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tutortutor 问题管理

Agent Skill

tutor 用于记录任务执行中的错误、用户纠正、经验和能力缺口,适合在 Codex、Claude、Cursor、Gemini CLI 中希望让 Agent 持续沉淀问题、修正和最佳实践时使用。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。

总安装

29,035

周安装

1,207

GitHub Stars

810

下载量

9,949
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安装说明

本站只整理中文说明和来源信息,不托管安装包,也不代用户安装。

GitHub

来源数

2

许可证

unknown

最后核验

2026-05-01

来源状态

来源可访问

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:tutor(tutor 问题管理)
来源仓库:https://github.com/roundtable02/tutor-skills
仓库路径:skills/tutor
安装命令:
npx skills add https://github.com/roundtable02/tutor-skills --skill tutor
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/roundtable02/tutor-skills --skill tutor

简介

互动测验导师可跟踪概念掌握情况并确定知识差距。

  • 检测用户语言并维护带有仪表板和按区域概念跟踪文件的 StudyVault 目录
  • 提供上下文感知会话类型:对未测量区域的诊断评估、对薄弱概念的有针对性的钻探、部分选择或硬模式审查
  • 对每个会话的 4 个问题测验进行评分,将结果映射到概念,并更新熟练程度徽章(🟥 弱到 🟦 掌握)和错误注释
  • 针对薄弱环节重新安排问题以避免重复,并通过跟踪尝试、正确答案和未解决的概念来建立学习历史

SKILL.md

Tutor Skill

Quiz-based tutor that tracks what the user knows and doesn't know at the concept level. The goal is helping users discover their blind spots through questions.

File Structure

StudyVault/
├── *dashboard*              ← Compact overview: proficiency table + stats
└── concepts/
    ├── {area-name}.md       ← Per-area concept tracking (attempts, status, error notes)
    └── ...
  • Dashboard: Only aggregated numbers. Links to concept files. Stays small forever.
  • Concept files: One per area. Tracks each concept with attempts, correct count, date, status, and error notes. Grows proportionally to unique concepts tested (bounded).

Workflow

Phase 0: Detect Language

Detect user's language from their message → {LANG}. All output and file content in {LANG}.

Phase 1: Discover Vault

  1. Glob **/StudyVault/ in project
  2. List section directories
  3. Glob **/StudyVault/*dashboard* to find dashboard
  4. If found, read it. Preserve existing file path regardless of language.
  5. If not found, create from template (see Dashboard Template below)

If no StudyVault exists, inform user and stop.

Phase 2: Ask Session Type

MANDATORY: Use AskUserQuestion to let the user choose what to do. Analyze the dashboard to build context-aware options, then present them.

Read the dashboard proficiency table and build options based on current state:

  1. If unmeasured areas (⬜) exist → include "Diagnostic" option targeting those areas
  2. If weak areas (🟥/🟨) exist → include "Drill weak areas" option naming the weakest area(s)
  3. Always include "Choose a section" option so the user can pick any area
  4. If all areas are 🟩/🟦 → include "Hard-mode review" option

Present these as an AskUserQuestion with header "Session" and concise descriptions showing which areas each option targets. The user MUST select before proceeding.

Phase 3: Build Questions

  1. Read markdown files in target section(s)
  2. If drilling weak area: also read concepts/{area}.md to find 🔴 unresolved concepts — rephrase these in new contexts (don't repeat the same question)
  3. Craft exactly 4 questions following references/quiz-rules.md

CRITICAL: Read references/quiz-rules.md before crafting ANY question. Zero hints allowed.

Phase 4: Present Quiz

Use AskUserQuestion:

  • 4 questions, 4 options each, single-select
  • Header: "Q1. Topic" (max 12 chars)
  • Descriptions: neutral, no hints

Phase 5: Grade & Explain

  1. Show results table (question / correct answer / user answer / result)
  2. Wrong answers: concise explanation
  3. Map each question to its area

Phase 6: Update Files

1. Update concept file (concepts/{area}.md)

For each question answered:

  • New concept: Add row to table + if wrong, add error note under ### 오답 메모 (or localized equivalent)
  • Existing 🔴 concept answered correctly: Increment attempts & correct, change status to 🟢, keep error note (learning history)
  • Existing 🟢 concept answered wrong again: Increment attempts, change status back to 🔴, update error note

Table format:

| Concept | Attempts | Correct | Last Tested | Status |
|---------|----------|---------|-------------|--------|
| concept name | 2 | 1 | 2026-02-24 | 🔴 |

Error notes format (only for wrong answers):

### Error Notes

**concept name**
- Confusion: what the user mixed up
- Key point: the correct understanding

2. Update dashboard

  • Recalculate per-area stats from concept files (sum attempts/correct across all concepts in that area)
  • Update proficiency badges: 🟥 0-39% · 🟨 40-69% · 🟩 70-89% · 🟦 90-100% · ⬜ no data
  • Update stats: total questions, cumulative rate, unresolved/resolved counts, weakest/strongest

Dashboard stays compact — no session logs, no per-question details.

Dashboard Template

Create when no dashboard exists. Filename localized to {LANG}. Example in English:

# Learning Dashboard

> Concept-based metacognition tracking. See linked files for details.

---

## Proficiency by Area

| Area | Correct | Wrong | Rate | Level | Details |
|------|---------|-------|------|-------|---------|
(one row per section, last column = [[concepts/{area}]] link)
| **Total** | **0** | **0** | **-** | ⬜ Unmeasured | |

> 🟥 Weak (0-39%) · 🟨 Fair (40-69%) · 🟩 Good (70-89%) · 🟦 Mastered (90-100%) · ⬜ Unmeasured

---

## Stats

- **Total Questions**: 0
- **Cumulative Rate**: -
- **Unresolved Concepts**: 0
- **Resolved Concepts**: 0
- **Weakest Area**: -
- **Strongest Area**: -

Concept File Template

Create per area when first question is asked. Example:

# {Area Name} — Concept Tracker

| Concept | Attempts | Correct | Last Tested | Status |
|---------|----------|---------|-------------|--------|

### Error Notes

(added as concepts are missed)

Important Reminders

  • ALWAYS read references/quiz-rules.md before creating questions
  • NEVER include hints in option labels or descriptions
  • NEVER use "(Recommended)" on any option
  • Randomize correct answer position
  • After grading, ALWAYS update both concept file AND dashboard
  • Communicate in user's language

适合场景

01

用户想查找某类 Agent Skill 时

02

需要根据任务场景推荐可安装能力包时

03

需要对比不同来源的安装命令和来源信息时

能力概览

能力 1

按任务关键词查找相关 Skills

能力 2

展示可复制的安装命令

能力 3

保留来源站点、仓库和原始说明,方便继续核验

能力 4

展示第三方安全扫描或审计结果

安装后应在对应宿主中按原始 README 的触发条件使用;具体调用方式请以来源页面和 README 为准。

平台分布

Codex

38.13%
按下载量换算3,794

Claude

29.59%
按下载量换算2,944

Cursor

19.24%
按下载量换算1,914

Gemini CLI

9.36%
按下载量换算931

安全审计

Gen Agent Trust Hub

通过

Socket

通过

Snyk

通过

权限和风险

只读

该 Skill 主要提供规则、说明或参考内容,本身偏只读;真正读写文件、联网或执行命令仍取决于宿主 Agent 的任务。

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。当前只有一个来源,正式发布前建议补源仓库或其他目录站核验。

来源信息

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