Tutor Skills is a pair of Claude Code skills that turns documents or software codebases into linked Obsidian study vaults and then quizzes users on the material. Learners use it to create notes, dashboards, practice questions, and interactive review sessions from knowledge sources. The catalogue skills are the project's own study-vault and quiz workflow.
Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add bevibing/tutor-skills --skill tutor-setupgit clone --depth 1 https://github.com/bevibing/tutor-skillsWrote 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/bevibing/tutor-skills/tutor-setup)<a href="https://agentmods.dev/skills/bevibing/tutor-skills/tutor-setup"><img src="https://agentmods.dev/badge/skills/bevibing/tutor-skills/tutor-setup/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/bevibing/tutor-skills/tutor-setup"><img src="https://agentmods.dev/badge/skills/bevibing/tutor-skills/tutor-setup.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- Socket pass
- Snyk warn
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 | $0.00066 | $0.01855 |
| Opus 5.5 | $0.00026 | $0.00742 |
| Sonnet 5.5 | $0.00013 | $0.00371 |
| Haiku 4.5 | $0.00007 | $0.00186 |
Grade A, and why
tutor-setup 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 1mo 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.
Copies of this mod
1 near-identical copy found in the catalogue:
- tutor-setup — 100% identical, 0 lines differ
How it starts
The opening of the file, as written. The whole thing — 151 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Tutor Setup — Knowledge to Obsidian StudyVault
CWD Boundary Rule (ALL MODES)
NEVER access files outside the current working directory (CWD). All source scanning, reading, and vault output MUST stay within CWD and its subdirectories. If the user provides an external path, ask them to copy the files into CWD first.
Mode Detection
On invocation, detect mode automatically:
- Check for project markers in CWD:
package.json,pom.xml,build.gradle,Cargo.toml,go.mod,Makefile,*.sln,pyproject.toml,setup.py,Gemfile
- If any marker found → Codebase Mode
- If no marker found → Document Mode
- Tie-break: If
.git/is the sole indicator and no source code files (*.ts,*.py,*.java,*.go,*.rs, etc.) exist, default to Document Mode. - Announce detected mode and ask user to confirm or override.
Document Mode
Transforms knowledge sources (PDF, text, web, epub) into study notes. Templates: templates.md
Phase D1: Source Discovery & Extraction
- Auto-scan CWD for
**/*.pdf,**/*.txt,**/*.md,**/*.html,**/*.epub(excludenode_modules/,.git/,dist/,build/,StudyVault/). Present for user confirmation. - Extract text (MANDATORY tools):
- PDF →
pdftotextCLI ONLY (run via Bash tool). NEVER use the Read tool directly on PDF files — it renders pages as images and wastes 10-50x more tokens. Convert to.txtfirst, then Read the.txtfile.pdftotext "source.pdf" "/tmp/source.txt" - If
pdftotextis not installed, install it first:brew install poppler(macOS) orapt-get install poppler-utils(Linux). - URL → WebFetch
- Other formats (
.md,.txt,.html) → Read directly.
- PDF →
- Read extracted
.txtfiles — understand scope, structure, depth. Work exclusively from the converted text, never from the raw PDF. - Source Content Mapping (MANDATORY for multi-file sources):
- Read cover page + TOC + 3+ sample pages from middle/end for EVERY source file
- NEVER assume content from filename — file numbering often ≠ chapter numbering
- Build verified mapping:
{ source_file → actual_topics → page_ranges } - Flag non-academic files and missing sources
- Present mapping to user for verification before proceeding
What ships with it
4 files 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.
- 1mo ago First seen · 151 lines · 66 tokens per session scan A 69bf456cc1d8
tutor-setup is a skill published in the GitHub repository bevibing/tutor-skills (1,354 stars, last pushed 7mo ago), licensed MIT. It adds 66 tokens to every session and 1,855 once invoked, about $0.0003 per session on Opus 5.5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
Other skills, from other repositories
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iflytek-pdf-image-ocr
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PDF Processing Pro
A PDF-processing workflow for handling forms, extracting tables, and using OCR to turn scanned text into searchable data. It also performs automated data checks using built-in scripts.
law-to-markdown
A legal-document conversion skill for turning PDF, Word, or plain-text regulations into structured Markdown. Markdown is a text format that uses simple symbols for headings and lists.
Summarize document text and identify its main claims, evidence, and unanswered questions.