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Tutor

OrganizationPopular
bevibing
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".

Overview

Publisherbevibing
Repositorytutor-skills
Skill nametutor
Stars
1.3K
Forks
124
Bundled files
1
LicenseMIT
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • 1 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by bevibing on GitHub. Read the source before you install it.

Installation

Install the Tutor AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/bevibing/tutor-skills/tree/main/skills/tutor
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/bevibing/tutor-skills.git /tmp/tutor-skills
mkdir -p .claude/skills
cp -r /tmp/tutor-skills/skills/tutor .claude/skills/tutor
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Tutor in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Tutor on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Tutor is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

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:

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

Error notes format (only for wrong answers):

markdown
### 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:

markdown
# 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:

markdown
# {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

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Tutor AI skill do?

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".

Why use Tutor on TypingMind?

Because you install it once and use it with any model. Tutor is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Tutor in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/bevibing/tutor-skills/tree/main/skills/tutor. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Tutor?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Tutor?

As many as you like. As long as a model supports skills, you can use Tutor with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Tutor AI skill free?

Yes. It is published on GitHub by bevibing under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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