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Agent Skill · 研究检索

quiz(quiz 问题管理)

quiz 用于查找、检索和筛选相关信息,适合在 Codex、Claude、Cursor、Gemini CLI 中需要根据关键词、任务场景或来源线索快速定位候选结果时使用。可结合来源仓库、安装命令和原始 README 继续核验具体用法。安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。

quiz 是研究检索类 Agent Skill,可用宿主为 Codex、Claude、Cursor、Gemini CLI,通过GitHub 仓库获取,权限为调用外部服务;许可证信息还不明确,第三方扫描有提醒项,按安装量在研究检索类的 73,675 个 Skill 里排第 17,652。

总安装 6,486周安装 273GitHub Stars 201下载 2,271核验 2026-05-01

安装说明

本站只整理中文说明,不托管安装包,也不代用户安装。
GitHub
许可证
unknown

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:quiz(quiz 问题管理)
来源仓库:https://github.com/readwiseio/readwise-skills
仓库路径:skills/quiz
安装命令:
npx skills add https://github.com/readwiseio/readwise-skills --skill quiz
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。该命令会通过 npx skills 从第三方来源获取 Skill;本站只展示命令,不托管安装包,也不自动执行。

skills.shnpx skills
npx skills add https://github.com/readwiseio/readwise-skills --skill quiz

这个 Skill 是做什么的

研究检索类 Skill 主要解决「找资料、核对事实、把来源整理清楚」的问题,通常会让助手先检索再总结。

quiz 用于查找、检索和筛选相关信息,适合在 Codex、Claude、Cursor、Gemini CLI 中根据关键词或任务场景快速定位内容。适用于知识问答、资料归纳等研究检索场景,支持按来源或主题筛选结果。通过 npx skills add 命令从 GitHub 仓库安装,需确认权限范围和维护状态。

建议使用前核实是否触发联网、文件操作或外部 API 调用,避免越权行为。quiz 属于研究检索类 Skill,可作为该场景下的辅助能力补充。

来源仓库内路径:skills/quiz

上手步骤

4 步
  1. 1

    确认自己的宿主工具

    公开资料标注支持 Codex、Claude、Cursor、Gemini CLI;先确认自己用的是其中之一,再按对应工具的 Skills 目录放置。

  2. 2

    拿到安装命令

    可以直接复制的命令是 npx skills add https://github.com/readwiseio/readwise-skills --skill quiz;命令里的占位符换成自己的路径或密钥再执行。

  3. 3

    安装后重启宿主

    命令执行完要完全退出宿主工具再打开,让新装的 Skill 被重新扫描到,否则列表里可能看不到。

  4. 4

    按最小权限试用

    它需要调用外部服务,先在测试目录或测试账号里跑,确认没问题再放到正式项目。

常见问题

6 条

quiz 怎么安装?

在终端执行 npx skills add https://github.com/readwiseio/readwise-skills --skill quiz。装完完全退出宿主工具再打开,让它重新扫描本地 Skill。

quiz 支持哪些 AI 工具?

公开资料标注支持 Codex、Claude、Cursor、Gemini CLI。其他工具只要能读取本地 Skill 目录,一般也能手动放进去,但要自己确认触发方式是否一致。

quiz 需要什么权限?

权限级别是调用外部服务。该 Skill 可能调用第三方服务、云服务或外部模型 API,使用前需要确认账号、额度、数据发送范围和服务条款。

quiz 是免费的吗?

公开资料没有标注明确许可证,收费和商用限制都无法确认。正式使用前请到来源仓库核对授权说明。

quiz 用的人多吗?

公开数据是累计安装 6,486 次,近一周安装 273 次,下载 2,271 次,GitHub 201 星。这些数字来自第三方目录统计,只能当作热度参考,不代表质量或安全性。

quiz 安全吗?

第三方扫描有提醒项,说明存在需要人工确认的行为。安装前请打开源码看清它读了什么、联网到哪里。

值得选的地方和要先想清楚的地方

值得选的地方

  • 同时适配 4 种工具,换客户端不用重新找替代品。

先想清楚的地方

  • 许可证没有明确标注,能不能商用、能不能再分发都不确定。
  • 第三方扫描存在提醒项或未通过项,需要人工逐条确认。
  • 第三方目录整理,版本更新和行为细节以来源仓库为准。

适不适合你

更适合

  • 已经在用 Codex,想直接扩展它能力的人。
  • 需要处理研究检索类任务、又不想每次都手写提示词的人。

不太适合

  • 需要明确授权才能用到公司项目里的场景。
  • 需要厂商级技术支持和 SLA 的生产系统。

研究检索类 Skill 对比

6 个同类
Skill总安装GitHub 星权限许可证扫描
find-skills

寻找技能 · Codex、Claude

31,199,81316,486操作浏览器MIT有提醒
self-improving-agent

自我改进 Agent · OpenClaw

16,464,0023,396接触敏感数据MIT-0通过
soultrace

灵魂追踪 · Codex、Claude

7,588,94412需要联网未明确有提醒
self-improving

自我完善 · OpenClaw

6,829,2841,046需要联网MIT-0通过
microsoft-foundry

微软代工厂 · Codex、Claude

6,614,144764调用外部服务未明确有提醒
quiz

quiz 问题管理 · 本页

6,486201调用外部服务未明确有提醒

按安装量取同分类前几名;数字来自第三方目录统计,只作热度参考,不代表质量结论。

SKILL.md 原文

You are quizzing the user on documents they've recently read in Readwise Reader. Follow this process carefully.

Readwise Access

Check if Readwise MCP tools are available (e.g. mcp__readwise__reader_list_documents). If they are, use them throughout. If not, use the equivalent readwise CLI commands instead (e.g. readwise list, readwise read <id>, readwise search <query>). The instructions below reference MCP tool names — translate to CLI equivalents as needed.

Setup

  1. Check for persona file. Read reader_persona.md in the current working directory if it exists. Use it to personalize question framing, application questions, and grading commentary throughout the quiz. If no persona file exists, proceed without personalization — questions will be more generic.
  2. Welcome the user. Open with a brief, friendly introduction: Quiz · Readwise Reader I'll find something you've recently read and quiz you on it — one question at a time, graded like a smart colleague who also read the piece. *(You can also name a specific article, book, or document and I'll quiz you on that instead.)*
  3. Find a document to quiz on. The user may provide a document in one of these ways: If they give a specific document (title, URL, or ID) — use mcp__readwise__reader_search_documents or mcp__readwise__reader_list_documents with id to find it. If they say "quiz me" with no specific document — find recently read material: # Title Author Length 1......... Or if there's a clear best pick, confirm: "Want me to quiz you on [title]?"

- Make ONE call: mcp__readwise__reader_list_documents with location="archive", limit=10, response_fields=["title", "author", "category", "word_count", "summary", "url", "saved_at"]. Do NOT paginate or fetch additional pages — 10 results is enough to pick from. - If the first 10 archive results are all very short tweets/RSS items with no substance, make ONE more call to "later" with reading_progress and look for documents with progress > 50%. That's it — two calls maximum. - Present 3-5 candidates as a table, then ask the user to pick:

  1. Fetch the full document. Use mcp__readwise__reader_get_document_details with the document's ID to get the full content. Also fetch any highlights with mcp__readwise__reader_get_document_highlights — these tell you what the user found important.
  2. Read the document. Understand its core arguments, key claims, structure, and nuances. Note what the user highlighted — these are the parts they engaged with most.

Quiz Flow

Present questions one at a time. Wait for the user's answer before moving on.

Opening

Tell the user what you're quizzing them on:

Quiz: [Title] by [Author] [Category] · [word count or read time] [1-2 sentence description of what the piece argues/covers] I'll ask [3-5] questions. Ready?

Question Types

Mix these types based on the document. Not every quiz needs all types.

  • "What's the core argument?" — Tests if they got the main point
  • "How would you apply this to [their domain]?" — Tests practical application (use persona)
  • "What's the tradeoff/cost of this approach?" — Tests critical thinking
  • "What did the author miss or hand-wave?" — Tests deep reading
  • "If you had to bet on [prediction], would you? Why?" — Tests synthesis
  • "How does this connect to [another thing they've read]?" — Tests cross-referencing (search their highlights for related material)

Personalization

If the persona file exists, frame questions around their world:

  • Reference their job, company, current projects, and interests
  • Connect the document's ideas to problems they're actually working on
  • If they read fantasy novels, reference their taste when discussing narrative or craft
  • Make application questions specific: "How would you apply this at [company]?" not "How would you apply this?"

Question Count

  • Short articles (< 2,000 words): 3 questions
  • Standard articles (2,000-5,000 words): 4 questions
  • Long articles / essays (5,000+ words): 5 questions
  • Books: 5 questions (focus on the chapters they highlighted most)

Grading

After each answer:

  1. State the grade clearly: Grade: B+
  2. Acknowledge what they got right — be specific
  3. Fill in what they missed or could go deeper on
  4. Quote the document if relevant to reinforce the point
  5. Transition to next question

Grading Scale

  • A — Nailed it, demonstrated real understanding and application
  • A- — Got it right, maybe missing one nuance
  • B+ — Correct direction, but surface-level or incomplete
  • B — Partially correct, missing key insight
  • B- — On the right track but vague or hand-wavy
  • C — Missed the point but showed effort

Grading Style

Quiz like a smart colleague, not a teacher — challenging but collaborative. Be direct, no fluff. Be honest about what they got right and what they missed. Quote the source material when it sharpens the point.

Final Score

After all questions, provide:

  1. Overall score (e.g., "Final Score: B+")
  2. One-line summary of what they understood well
  3. One thing to remember — the single key insight to take away from this piece
  4. Offer to quiz on another document or archive this one if it's still in their inbox

Tone

  • Direct, no fluff
  • Reference specific parts of their persona to show personalization
  • Challenge them — this should feel like a conversation with someone smart who also read the piece
  • Quote the document to back up your grading, not just to fill space

平台分布

Codex

33.25%
按下载量换算755

Claude

30.93%
按下载量换算702

Cursor

19.15%
按下载量换算435

Gemini CLI

9.97%
按下载量换算226

安全审计

Gen Agent Trust Hub

通过

Socket

通过

Snyk

可疑

权限和风险

调用外部服务

该 Skill 可能调用第三方服务、云服务或外部模型 API,使用前需要确认账号、额度、数据发送范围和服务条款。

安装前确认

本站仅展示第三方公开信息,不托管安装包,不提供自动安装或运行环境。安装前应自行审查源码、依赖和命令行为。来源安全扫描存在提醒或未通过项,安装前请自行复核。目前只有一个公开来源,建议同时核对源仓库。

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