tutor

Interactive quiz tutor for Obsidian StudyVault learning. Use when the user wants to: (1) Take a diagnostic assessment of their knowledge, (2) Study or review specific sections/topics, (3) Drill weak areas identified in previous sessions, (4) Check their learning progress or dashboard, or says things like "quiz me", "test me", "let's study", "/tutor", "학습", "퀴즈", "평가".

Safety Notice

This listing is imported from skills.sh public index metadata. Review upstream SKILL.md and repository scripts before running.

Copy this and send it to your AI assistant to learn

Install skill "tutor" with this command: npx skills add roundtable02/tutor-skills/roundtable02-tutor-skills-tutor

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

Source Transparency

This detail page is rendered from real SKILL.md content. Trust labels are metadata-based hints, not a safety guarantee.

Related Skills

Related by shared tags or category signals.

General

tutor-setup

No summary provided by upstream source.

Repository SourceNeeds Review
Research

AI Learning Tutor

AI学习私教 - 搭知识库、规划路径、出题练习、批改讲解、总结输出。学练查写闭环,从零学成高手。支持任意学科:专业、考证、编程、论文等。

Registry SourceRecently Updated
1070Profile unavailable
Coding

Code Mentor

Comprehensive AI programming tutor for all levels. Teaches programming through interactive lessons, code review, debugging guidance, algorithm practice, project mentoring, and design pattern exploration. Use when the user wants to: learn a programming language, debug code, understand algorithms, review their code, learn design patterns, practice data structures, prepare for coding interviews, understand best practices, build projects, or get help with homework. Supports Python and JavaScript.

Registry SourceRecently Updated
5.9K2Profile unavailable
General

Language Learning Tutor

AI language tutor for learning ANY language through conversation, vocab drills, grammar lessons, flashcards, and immersive practice. Use when the user wants to: learn a new language, practice vocabulary, study grammar, do flashcard drills, translate phrases, practice conversation, prepare for travel, learn slang/idioms, or improve pronunciation. Supports ALL languages including Spanish, French, German, Japanese, Chinese (Mandarin/Cantonese), Korean, Arabic, Hindi, Bengali/Bangla, Portuguese, Russian, Italian, Turkish, Vietnamese, Thai, Swahili, Hebrew, Polish, Dutch, Greek, and 100+ more.

Registry SourceRecently Updated
7.3K21Profile unavailable