An intelligent AI skill designed to parse academic PDFs and extract core methodologies, findings, and simplified explanations.
Install & Download
1. ClawHub CLI
The fastest way to install a skill directly from the registry.
npx clawhub@latest install academic-paper-summarizer
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 academic-paper-summarizer 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 Academic Paper Summarizer?
The Academic Paper Summarizer is a specialized tool within the Openclaw Skills ecosystem designed for researchers, students, and academics who need to process large volumes of literature efficiently. It leverages advanced PDF parsing libraries and AI logic to transform dense, technical papers into structured, readable summaries without losing academic rigor.
By integrating this skill into your workflow, you can automate the tedious process of reading entire papers just to identify key data points. It supports both English and Chinese languages, ensuring global research is accessible and easily digestible through structured Markdown reports.
Academic Paper Summarizer Use Cases
- Rapid literature review and screening for systematic reviews.
- Generating simplified explanations of complex technical papers for non-expert stakeholders.
- Extracting specific quantitative results and methodology details for meta-analysis.
- Batch processing directories of PDFs to create a searchable knowledge base.
How Academic Paper Summarizer Works
- The skill utilizes pypdf and pdfplumber to perform deep text and structural analysis of the uploaded PDF file.
- It identifies key sections such as the Abstract, Methodology, Results, and Conclusion using heuristic and AI-driven patterns.
- The engine synthesizes the extracted text to generate a structured Markdown summary covering core problems and major findings.
- Optional plain-language translation is applied to provide an easy-to-understand explanation of the research content.
Academic Paper Summarizer Setup
To use this contribution from the Openclaw Skills repository, ensure you have Python 3.8+ installed, then set up the dependencies:
pip install pypdf pdfplumber
Run the summarizer using the provided scripts:
python skills/academic-paper-summarizer/scripts/summarize.py --input paper.pdf --output summary.md
Academic Paper Summarizer Data Schema & Taxonomy
The skill produces a structured Markdown document with the following metadata and content taxonomy:
| Section | Description |
|---|---|
| Basic Info | Includes Title, Authors, Journal, and Year |
| Core Problem | The primary research question being addressed |
| Methodology | Details on the techniques and approaches used |
| Findings | Key data points and empirical conclusions |
| Limitations | Identified weaknesses or scope constraints |
| Simplified Explanation | A high-level summary in layman's terms |
Academic Paper Summarizer Advanced Features
- Batch Processing: Use the batch.py script to summarize entire folders of research papers simultaneously.
- Targeted Extraction: Define specific fields (e.g., results, method) to extract only the data you need via the extract.py utility.
- Multi-lingual Support: Seamlessly handles both Chinese and English academic publications.
- Length Customization: Adjust summary granularity using the --length parameter for short, medium, or long outputs.
SKILL.md
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