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Deeptutor

作者 tanjinlimkelvin-dot · GitHub ↗ · v1.2.0 · MIT-0
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在 OpenClaw 中安装
/install deeptutor
功能描述
A personalized content-driven deep reading tutor. Original-text-first, chapter-level understanding, close reading teacher + strategist hybrid. Auto-saves to...
使用说明 (SKILL.md)

DeepTutor

A personalized, content-driven deep reading tutor. Reads books chapter-by-chapter from EPUB, writes insight-driven deepdives, and auto-saves to Obsidian.

What it does

  • Reads from EPUB — extracts original chapter text directly from the book file
  • Content-driven deepdives — explains what each chapter is really doing, not just summarizing
  • Auto-saves to Obsidian — every deepdive is saved with navigation links
  • Quiz optional — generate comprehension checks after each chapter

Installation

Option 1: ClawHub (recommended)

clawhub install deeptutor

Or install a specific version:

clawhub install [email protected]

Option 2: Manual

Clone this repo to your OpenClaw skills folder:

git clone \x3Crepo-url> /data/workspace/skills/skills/deeptutor
# or
cp -r deeptutor /path/to/your/skills/folder/

Quick Start

From OpenClaw

Just invoke by name in your conversation:

deeptutor,读 Chapter 4

Or more explicitly:

用 deeptutor 带我读 Chapter 4

Subagent execution

If spawning a subagent to read a book:

Use deeptutor to read Chapter 3 of Supercommunicators from the EPUB, write a deepdive, and save to Obsidian.

The skill will:

  1. List chapters from the EPUB
  2. Extract the requested chapter's original text
  3. Write a content-driven deepdive
  4. Save to Obsidian automatically

Requirements

  • OpenClaw environment
  • EPUB file of the book to read
  • Obsidian vault at /data/workspace/obsidian-vault/ (or adjust the save script path)

SKILL.md — Execution Instructions

Treat yourself as a close reading teacher + strategist + reading partner — not a summarizer, not a template-filler.

The goal isn't to finish the content. It's to help the user:

  • Read and understand the author's actual intent
  • Remember what matters and why
  • Articulate it in their own words
  • Apply it — but only after the original text is clear

The Most Important Rule

Content drives structure. Structure doesn't drive content.

Don't sacrifice the authenticity of the content to make the output look neat. Some chapters deserve deep dissection. Some are short bridges. Let the chapter itself decide.

Anti-generic rule: If the deepdive could be pasted under any other nonfiction chapter with only minor edits, rewrite it. Every deepdive must feel chapter-specific.


What a strong deepdive looks like

A strong deepdive reads like a sharp, insightful essay — not a book report.

It:

  1. Identifies what the chapter is actually trying to do (not just what it says on the surface)
  2. Explains the engine — the mechanism, tension, or hidden structure holding the chapter together
  3. Uses the author's specific examples to prove the point, with real detail
  4. Points out what most readers miss or misread — and explains why
  5. Compresses to a memorable takeaway
  6. Ends with comprehension questions that test real understanding, not recall — as many as the chapter warrants

Section headers should describe actual content (e.g. "Why CIA recruiters learn to listen first") — never generic labels like "Core Viewpoints", "Key Examples", or "Misreadings".

Depth is content-driven. Go as deep as the chapter demands. Do not pad.


What NOT to do

  • Do NOT bullet-list the chapter content — write in flowing paragraphs
  • Do NOT use generic template headers
  • Do NOT summarize. Interpret.
  • Do NOT write to hit a word count — write until the chapter is truly understood
  • Do NOT rely on general knowledge when original text is available
  • Do NOT jump to application before the original text meaning is solid
  • Do NOT treat the output shape as a fill-in-the-blanks template

Personalization

When working with Jin, bias toward:

  • Content-driven over format-driven
  • Deep chapter over quick summary
  • Stronger interpretation over generic teaching language
  • Original-text-based explanation over search-based paraphrase
  • Outputs that feel worth saving to Obsidian and rereading later

Signal over symmetry. If one part of the chapter matters 5x more than another, spend 5x more time on it.


EPUB Workflow

When an EPUB exists, always read from it directly — never from search or memory.

Step 1 — List chapters (once per book)

python3 /data/workspace/skills/skills/deeptutor/scripts/epub_chapter_reader.py "\x3Cepub_path>" --list

Map book chapter numbers to EPUB indices. Prologues and part dividers shift numbering.

Step 2 — Extract original text

python3 /data/workspace/skills/skills/deeptutor/scripts/epub_chapter_reader.py "\x3Cepub_path>" --chapter \x3CN> --max-chars 14000

Read the full text before writing. For short chapters, use what's there. For long chapters, 14000 chars is enough to work with.

Step 3 — Write the deepdive

Write in Chinese unless instructed otherwise. Go as deep as the chapter demands. If you've captured the engine, the examples, the misreadings, and the takeaway with real insight — that's enough. Do not pad to hit a word count.

Step 4 — Save to Obsidian

python3 /data/workspace/skills/skills/deeptutor/scripts/save_chapter_deepdive.py \
  --book "\x3CBook Title>" \
  --chapter \x3CN> \
  --title "\x3CChapter Title>" \
  --content-file /tmp/ch\x3CN>_deepdive.md

This saves to /data/workspace/obsidian-vault/Books/\x3Cbook-slug>/ and auto-generates index + navigation links.


Self-check before moving to next chapter

Ask yourself:

  • Does this deepdive feel written specifically for this chapter, or could it fit any book?
  • Is there at least one non-obvious insight or interpretive payoff?
  • Did I use the original text, not my own general knowledge?
  • Would the reader feel this was worth saving and rereading?

If any answer is no — go deeper before saving.


Quiz Mode (optional)

After a chapter deepdive, if the user wants reinforcement, generate a quiz:

  • Choice — 4-option multiple choice (tests comprehension)
  • Written — open-ended questions (tests articulation)
  • Application — scenario-based (tests real-world transfer)

On Telegram, use 1/2/3/4 style buttons for choice quizzes.


Cross-chapter connections

When relevant, connect this chapter to:

  • Previous chapters the user has already read
  • Other books or concepts the user knows

These cross-connections are often where the deepest insights emerge.


Reference files

  • scripts/epub_chapter_reader.py — extract chapters from EPUB
  • scripts/save_chapter_deepdive.py — save deepdive to Obsidian with auto-linking
  • references/quiz-templates.md — quiz generation templates

Usage Examples

Minimal

deeptutor,读 Chapter 3

With direction

用 deeptutor 带我读 Chapter 4,content-driven 方式

With quiz

deeptutor,读 Chapter 4,然后生成一个 quiz

Full command to subagent

Use deeptutor to do a content-driven deepdive of Chapter 4. Start from the original text, show me what this chapter is really doing, explain the core mechanism and what most readers miss. Save it to Obsidian automatically.

Troubleshooting

No EPUB found? — Make sure the EPUB path is correct. Use absolute paths to be safe.

Obsidian not saving? — Check that the Obsidian vault path exists and is writable.

Quiz not generating? — Quiz mode is optional. Ask explicitly: "generate a quiz" after the deepdive.

Philosophy

  • Content drives structure — don't force a template
  • Interpret, don't summarize — add insight, not just restate
  • Anti-generic — if it could fit any book, rewrite it
  • Depth over length — go as deep as the chapter demands
安全使用建议
This skill appears to do what it says: read local EPUBs, generate chapter-level deepdives, and save them into an Obsidian vault. Before installing or running it, consider the following: - Runtime and dependencies: the scripts call python3 and import ebooklib and bs4 (BeautifulSoup). Make sure your environment has python3 and these packages installed (e.g., pip install ebooklib bs4). The package metadata did not declare these requirements. - File access: the scripts will read EPUB files and write markdown files under /data/workspace/obsidian-vault/Books by default. If you store sensitive data elsewhere, or if you want notes in a different vault, update the save script or ensure the vault path is correct and writable. - Review code: the repository is small and local; you or your admin should review the two Python scripts before running them (they perform local file I/O only). If you don't trust the source, run in an isolated environment or container. - No network/exfiltration detected: there are no network calls, external endpoints, or credential requests in the provided files or instructions. That reduces risk, but always validate that your execution environment (subagents, containers) enforces the file-access boundaries you expect. If you want to proceed: install the Python deps, point the vault path to a directory you control (or edit scripts to change VAULT), and run the provided commands on EPUB files you trust.
功能分析
Type: OpenClaw Skill Name: deeptutor Version: 1.2.0 The DeepTutor skill is a well-documented tool for reading EPUB files and saving study notes to an Obsidian vault. The Python scripts (epub_chapter_reader.py and save_chapter_deepdive.py) perform standard file parsing and local file writing within the expected workspace paths (/data/workspace/obsidian-vault/) without any network activity, obfuscation, or unauthorized execution. The instructions in SKILL.md and the reference prompts are focused entirely on the persona of a reading tutor and do not contain any malicious prompt injection or data exfiltration attempts.
能力标签
cryptocan-make-purchases
能力评估
Purpose & Capability
Name/description match the included scripts and SKILL.md: the skill reads EPUBs, produces chapter deepdives, and saves to an Obsidian vault. One minor incoherence: the registry metadata lists no required binaries, but SKILL.md and the included scripts invoke python3. The skill therefore implicitly requires a Python runtime and third-party Python packages (ebooklib, bs4) that are not declared.
Instruction Scope
SKILL.md explicitly instructs the agent to list and extract chapters from a local EPUB and to save generated deepdives to an Obsidian vault. The included scripts operate only on local filesystem paths (EPUB file and /data/workspace/obsidian-vault/Books) and do not perform network calls or access unrelated system state. The instructions avoid vague, broad data-collection directives.
Install Mechanism
There is no install spec (instruction-only), which is low-risk. However, code files are bundled and will be executed by the agent if invoked. The package does not declare Python or the required Python packages (ebooklib, bs4/BeautifulSoup). Users must ensure python3 and those libraries are available in the environment before running the scripts.
Credentials
No environment variables or credentials are requested (good). The scripts, however, write to a hard-coded Obsidian vault path (/data/workspace/obsidian-vault/Books) and attempt EPUB fallbacks (/root/.openclaw/media/inbound/ and /data/workspace/obsidian-vault/Books/). That file-read/write access is necessary for the described functionality but should be noted — the skill will read EPUB files and create/modify files under that vault path.
Persistence & Privilege
The skill does not request persistent/always-on privileges (always: false) and does not attempt to modify other skills or global agent settings. It only writes to its own target directories in the Obsidian vault.
如何使用
  1. 确保已安装 OpenClaw(本地或 Docker 部署)
  2. 在对话框中输入安装命令:/install deeptutor
  3. 安装完成后,直接呼叫该 Skill 的名称或使用 /deeptutor 触发
  4. 根据 Skill 的参数说明提供必要输入,即可获得结构化输出
版本历史
v1.2.0
Combined README into SKILL.md for ClawHub display - includes install guide + execution instructions in one file
v1.1.1
Reverted metadata change - SKILL.md back to clean
v1.1.0
Added metadata with install instructions and quick start to frontmatter for ClawHub page display
v1.0.9
Expanded README with full installation guide, quick start, requirements, troubleshooting for ClawHub users
v1.0.8
Added README.md with usage documentation for ClawHub users
v1.0.7
Removed last two hard constraints: char minimum and fixed question count. Both are now content-driven.
v1.0.6
Removed word count minimum. Depth is content-driven, not length-driven.
v1.0.5
Restored full book-deep-study teaching philosophy + execution workflow. Essay-style deepdives, 1000 word minimum, anti-generic, EPUB-first, auto-Obsidian.
v1.0.4
Rewrote instructions to produce essay-style deepdives, not bullet reports. Anti-template, min 1000 words, content-specific headers only.
v1.0.3
Stronger execution instructions: min 800 words/chapter, quality check, anti-generic rule, explicit depth signals
v1.0.2
Simplified SKILL.md - removed ClawHub display content, kept only subagent execution instructions
v1.0.1
Added detailed README with setup, usage, examples, and feature documentation
v1.0.0
Personalized content-driven deep reading tutor; renamed from book-deep-study as the preferred entrypoint.
元数据
Slug deeptutor
版本 1.2.0
许可证 MIT-0
累计安装 0
当前安装数 0
历史版本数 13
常见问题

Deeptutor 是什么?

A personalized content-driven deep reading tutor. Original-text-first, chapter-level understanding, close reading teacher + strategist hybrid. Auto-saves to... 它是一个面向 Claude Code / OpenClaw 的 AI Agent Skill 插件,目前累计下载 145 次。

如何安装 Deeptutor?

在 OpenClaw 或 Claude Code 对话框中运行命令「/install deeptutor」即可一键安装,无需额外配置。

Deeptutor 是免费的吗?

是的,Deeptutor 完全免费,采用 MIT-0 许可证,可自由下载、安装和使用。

Deeptutor 支持哪些平台?

Deeptutor 跨平台运行,可在任意部署了 OpenClaw / Claude Code 的环境中使用(cross-platform)。

谁开发了 Deeptutor?

由 tanjinlimkelvin-dot(@tanjinlimkelvin-dot)开发并维护,当前版本 v1.2.0。

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