Senior. Junior. You. The work unit, reimagined.
You did the research. Now you judge it.
AI takes the PI and Trainee roles — designing experiments, running analysis, writing the paper. You become the Editor: the sole decision maker who curates, judges, and steers the science.
Watch a research session unfold, step by step
Click Start Tutorial to begin
Watch how PI and Trainee collaborate on a research project
Each character is a persona backed by a curated set of scientific skills
title: Computational Biology PI
expertise: single-cell genomics and ML
goal: discover cell-type-specific
gene regulatory programs
skills:
- scanpy
- pytorch-lightning
- scvi-tools
- scientific-writing
- scientific-visualization
- statistical-analysis
personality:
- "Visionary: identifies novel
biological questions"
- "Rigorous: demands reproducible
pipelines"Give your character a title, expertise, and personality traits. These shape how the AI agent approaches problems and communicates.
Each skill name maps to a SKILL.md file—the same agent skills used by Cursor and Claude. The AI reads these instructions when acting as this character. Skills include scanpy, scientific-writing, pytorch-lightning, statistical-analysis, and 200+ more.
Drop the YAML file into your project's .autolab/profiles/ folder. The character is now part of your research team, with all attached skills active.
Browse community-created characters or share your own
Set up your own Autonomous Lab in minutes
Add Autonomous Lab to your Cursor MCP settings (~/.cursor/mcp.json):
{
"mcpServers": {
"autonomous-lab": {
"command": "uv",
"args": [
"--directory",
"/path/to/autonomous-lab",
"run", "autonomous-lab"
],
"timeout": 86400,
"env": {
"MCP_WEB_PORT": "8766"
}
}
}
}Install skills in ~/.cursor/skills/. Each skill is a SKILL.md that the AI reads when a character uses it:
# Skills directory structure:
~/.cursor/skills/
scientific-skills/
scanpy/SKILL.md
scvi-tools/SKILL.md
pytorch-lightning/SKILL.md
scientific-writing/SKILL.md
statistical-analysis/SKILL.md
...
# 200+ skills available
# Characters reference these
# by name in their YAMLDownload characters from the Marketplace or create your own in .autolab/profiles/:
title: Your Custom PI
expertise: your domain
goal: what to achieve
skills: # Cursor skill names
- scanpy
- scientific-writing
- statistical-analysis
personality:
- "Trait: description"The PI-Trainee loop runs, then you act as Editor:
# The research cycle:
autolab_next # PI sets agenda
autolab_next # Trainee executes
autolab_next # PI reviews
... # iterate
# When paper is ready:
autolab_editorial # You decide!
# Invite reviewers, then:
# Accept / Minor / Major / Reject