ai-papers-reader
agent
Gecti
Health Gecti
- License — License: MIT
- Description — Repository has a description
- Active repo — Last push 0 days ago
- Community trust — 21 GitHub stars
Code Gecti
- Code scan — Scanned 12 files during light audit, no dangerous patterns found
Permissions Gecti
- Permissions — No dangerous permissions requested
Purpose
This is an automated agent that fetches recently published AI research papers, filters them based on your specific interests using a large language model, and publishes a customized weekly digest.
Security Assessment
Overall risk: Low. The tool does not request dangerous local permissions, execute shell commands, or access sensitive local files. It does make external network requests to the Hugging Face API to retrieve paper metadata and communicates with the Google Gemini API for text processing. A code scan of 12 files found no dangerous patterns or hardcoded secrets. Your primary security consideration should be managing the external Gemini API key safely within your environment variables.
Quality Assessment
The project is actively maintained, with its latest code push occurring just today. It is backed by the permissive and standard MIT license, making it fully open-source and safe for integration. While it is a relatively small tool with 21 GitHub stars, it demonstrates clear community interest and relies on highly reputable external services (GitHub Actions, Hugging Face, and Google).
Verdict
Safe to use.
This is an automated agent that fetches recently published AI research papers, filters them based on your specific interests using a large language model, and publishes a customized weekly digest.
Security Assessment
Overall risk: Low. The tool does not request dangerous local permissions, execute shell commands, or access sensitive local files. It does make external network requests to the Hugging Face API to retrieve paper metadata and communicates with the Google Gemini API for text processing. A code scan of 12 files found no dangerous patterns or hardcoded secrets. Your primary security consideration should be managing the external Gemini API key safely within your environment variables.
Quality Assessment
The project is actively maintained, with its latest code push occurring just today. It is backed by the permissive and standard MIT license, making it fully open-source and safe for integration. While it is a relatively small tool with 21 GitHub stars, it demonstrates clear community interest and relies on highly reputable external services (GitHub Actions, Hugging Face, and Google).
Verdict
Safe to use.
AI agent for creating personalized digests of research papers
README.md
AI Papers Reader
AI Papers Reader is an AI agent that brings you weekly digests of latest AI papers, customizable to topics you care about. Check out the published digests at https://ai-papers-reader.taodong.net/.
Implementation
AI Papers Reader is built with the following building blocks:
- Hugging Face's Daily Papers API: It's used to retrieve the metadata of recently published AI papers.
- Gemini 2.5 Flash: It's the LLM used to process the paper metadata and identify those that are most relevant to a set of topics specified in the prompt. The LLM is also used for summarizing recommended papers.
- Github Actions: A workflow runs automatically on Fridays to retrieve the latest paper metadata and use the AI model to generate a new digest. The digests are saved in the docs folder as markdown files.
- Netlify: The markdown files are then deployed to a static website using Netlify.
Customizing Agent Behavior
The default set of topics AI Papers Reader currently use to identify relevant papers are based on my research interest. You can customize them by forking the repo and edit the prompt template to your liking. To generate digests from your own fork of the repo, you will need to supply an API key for Gemini models. You can obtain one for free at http://aistudio.google.com.
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