Convert arXiv papers to clean Markdown optimized for LLM agents.
Running list of tools for literature review, reference management, and academic research. Includes AI assistants, citation managers, PDF readers, and systematic review software for PhD students and researchers.
Standardized template for journal-ready academic research replication packages. Organizes LaTeX, Python, Stata, and R code from day one. Ships with a Claude Code skill and Codex agent that automate converting any existing project into a submission-ready package (AEA, QJE, RES, EJ, etc.).
A curated, researcher-focused guide to arXiv tools, workflows, datasets, and infrastructure for discovering, reading, analyzing, and building on top of scientific papers.
An automated, config-driven pipeline for literature reviews. Searches academic papers, enriches metadata, downloads open-access PDFs, and generates structured Markdown notes.
A local-first Chrome extension for literature reviews: save articles, AI summaries, grounded chat with Gemini, rich notes, and styled Excel exports.
Academic web app that converts Ancient Greek verse and metrical scansion into downloadable MIDI compositions —with pitch models (Pythagorean, Ptolemaic), rhythm models (Aristoxenian, Sapphic/Alcaic, dochmiac), ancient-instrument MIDI mappings, and full provenance docs separating attested evidence from experimental interpretation.
arxiv research papers metadata extractor
The Advanced RAG Academic Assistant is a sophisticated Retrieval-Augmented Generation (RAG) application designed for researchers and students. It allows users to upload multiple academic PDF papers, which are then processed, chunked, and embedded into a local vector store.
Rangkumin is a Manifest V3 Google Chrome extension designed to help students, researchers, and academics instantly extract and summarize scientific journals.
Python toolkit for automated BibTeX metadata enrichment using Semantic Scholar API
SPA em React para recomendação de periódicos científicos com integração Qualis + APIs acadêmicas
🧠 Turn Reasonix Code into a PhD-level research team — 16 MCP tools, 12 AI subagents, 5-engine parallel search, one-click migration
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