Borrowing it
Nothing to install: this file belongs to levi-qiao/obsidian-llm-wiki. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/levi-qiao/obsidian-llm-wiki/main/.claude/skills/tutor/SKILL.mdgit clone --depth 1 https://github.com/levi-qiao/obsidian-llm-wikiWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/levi-qiao/obsidian-llm-wiki/tutor)<a href="https://agentmods.dev/skills/levi-qiao/obsidian-llm-wiki/tutor"><img src="https://agentmods.dev/badge/skills/levi-qiao/obsidian-llm-wiki/tutor/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/levi-qiao/obsidian-llm-wiki/tutor"><img src="https://agentmods.dev/badge/skills/levi-qiao/obsidian-llm-wiki/tutor.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00097 | $0.01403 |
| Opus 5 | $0.00048 | $0.00701 |
| Sonnet 5 | $0.00019 | $0.00281 |
| Haiku 4.5 | $0.00010 | $0.00140 |
Grade A, and why
tutor scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 12d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
This is a copy
100% identical to tutor — 0 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 167 lines — stays where its author put it; the contents beside it link to each section on GitHub.
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
What ships with it
1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 12d ago First seen · 167 lines · 97 tokens per session scan A 94bd0aec3fbb
tutor is a skill published in the GitHub repository levi-qiao/obsidian-llm-wiki (10 stars, last pushed 29d ago), licensed MIT. It adds 97 tokens to every session and 1,403 once invoked, about $0.0005 per session on Opus 5. A static security scan graded it A with 0 findings. It is 100% identical to tutor, differing in 0 lines, and is treated as a copy.
Other skills, from other repositories
llm-wiki
Build and maintain a persistent, interlinked Obsidian-compatible markdown wiki using Karpathy's LLM Wiki pattern. Extension-backed with auto-generated metadata, guardrails, and 14 custom tools (+3 opt-in agent-trajectory tools).
lecture-to-notes
A workflow that turns lecture or conference recordings into organised notes using local transcription and slide extraction. It accepts video and audio files, including MOV, MP4, M4A, MP3, and WAV.
textbook-to-md
Convert PDF/EPUB textbooks to searchable markdown files for an AI agent's own reference. Use this skill whenever: (1) the user asks to convert a textbook/PDF chapter to markdown, (2) you need to search textbook content and no markdown version exists yet, (3) batch-converting a set of reference books into a knowledge…
cognitive-compile
Use when source material must be transformed into a compact, evidence-aware model for learning, decisions, or an Obsidian concept note.
kb-lint
Health check for the PARA Knowledge Base. Detects orphan documents, broken links, index drift, tag issues, and stale content. Run periodically or as part of weekly review.
kb-index
Update Knowledge Base indexes. Smart mode detects changes and updates only what's needed. Full rebuild available with --full flag. Use after adding/moving documents or when indexes feel stale.