4,873,866 AI resources indexedWorking toward the world’s largest AI resource index.
Reusable instructions for compatible AI agents.
Field counts come from the latest full-catalog snapshot. A resource can belong to several fields and platforms.
Quantitative finance analysis including portfolio optimization, risk modeling, and time series econometrics using jupyter_execute. Use when the user asks about portfolio analysis, stock returns, financial risk, investment optimization, or volatility modeling.
Browse trending papers, search by keyword, and get paper details from Hugging Face Papers. Use when the user wants to find ML research, asks about recent AI papers, trending models, or mentions Hugging Face Papers.
Create and execute Jupyter notebooks for interactive data analysis using jupyter_execute and jupyter_notebook tools. Use when the user asks to run Python code interactively, create notebooks, analyze data in cells, or mentions .ipynb files.
Create, edit, and compile LaTeX documents for academic papers using latex_compile, update_latex, and send_ui_directive tools. Use when the user mentions LaTeX, .tex files, academic writing, typesetting, or needs to compile documents with equations, theses, or journal submissions.
Conduct thorough academic peer reviews with structured feedback using load_pdf and arxiv_to_prompt. Use when the user asks to review a paper, provide manuscript feedback, critique research, or write a referee report.
Design and run machine learning experiments with proper evaluation using jupyter_execute, including training, benchmarking, and ablation studies. Use when the user wants to train models, compare algorithms, run ablation studies, evaluate ML performance, or reproduce paper results.
Core academic workspace tools: LaTeX compilation, Jupyter execution, PDF loading, UI control, content updates, and arXiv paper conversion. Use when the user asks to compile LaTeX, run Python code, load PDFs, display data, or control workspace editors.
Read and analyze arXiv papers by fetching LaTeX source, listing sections, or extracting abstracts. Use when the user mentions arXiv, research papers, preprints, paper IDs like 2301.xxxxx, or wants to read academic publications.
Construct and verify mathematical proofs using LaTeX typesetting and computational verification via jupyter_execute. Use when the user asks to prove a theorem, verify a mathematical argument, construct a formal proof, or check proof correctness computationally.
Try a broader search or clear some filters.
Platform labels describe intended use. Read each resource's author credits, requirements and available access methods.