A professional-grade research agent that transforms books into structured teaching materials, critical evaluations, and actionable knowledge frameworks.
Install & Download
1. ClawHub CLI
The fastest way to install a skill directly from the registry.
npx clawhub@latest install book-deep-reader
2. Manual Installation
Copy the skill folder to one of these locations
~/.openclaw/skills/ <project>/skills/ Priority: Workspace > Local > Bundled
3. Prompt Installation
Copy this prompt to OpenClaw to install it automatically.
Help me install book-deep-reader using Clawhub. If Clawhub is not installed, install it first (npm i -g clawhub).
Prefer to download?
Get the raw skill files in a ZIP archive.
What is Book Deep Reader?
Book Deep Reader is a sophisticated research and synthesis tool designed for the Openclaw Skills ecosystem. It goes beyond simple summarization by employing a 5-layer analysis methodology to extract the structural, conceptual, and practical essence of any book. Whether you are dealing with complex academic texts or business manifestos, this skill identifies the central problem the author aims to solve and builds a comprehensive knowledge system around it.
By leveraging advanced web research and cross-referencing capabilities, Book Deep Reader ensures high-fidelity output that is accurate to the original source. It is specifically engineered for users who need to teach others, verify their understanding against original sources, or gain cross-disciplinary insights without spending dozens of hours in manual reading. The skill supports both English and Chinese literature, making it a versatile asset for global knowledge workers.
Book Deep Reader Use Cases
- Creating teaching-quality lecture notes or presentation materials from a specific book.
- Rapidly onboarding onto a new knowledge system using a book's core principles and models.
- Performing critical evaluations and comparative analyses between competing theories in the same field.
- Verifying personal understanding of a text against authoritative wikis and expert reviews.
- Generating actionable implementation plans and 'how-to' guides based on a book's practical cases.
How Book Deep Reader Works
- Identification: The agent identifies the book via title, author, or ISBN and gathers foundational metadata from sources like Douban, Goodreads, and publisher pages.
- Deep Research: It performs an exhaustive search for authoritative references, including author interviews, academic context, and community wikis to build a rich source database.
- 5-Layer Extraction: The skill analyzes the content through five distinct lenses: Structure, Core Framework, Chapter Details, Depth Mechanisms (underlying assumptions), and Teaching Materials.
- Critical Evaluation: It assesses the book's innovation, academic positioning, and limitations while identifying cross-disciplinary applications.
- Verification: A rigorous cross-check is performed to ensure every claim traces back to an authoritative source, flagging any uncertainties.
- Output Generation: A structured Markdown file is generated in the workspace, optimized for both quick skimming and deep study.
Book Deep Reader Setup
To utilize Book Deep Reader within your environment, ensure you have the necessary search tools configured in your Openclaw Skills setup.
# Standard setup for Openclaw Skills research agents
npm install @openclaw/mimo-web-search
npm install @openclaw/web-fetch
# Configure your workspace directory for output
export OPENCLAW_WORKSPACE="./my-knowledge-base"
Once installed, you can trigger the skill by providing a book title or ISBN to your AI agent.
Book Deep Reader Data Schema & Taxonomy
The skill produces a highly structured Markdown (.md) file. The taxonomy follows this schema:
| Section | Description |
|---|---|
| Knowledge Framework | Visual map and 1-3 core concepts defining the book. |
| Chapter Outline | Purpose-driven breakdown of the book's architecture. |
| Case Study Database | Concrete examples with data, names, and quotes. |
| Critical Evaluation | Assessment of innovation, limitations, and academic context. |
| Teaching Toolkit | Analogies, metaphors, and responses to common skepticism. |
| Action Plan | Immediate implementation steps and actionable takeaways. |
Book Deep Reader Advanced Features
- Multi-source cross-referencing: Validates book content against author keynotes, YouTube transcripts, and academic predecessor research.
- Bilingual Support: Seamlessly handles deep research and output generation for both English and Chinese sources.
- Comparative Analysis Hook: Automatically searches for contemporary books on the same topic to highlight differing viewpoints.
- Boundary Condition Analysis: Identifies specifically where the author's theories may fail or encounter limitations.
- Teaching-Ready Output: Formats content specifically so the user can explain the book to others without having read it themselves.
SKILL.md
Loading
Related Openclaw Skills
Learning Aggregator
A cross-session analysis tool that synthesizes accumulated learning files into ranked promotion candidates for AI project instructions.
WeShop Baby Face Generator Skill
An AI-powered skill that predicts a baby's appearance by blending facial features from two parent photos via the WeShop OpenAPI.
Bikini Try-On OpenAPI Skill
An advanced AI-powered virtual try-on tool that allows users to realistically overlay bikini designs onto person photos using the WeShop OpenAPI.
Intent Framed Agent
A specialized agent protocol that formalizes coding intent and monitors for scope drift during implementation sessions.
Lockheed Martin Knowledge Skill
A specialized Openclaw Skills module providing deep technical and business intelligence on Lockheed Martin, the world's leading defense and aerospace contractor.
Junqi Dark Layout
A sophisticated layout generator for Chinese Military Chess that blends LLM-driven strategy with automated Python rule validation and image rendering using Openclaw Skills.
Featured*
