tutor▌
roundtable02/tutor-skills · updated Apr 8, 2026
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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
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
- Glob
**/StudyVault/in project - List section directories
- Glob
**/StudyVault/*dashboard*to find dashboard - If found, read it. Preserve existing file path regardless of language.
- 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:
- If unmeasured areas (⬜) exist → include "Diagnostic" option targeting those areas
- If weak areas (🟥/🟨) exist → include "Drill weak areas" option naming the weakest area(s)
- Always include "Choose a section" option so the user can pick any area
- 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
- Read markdown files in target section(s)
- If drilling weak area: also read
concepts/{area}.mdto find 🔴 unresolved concepts — rephrase these in new contexts (don't repeat the same question) - 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
- Show results table (question / correct answer / user answer / result)
- Wrong answers: concise explanation
- 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.mdbefore 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 on Cursor
AI-first code editor with Composer
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
Execute installation command
Execute the skills CLI command in your project's root directory to begin installation:
The skills CLI fetches tutor from GitHub repository roundtable02/tutor-skills and configures it for Cursor.
Select Cursor when prompted
The CLI will show a list of available agents. Use arrow keys to navigate and space to select Cursor:
Verify installation
Confirm successful installation by checking the skill directory location:
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
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.Install product management skill
- 2.Start with user story generation for known feature
- 3.Progress to competitive analysis: research 2-3 competitors
- 4.Use for roadmap prioritization: apply RICE/ICE scoring
- 5.Draft stakeholder communications and refine based on feedback
- 6.Build template library for recurring PM tasks
- 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▌
- 1Basic: user stories, feature specs, status updates
- 2Intermediate: competitive analysis, prioritization frameworks, PRDs
- 3Advanced: product strategy, go-to-market planning, OKR setting
- 4Expert: product vision, market positioning, business model innovation
Discussion
Product Hunt–style comments (not star reviews)- No comments yet — start the thread.
Ratings
4.8★★★★★71 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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