  • “/exam-review”

Requirements

  • Python 3

Workflow steps

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

  1. Replay recorded mistakes. Reload state (or update_progress.py show), fetch each exact bank item, and ask it again. Never add an…
  2. Update mistakes. Correct replay → 已订正; still wrong → explain from the stored explanation and retain it.
  3. Replay confusions. Reload confusion_log; ask the student to restate what/why/how. Correct restatement → 已回顾; vague → explain once and…
  4. Persist the open list first. Compile unresolved mistakes plus 待回顾 confusions for the final sprint/exam-cheatsheet. Pipe each…
  5. Persist row status. If study_state.json is absent and Python works, run update_progress.py --workspace init first; only when Python truly…

What it can do on your machine

Read from SKILL.md and the folder at commit b9e84f5. 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

    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

Exam Review loads about 1.1k tokens when it runs. Until then it costs about 22 tokens; SKILL.md has 494 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~22
When it runs · the whole SKILL.md, loaded when a task matches
~1.1k

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); files beside SKILL.md are not scanned.

SKILL.md

The full file from ZeKaiNie/universal-examprep-skill at commit b9e84f5, republished under its MIT licence (© ZeKaiNie). 494 words, ~1,089 tokens.

Download SKILL.mdSave it as .claude/skills/exam-review/SKILL.md (or your agent's skills folder).
name
exam-review
description
考前复盘已记录错题与概念疑难:重做原题、复述疑难、更新已订正/已回顾/待回顾状态,并形成最后扫雷清单。 进入最终复习阶段或用户要求复盘、查漏补缺时使用。
license
MIT

exam-review — mistake and confusion review

Purpose

Clear recorded mistakes/confusions before the exam. Replay only existing records; teach no new chapter and invent no question.

Activation

Use at final review or when the student explicitly asks to replay mistakes/find gaps.

Inputs

  • study_state.json's mistake_archive and confusion_log when state exists; otherwise generated 「❌ 错题档案」 and confusion compatibility rows.
  • references/quiz_bank.json, used to fetch each recorded mistake by exact ID.

Workflow

  1. Replay recorded mistakes. Reload state (or update_progress.py show), fetch each exact bank item, and ask it again. Never add an unrecorded/bank-external question.

    For requires_assets=true or maybe_requires_assets=true, before asking, explaining, hinting, or solving, render every question-side question_context / figure / diagram / table asset, labelled 题面图 or Question-side asset. Only later may solution/review show 答案图 / Answer-side asset. A path is not an image. Preserve but never display student_attempt; its physical path is tainted across the complete quiz, teaching, and content-unit layers, including duplicate official-looking declarations. Missing/unreadable or UI-unrenderable prompt assets cause a fail-closed skip; stub / page_reference also require the original prompt page first. Use scripts/show_question_assets.py for every replay and treat a nonzero result as a skip; do not render a raw bank path directly. See exam-quiz and docs/file-format.md §4.

  2. Update mistakes. Correct replay → 已订正; still wrong → explain from the stored explanation and retain it.

  3. Replay confusions. Reload confusion_log; ask the student to restate what/why/how. Correct restatement → 已回顾; vague → explain once and retain 待回顾.

  4. Persist the open list first. Compile unresolved mistakes plus 待回顾 confusions for the final sprint/exam-cheatsheet. Pipe each conclusion/list to python "${CLAUDE_SKILL_DIR}/scripts/notebook.py" --workspace <ws> add-entry --chapter <ch> --type review --id <slug> --title <gist>; same IDs replace and rebuild the index. Then send a digest and language-pack notebook link. If writing fails, say so and give the full list in chat; file-less clients use chat/text breakpoints.

  5. Persist row status. If study_state.json is absent and Python works, run update_progress.py --workspace <ws> init first; only when Python truly cannot run may Markdown rows be changed in place. Write results via update_progress.py set-mistake-status / set-confusion-status, and genuinely new rows via add-mistake / add-confusion. A nonzero Python command is a fail-loud error, not permission to hand-edit. Never leave a mastered row stale or overwrite another skill's writes.

Show full SKILL.md (136 more words)Show less

Output Contract

  • Produce one 「还没拿下的清单」 with current 已订正 / 已回顾 / 待回顾 statuses, notebook link, and refreshed panel.
  • Persist conclusions before the digest and persist every status via update_progress.py set-mistake-status / set-confusion-status.
  • Student prose is English by default, Simplified Chinese for a Chinese opening, or explicit bilingual blocks.

Language packs

Display aliases are normalized to zh, en, or bilingual.

Boundaries

  • study_state.json is the source of truth; mutate rows only via update_progress.py. Mark replay results via update_progress.py set-mistake-status / set-confusion-status; set-check alone is not a substitute.
  • Default question scope is mixed. A restricted scope excludes/counts missing source_type; announce any one-turn override first: 「⚠️ 临时覆盖你的 <scope> 范围偏好」 / ⚠️ Temporarily overriding your <scope> scope preference. Use scripts/select_questions.py.
  • Share confusion rows with confusion-tracker; replay only recorded bank items and never erase concurrent writes.

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

Files

Just SKILL.md in full/skills/exam-review of ZeKaiNie/universal-examprep-skill.

Open the folder on GitHubat commit b9e84f5

Compare with similar skills

Exam Review 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.

Exam Review compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Exam Review this skillZeKaiNie/universal-examprep-skill303—~1.1kAutomated safety check: PassMIT
Deep Reading Analystginobefun/deep-reading-analyst-skill3544 repos~3.6kAutomated safety check: PassMIT
NihaishaJuneYaooo/nihaisha-nishi-tcm2.2k—~4kAutomated safety check: PassNone
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

Similar skills

  • Deep Reading Analyst

    ginobefun/deep-reading-analyst-skill

    Comprehensive framework for deep analysis of articles, papers, and long-form content using 10+ thinking models (SCQA, 5W2H, critical thinking, inversion, mental models, first principles, systems…

    354 GitHub starsUsed in 4 repos~3.6k tokens
    EducationAuto-check passed
  • Nihaisha

    JuneYaooo/nihaisha-nishi-tcm

    A skill your agent uses when the user asks about Ni Haisha / 倪海厦 TCM course material, especially Shang Han Lun / 伤寒论, Jingui / 金匮要略, Zhongjing Xinfa / 仲景心法, clinical cases / 临床案例 / 倪师医案, Bagang…

    2.2k GitHub stars~4k tokensUpdated 25 days ago
    EducationAuto-check passed
  • Claude Certification Tutor

    rohitg00/ai-engineering-from-scratch

    Guides a learner through one of four independent Claude certification tracks with onboarding, lessons, practice labs, mock exams and remediation.

    67k GitHub stars~3k tokensUpdated today
    EducationAuto-check passed
  • StudyVault Quiz Tutor

    bevibing/tutor-skills

    Quizzes you on the notes in an Obsidian StudyVault, tracks proficiency per concept and drills weak areas in four-question rounds.

    1.3k GitHub stars~1.4k tokensUpdated 7 mo ago
    EducationAuto-check passed
  • Project Mastery Coach

    tudoumashu/ai-memory-skillpack

    Train strict project ownership from repo-local docs/ai memory and central LLM Wiki project entities.

    456 GitHub stars~1.8k tokensUpdated 1 mo ago
    EducationAuto-check passed
  • Turns a named classical Chinese chapter, such as one from the Tao Te Ching or the Analects, into a single annotated PNG image with notes and commentary.

    7.5k GitHub stars~551 tokensUpdated 2 days ago
    EducationAuto-check passed

More from ZeKaiNie/universal-examprep-skill

All 12 skills in this repo
  • Universal Exam Cram Coach Full

    ZeKaiNie/universal-examprep-skill

    帮助学生在临考前进行结构化极速复习:解析课程资料/大纲/重点,按章节生成 wiki 知识库与标准题库,组织针对性刷题与判分,并记录复习进度和错题。当用户即将考试、需要快速复习计划、练习题、错题复盘或考前小抄时使用(关键词:期末/备考/复习/刷题/划重点/错题;exam, cram, study plan, quiz, review)。不适用于长期学习规划、与考试无关的写作或编程任务。

    303 GitHub stars~2.6k tokensUpdated 13 days ago
    Auto-check passed
  • Exam Ingest

    ZeKaiNie/universal-examprep-skill

    从学生上传的课件/大纲/老师勾的重点/真题,一键初始化并验证备考工作区:解析 PDF、DOCX、PPTX、 XLSX、常见独立图片与 txt/md,建立分章节 LLM Wiki、标准题库、结构化接管队列与进度状态;仅在 Python 确实无法运行时 明确降级为手动写盘。当工作区尚未建立、资料发生变化、或建库 readiness 被阻断时使用。

    303 GitHub stars~5.6k tokensUpdated 13 days ago
    Auto-check passed
  • Exam Study Guide

    ZeKaiNie/universal-examprep-skill

    将已经讲完但尚未完成阶段门禁的一个章节整理成强类型教材清单,并在视觉模式下编译为公式可读、图片可见、知识点与全部对应例题逐项精讲的自包含 HTML/PDF。结构化工作区准备阶段完成证据、用户说 Markdown 公式仍是 raw LaTeX、图片缺失、要含课件/作业/Quiz/模拟考试题及答案的零基础讲义,或要求打印版时使用。

    303 GitHub stars~7.6k tokensUpdated 13 days ago
    Auto-check passed
  • Universal Exam Cram Coach

    ZeKaiNie/universal-examprep-skill

    临考复习教练 / Exam cram coach. An agent skill from ZeKaiNie/universal-examprep-skill.

    303 GitHub stars~2.4k tokensUpdated 13 days ago
    Auto-check: warnings
  • Confusion Tracker

    ZeKaiNie/universal-examprep-skill

    教学过程中自动捕获和记录学习者的概念疑难点("为什么/是什么/怎么推/什么意思"类型的问题),保存到进度文件的"概念疑难点记录"区,形成考前回顾清单。

    303 GitHub stars~1.5k tokensUpdated 13 days ago
    Auto-check passed
  • Exam Audit

    ZeKaiNie/universal-examprep-skill

    只读检查一个已生成的备考工作区是否健康并报告问题,默认不做任何修改。核对 .ingest 原材料版本、 内容单元、接管队列与派生产物完整性,以及 wiki、题库、视觉证据、计划和进度的一致性。当用户怀疑 工作区有问题、建库 readiness 被阻断、或想在开始复习前体检时使用。

    303 GitHub stars~2.6k tokensUpdated 13 days ago
    Auto-check passed

Categories

Questions about Exam Review

What does Exam Review do?

考前复盘已记录错题与概念疑难:重做原题、复述疑难、更新已订正/已回顾/待回顾状态,并形成最后扫雷清单. An agent skill from ZeKaiNie/universal-examprep-skill. Exam Review is an agent skill from ZeKaiNie/universal-examprep-skill.

When should I use Exam Review?

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

How do I install Exam Review in Claude Code?

Run `npx skills add ZeKaiNie/universal-examprep-skill --skill exam-review -a claude-code`. Or copy the skill folder (full/skills/exam-review in ZeKaiNie/universal-examprep-skill) into .claude/skills/exam-review in your project. Claude Code loads it when a task matches its description.

How do I install Exam Review in Codex?

Run `npx skills add ZeKaiNie/universal-examprep-skill --skill exam-review -a codex`. Or copy the skill folder (full/skills/exam-review in ZeKaiNie/universal-examprep-skill) into .agents/skills/exam-review in your project. Codex loads it when a task matches its description.

Can I use Exam Review 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 ZeKaiNie/universal-examprep-skill --skill exam-review -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/exam-review, .gemini/skills/exam-review, .github/skills/exam-review and .opencode/skills/exam-review in your project.

What does Exam Review need to run?

Going by SKILL.md and its folder, Exam Review needs the command-line tools its instructions call (python). Our summary lists: Python 3.

Does Exam Review 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 Exam Review 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. Review the folder before installing.

What licence does Exam Review use?

Exam Review is published under the MIT licence (declared in SKILL.md). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Exam Review use?

About 1.1k tokens (SKILL.md is roughly 4.4k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to Exam Review?

Skills that share tags, products or a category with Exam Review: 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 Exam Review?

ZeKaiNie (a GitHub user) maintains it in ZeKaiNie/universal-examprep-skill, which has 303 GitHub stars. The repository holds 12 skills in this directory. The repository was last updated on September 28, 2026.

Source: ZeKaiNie/universal-examprep-skill on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.