An advanced AI agent skill designed to generate mathematically rigorous, visually polished HTML study notes and step-by-step homework solutions for STEM subjects.
Install & Download
1. ClawHub CLI
The fastest way to install a skill directly from the registry.
npx clawhub@latest install study-notes
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 study-notes 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 Study Notes Generator?
The study-notes skill is a highly advanced, multi-branch workflow skill designed to generate comprehensive, visually polished, and mathematically rigorous HTML study guides and homework solutions. Built to optimize study workflows, this framework is part of the larger ecosystem of Openclaw Skills, enabling AI coding agents to process complex academic material—such as physics, mathematics, chemistry, and computer science—and output publication-ready study materials.
By utilizing this skill, users can transform raw text, scanned documents, and student questions into pedagogical masterpieces. It addresses the common pitfall of shallow AI-generated notes and incorrect calculations by enforcing strict validation, programmatic computation, and a systematic multi-phase execution process. Whether digesting full textbooks or generating step-by-step solutions with embedded SVG diagrams, this tool provides unparalleled educational depth.
Study Notes Generator Use Cases
- PDF Textbook to Complete Study Guides: Transform uploaded lecture notes or scanned textbook chapters (using built-in OCR and image rendering) into comprehensive, structured HTML review notes.
- Homework-Guided Concept Re-learning: Input a few homework questions to reverse-infer the academic chapter, producing exhaustive, foundational notes focused around those specific core concepts.
- Self-Assessment Homework Solutions: Generate standalone HTML sheets where problem statements and figures are always visible, but the step-by-step solutions remain hidden in collapsible interactive details elements.
- Interactive Active-Recall Materials: Create interactive multi-choice quizzes and hidden, exportable Anki flashcard decks embedded directly within the generated HTML file for spaced repetition.
How Study Notes Generator Works
- Workflow Routing: The AI agent analyzes the input (PDFs, text prompts, or homework images) and automatically routes to Mode A (PDF to Notes), Mode B (Homework to Chapter Notes), or Mode C (Homework to Solutions).
- Planning & Specification Generation: The agent scans the source material to create a table of contents and a shared specification sheet, aligning symbol notations, math conventions, and visual color schemes.
- Parallel Concept Fan-Out: The topic is divided into individual concept blocks, generated in parallel via sub-agents or focused sequential runs to maximize explanatory depth and derivation accuracy.
- Rigorous Double-Solve Verification: For any worked examples or solutions, the agent performs a blind double-solve (solving independently twice), validates numeric steps using Python and SymPy, and cross-checks against a per-problem quality checklist.
- Coherent Assembly & Quality Audit: Individual sections are compiled into a single HTML file. The script performs static analysis to find KaTeX math syntax issues, silent Unicode characters, or rendering bugs before presentation.
Study Notes Generator Setup
Ensure your environment has the required dependencies. To get started with this skill from the Openclaw Skills library, install the necessary Python packages and run the extraction scripts:
# Install Python dependencies for PDF processing and math analysis
pip install pymupdf sympy --break-system-packages -q
# Extract text from your source PDF textbook or lecture slides
python3 scripts/extract_pdf.py text input_material.pdf -o extracted_content.txt
# Alternatively, if dealing with a scanned image-only PDF, render pages to PNGs
python3 scripts/extract_pdf.py images input_material.pdf -o output_pages_directory --dpi 150
Configure your AI workspace to use this skill by copying the SKILL.md rules into your agent's system instructions.
Study Notes Generator Data Schema & Taxonomy
This skill generates self-contained HTML files and relies on specific auxiliary scripts. The generated outputs are structured as follows:
| File Name / Path | Type | Description |
|---|---|---|
<subject>学习笔记.html |
Output HTML | Standalone, interactive study guide with hierarchical TOC, math formulas, and interactive elements. |
<subject>作业解答.html |
Output HTML | Standalone homework solution sheet with collapsible answer blocks and inline SVG/base64 diagrams. |
scripts/extract_pdf.py |
Helper Script | Utility to extract text or render pages to images from academic PDFs. |
scripts/fix_math.py |
Helper Script | Automatically scans and rewrites naked Unicode symbols (e.g., center dots or minus signs) to standard KaTeX commands. |
scripts/build_and_check.py |
Helper Script | Concatenates part files, checks for div balance, and performs syntax tests for KaTeX errors. |
scripts/make_anki.py |
Helper Script | Parses generated HTML files to extract flashcards and output an Anki-importable TSV deck. |
Metadata Taxonomy
All outputs embed KaTeX configurations for dynamic browser rendering, direct SVG markers, and localStorage state tracking for interactive multi-choice quizzes.
Study Notes Generator Advanced Features
- Blind Double-Solve Verification: Guarantees zero-error math calculations by executing a programmatic verification loop and computing expressions independently via Python's SymPy engine.
- Self-Contained Interactive Quizzes: Integrates interactive multiple-choice widgets that grade student answers instantly, render explanations, and save progression within browser local storage.
- Embedded Anki Flashcard Decks: Generates hidden spaced-repetition card decks in HTML that can be easily compiled into standard
.tsvflashcards via backend scripts. - Source-Grounded Fidelity Citations: Adds NotebookLM-style citations (e.g.,
见课本 p.123) to math boxes and core definitions to verify alignment with official curriculum materials. - Automated KaTeX Auditing: Features strict pre-flight checks using
build_and_check.pyto catch silent Unicode glitches, nested boxes, and parser errors before delivery.
SKILL.md
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