Скачать или смотреть PaperDebugger: A Plugin-Based Multi-Agent System for In-Editor Academic Writing, Review, and Editing

Title: PaperDebugger: A Plugin-Based Multi-Agent System for In-Editor Academic Writing, Review, and Editing (Dec 2025)
Link: http://arxiv.org/abs/2512.02589v1
Date: December 2025

Summary:
PaperDebugger is a Chrome extension that integrates Large Language Model (LLM) agents directly into the Overleaf editor, eliminating the need for copy-paste workflows in academic writing. It utilizes a Kubernetes-native orchestration layer and the Model Context Protocol (MCP) to provide context-aware features such as deep literature research, structured critiques, and diff-based revisions within the document's native environment.

Key Topics:
In-editor writing assistance
Multi-agent orchestration
Overleaf integration
Model Context Protocol (MCP)
Large Language Models
Academic writing tools

Chapters:
00:00 - Introduction to PaperDebugger
01:25 - Solving Context Fragmentation
02:57 - Technical Architecture Breakdown
05:22 - Multi-Agent System Design
07:35 - In-Editor Patch Workflow
08:20 - Automated Literature Review
09:39 - User Telemetry Analysis
11:20 - Future of Authorship

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