ai-agent

autoresearch: AI Research

Name: autoresearch: AI Research
Author: karpathy

Get automated research with autoresearch. For startup founders using AI agents.

93,765 stars13,298 forksPythonGuide quality 8/10Updated 3/26/2026100% free · open source

What it does

Autoresearch generates automated research papers and articles using AI agents, allowing startup founders to quickly explore and summarize large amounts of information on a given topic.

When to use it

•When you need to quickly research and summarize a large amount of information on a new topic
•When you want to automate the process of generating research papers or articles
•When you need to explore and analyze large datasets and generate insights

Ready-to-paste prompt

python generate.py --topic 'AI for startup founders' --dataset 'startup_data.csv' --output 'research_paper.md'

Heads up: Make sure you have the correct version of Python (3.8 or later) and the required dependencies installed, as specified in the `requirements.txt` file, to avoid compatibility issues

Saves to your device

Use with Claude

New

Skip the builder — one click puts this in Claude, Cursor, Antigravity and more.

✅ Light setup

Installs with a command or two; your AI agent can do it for you.

Try it instantly — no install

Claude Code

mkdir -p ~/.claude/skills/autoresearch && curl -fsSL https://workflowstacks.com/api/skills/autoresearch/claude-skill -o ~/.claude/skills/autoresearch/SKILL.md

Open in another AI app

Opens the app with this repo with the prompt ready to go — no copy-paste needed.

Connect the whole catalog (MCP)

claude mcp add --transport http workflowstacks https://workflowstacks.com/api/mcp

Adds a WorkflowStacks connector to Claude Code: search and load any skill here by chatting.

How autoresearch: AI Research works

Codeflow

Free to inspect

Autoresearch: AI Research is a small Python project (~1.1k lines across 2 code files). Setup is light: install Python, run one command. Last commit 5 months ago, no license file, no tests found.

Size

Small codebase

~1.1k lines · 2 code files · 9 min skim

Setup

Light setup

Install Python, run one command.

Runs on

Python

No API keys detected

Python 83%Jupyter Notebook 17%

What happens, step by step

AI agent experiments with code

You give

program instructions

1Prepare Data

download training data

prepare.py

2Train Model

train model for 5 minutes

train.py

3Run Experiment

run experiment and check results

4Edit Code

agent edits train.py file

train.py

5Repeat Experiment

repeat experiment with new code

You get

experiment results

Where to start reading

1
README.md
Start here — what it does and how to install it
2
pyproject.toml
Dependencies and the commands it exposes

READMENo tests foundThin docsNo CINo licenseUpdated 5 mo ago