[Tool Proposal] Enhance ArXiv Toolkit to Read Paper Content

[RamaPranav01]

Hello LangChain Maintainers and Community,
I'm proposing a new, high value tool to fill a critical gap in the Arxiv toolkit.

The Problem

Currently, an agent can use ArxivQueryRun to search for academic papers and get their summaries. However, the workflow stops there. The agent receives a PDF URL but has no tool to read the actual content of the paper. This prevents the creation of true "AI Research Assistants" that can analyze or summarize the full text of the literature they discover.

The Proposal

I propose creating a new tool named ArxivGetPageContentTool.
Function: It will take a single ArXiv paper_id (e.g., '1706.03762') as input.
Action: It will download the corresponding paper, extract the full text from the PDF, and return it as a string.
Synergy: This tool is designed to work perfectly with the existing ArxivQueryRun. An agent would first search for papers, then use this new tool to read the most relevant one.

Value to the Ecosystem

Enables a Core Use Case: Unlocks the ability for agents to perform end-to-end academic research.
Completes a Workflow: Fixes the current "dead end" user experience in the ArXiv toolkit.
Simple & Robust: A straightforward addition with minimal dependencies (pypdf, which is already in the ecosystem).
I have already started working on the implementation, including the necessary mocked unit tests and documentation, and plan to open a Draft PR shortly. I believe this will be a valuable contribution to the community.
Please let me know your thoughts.