relatedwork-summarizer

Summarize and index related research literature using OpenAI-compatible LLMs.

43|2|Updated Apr 5, 2026

Search Tags:#summary generation #research tool #literature summarization #cross-index #AI literature analysis

Ready to run

npx skills add https://github.com/PKU-ASAL/CoPaper-OpenCode --skill relatedwork-summarizer-pku-asal

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: relatedwork-summarizer
Source: https://github.com/PKU-ASAL/CoPaper-OpenCode/tree/main/.agents/skills/relatedwork-summarizer
Command: npx skills add https://github.com/PKU-ASAL/CoPaper-OpenCode --skill relatedwork-summarizer-pku-asal

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires OPENAI_API_KEY, COPAPER_MODEL, OPENAI_BASE_URL, pypdf, pdfplumber, and includes scripts (resource) and references (resource) components.

What problem does it solve?

This Skill streamlines the process of summarizing related work, building a literature cross-index, and generating coverage reports for research papers.

Core Features & Use Cases

Automated Summarization: Summarize PDFs into readable, structured text using OpenAI-compatible LLMs.
Cross-Index Building: Create an indexed catalog of summaries for easy literature retrieval.
Coverage Reporting: Assess the coverage of the summary against the paper's storyline.
Use Case: Ideal for researchers looking to efficiently summarize related work and track its relevance to their research project.

Quick Start

Use the relatedwork-summarizer skill to summarize and index related work in your paper.

Frequently Asked Questions about relatedwork-summarizer

High-intent search queries and answers about installing and using this skill.

FAQPage Schema

How do I automate literature summarization and build a cross-index for my research paper?▼

Automated literature summarization generates structured text from PDFs using OpenAI-compatible LLMs, building an indexed catalog for easy retrieval. It streamlines summarizing related work and tracking relevance to your research project.

Does AI literature analysis require an OpenAI API key to process PDFs?▼

AI literature analysis requires an OpenAI API key and a compatible base URL to extract text. It also uses pypdf and pdfplumber dependencies alongside copaper CLI tools to process and index PDF documents.

What is the best way to assess the coverage of a summary against a paper's storyline?▼

Assessing summary coverage involves generating a report that evaluates how well the summarized related work aligns with your research paper's storyline. This ensures your literature review comprehensively tracks relevance to your project.

Can I use the copaper CLI tool to summarize related work without manual extraction?▼

You can use the copaper CLI tool to automate text extraction and summary generation from PDFs. It leverages OpenAI-compatible LLMs to create readable structured text, eliminating manual extraction for your literature review.

How do I generate a literature cross-index from multiple research PDFs?▼

Generating a literature cross-index involves summarizing multiple research PDFs into structured text and cataloging them for easy retrieval. This automated indexing creates a comprehensive map of related work for your research workflow.