research-agent

What problem does it solve?

Academics face a "late-discovery" problem with research papers, where relevant new findings are often missed until significant work has already been done in the wrong direction. This agent provides an early-warning system tailored to an individual's research context.

Core Features & Use Cases

• Personalized Discovery: Filters new arXiv papers based on your GitHub repos, Overleaf projects, and specified interests.
• Deep Connection Analysis: Summarizes papers and explains their relevance to your specific research strands, identifying potential citations, competing approaches, or useful methods.
• Automated Triage: Provides structured memos and batch summaries for discovered papers.
• Use Case: A computer science PhD student working on reinforcement learning can use this agent to automatically get daily digests of new arXiv papers relevant to their specific projects, along with explanations of how each paper connects to their current research.

Quick Start

Use the research-agent skill to set up your research profile by running the onboarding flow.