tutor

roundtable02/tutor-skills · updated Apr 8, 2026

MDX-style export adds YAML metadata + attribution linking explainx.ai and this canonical listing URL.

$npx skills add https://github.com/roundtable02/tutor-skills --skill tutor
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summary

Interactive quiz tutor that tracks concept mastery and identifies knowledge gaps.

  • Detects user language and maintains a StudyVault directory with a dashboard and per-area concept tracking files
  • Offers context-aware session types: diagnostic assessment for unmeasured areas, targeted drilling of weak concepts, section selection, or hard-mode review
  • Grades 4-question quizzes per session, maps results to concepts, and updates proficiency badges (🟥 weak through 🟦 mastered) and error not
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
how to use tutor

How to use tutor on Cursor

AI-first code editor with Composer

1

Prerequisites

Before installing skills in Cursor, ensure your development environment meets these requirements:

  • Cursor installed and configured on your development machine
  • Node.js version 16.0+ with npm package manager (verify with node --version)
  • Active project directory or workspace where you want to add tutor
2

Execute installation command

Execute the skills CLI command in your project's root directory to begin installation:

$npx skills add https://github.com/roundtable02/tutor-skills --skill tutor

The skills CLI fetches tutor from GitHub repository roundtable02/tutor-skills and configures it for Cursor.

3

Select Cursor when prompted

The CLI will show a list of available agents. Use arrow keys to navigate and space to select Cursor:

◆ Which agents do you want to install to?
│ ── Universal (.agents/skills) ── always included ────
│ • Amp
│ • Antigravity
│ • Cline
│ • Codex
│ ●Cursor(selected)
│ • Cursor
│ • Windsurf
4

Verify installation

Confirm successful installation by checking the skill directory location:

.cursor/skills/tutor

Reload or restart Cursor to activate tutor. Access the skill through slash commands (e.g., /tutor) or your agent's skill management interface.

Security & Verification Notice

We perform automated surface-level scans (Gen AI Scanner, Socket, Snyk) during installation. These checks detect common vulnerabilities but do not guarantee complete security. Always review skill source code and verify the publisher's reputation before production use.

Skills execute code in your development environment. Always verify the publisher's identity, review recent commits, and test in isolated environments before production deployment.

List & Monetize Your Skill

Submit your Claude Code skill and start earning

GET_STARTED →

Use Cases

User Story & Requirements Generation

Create detailed user stories, acceptance criteria, and feature specs

Example

Generate user stories for 'password reset feature' with acceptance criteria, edge cases, and test scenarios

Reduce spec writing time by 50%, ensure comprehensive coverage

Competitive Analysis

Research competitors, compare features, identify gaps

Example

Analyze 5 competitor products, create feature comparison matrix, suggest differentiation opportunities

Complete competitive research in 2 hours instead of 2 days

Roadmap Prioritization

Evaluate features using frameworks (RICE, ICE, Kano) and create prioritized backlogs

Example

Score 20 feature ideas using RICE framework, generate prioritized roadmap with rationale

Make data-driven prioritization decisions faster

Stakeholder Communication

Draft PRDs, status updates, and stakeholder presentations

Example

Create executive summary of Q3 roadmap, monthly progress report, feature launch announcement

Save 3-5 hours/week on communication overhead

Implementation Guide

Prerequisites

  • Claude Desktop or compatible AI client
  • Access to product documentation and roadmap tools (Jira, Notion, etc.)
  • Understanding of product management frameworks (RICE, Jobs-to-be-Done, etc.)
  • Stakeholder contact information and communication channels

Time Estimate

30-60 minutes to see productivity improvements

Installation Steps

  1. 1.Install product management skill
  2. 2.Start with user story generation for known feature
  3. 3.Progress to competitive analysis: research 2-3 competitors
  4. 4.Use for roadmap prioritization: apply RICE/ICE scoring
  5. 5.Draft stakeholder communications and refine based on feedback
  6. 6.Build template library for recurring PM tasks
  7. 7.Share effective prompts with product team

Common Pitfalls

  • Not validating competitive research—verify facts before sharing
  • Accepting user stories without involving engineering team
  • Over-relying on frameworks without qualitative judgment
  • Not customizing outputs to company culture and communication style
  • Skipping stakeholder validation of generated requirements

Best Practices

✓ Do

  • +Validate research and competitive analysis with real data
  • +Collaborate with engineering when generating technical requirements
  • +Customize frameworks and templates to your company context
  • +Use skill for first drafts, refine with stakeholder input
  • +Document successful prompt patterns for PM tasks
  • +Combine AI efficiency with human judgment and intuition

✗ Don't

  • Don't publish competitive analysis without fact-checking
  • Don't finalize user stories without engineering review
  • Don't make prioritization decisions solely on AI scoring
  • Don't skip customer validation of generated requirements
  • Don't ignore company-specific context and culture

💡 Pro Tips

  • Provide context: company goals, constraints, customer feedback
  • Ask for alternatives: 'Show 3 ways to prioritize this roadmap'
  • Request stakeholder-specific formatting: 'Executive summary vs. engineering spec'
  • Use skill for 70% generation + 30% customization to company needs

When to Use This

✓ Use When

Use for user story writing, competitive research, roadmap prioritization, stakeholder communication, and PRD drafting. Best for reducing repetitive documentation and research work.

✗ Avoid When

Avoid for strategic product vision (requires deep customer empathy), pricing decisions (needs market and financial expertise), or when face-to-face customer discovery is more valuable than speed.

Learning Path

  1. 1Basic: user stories, feature specs, status updates
  2. 2Intermediate: competitive analysis, prioritization frameworks, PRDs
  3. 3Advanced: product strategy, go-to-market planning, OKR setting
  4. 4Expert: product vision, market positioning, business model innovation

Discussion

Product Hunt–style comments (not star reviews)
  • No comments yet — start the thread.
general reviews

Ratings

4.871 reviews
  • Henry Jain· Dec 28, 2024

    We added tutor from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.

  • Henry Diallo· Dec 28, 2024

    Solid pick for teams standardizing on skills: tutor is focused, and the summary matches what you get after install.

  • Pratham Ware· Dec 16, 2024

    tutor reduced setup friction for our internal harness; good balance of opinion and flexibility.

  • Anika Gonzalez· Dec 12, 2024

    Useful defaults in tutor — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.

  • Arjun Dixit· Dec 4, 2024

    tutor reduced setup friction for our internal harness; good balance of opinion and flexibility.

  • Charlotte Gupta· Nov 23, 2024

    I recommend tutor for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.

  • Anaya Gonzalez· Nov 19, 2024

    Solid pick for teams standardizing on skills: tutor is focused, and the summary matches what you get after install.

  • Ama Zhang· Nov 19, 2024

    We added tutor from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.

  • Sakshi Patil· Nov 7, 2024

    I recommend tutor for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.

  • Noah Perez· Nov 3, 2024

    Registry listing for tutor matched our evaluation — installs cleanly and behaves as described in the markdown.

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