Interactive quiz tutor that tracks concept mastery and identifies knowledge gaps.
Works with
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
AI-first code editor with Composer
Before installing skills in Cursor, ensure your development environment meets these requirements:
node --versiontutorExecute the skills CLI command in your project's root directory to begin installation:
Fetches tutor from roundtable02/tutor-skills and configures it for Cursor.
The CLI shows a list of agents. Use arrow keys and space to select Cursor:
Confirm successful installation by checking the skill directory location:
Restart Cursor to activate tutor. Access via /tutor in your agent's command palette.
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 environment. Always review source, verify the publisher, and test in isolation before production.
Submit your Claude Code skill and start earning
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
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
Evaluate features using frameworks (RICE, ICE, Kano) and create prioritized backlogs
Example
Score 20 feature ideas using RICE framework, generate prioritized roadmap with rationale
0
total installs
0
this week
636
GitHub stars
0
upvotes
Run in your terminal
0
installs
0
this week
636
stars
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.
StudyVault/
├── *dashboard* ← Compact overview: proficiency table + stats
└── concepts/
├── {area-name}.md ← Per-area concept tracking (attempts, status, error notes)
└── ...
Detect user's language from their message → {LANG}. All output and file content in {LANG}.
**/StudyVault/ in project**/StudyVault/*dashboard* to find dashboardIf no StudyVault exists, inform user and stop.
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:
Present these as an AskUserQuestion with header "Session" and concise descriptions showing which areas each option targets. The user MUST select before proceeding.
concepts/{area}.md to find 🔴 unresolved concepts — rephrase these in new contexts (don't repeat the same question)references/quiz-rules.mdCRITICAL: Read references/quiz-rules.md before crafting ANY question. Zero hints allowed.
Use AskUserQuestion:
concepts/{area}.md)For each question answered:
### 오답 메모 (or localized equivalent)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
Dashboard stays compact — no session logs, no per-question details.
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**: -
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)
references/quiz-rules.md before creating questionsMake data-driven prioritization decisions faster
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
Prerequisites
Time Estimate
30-60 minutes to see productivity improvements
Steps
Common Pitfalls
✓ Do
✗ Don't
💡 Pro Tips
✓ 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.
mattpocock/skills
parcadei/continuous-claude-v3
cursor/plugins
ailabs-393/ai-labs-claude-skills
pproenca/dot-skills
ailabs-393/ai-labs-claude-skills
We added tutor from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.
Solid pick for teams standardizing on skills: tutor is focused, and the summary matches what you get after install.
tutor reduced setup friction for our internal harness; good balance of opinion and flexibility.
Useful defaults in tutor — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.
tutor reduced setup friction for our internal harness; good balance of opinion and flexibility.
I recommend tutor for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.
Solid pick for teams standardizing on skills: tutor is focused, and the summary matches what you get after install.
We added tutor from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.
I recommend tutor for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.
Registry listing for tutor matched our evaluation — installs cleanly and behaves as described in the markdown.
showing 1-10 of 71