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OpenScience template

AI Co-Scientist for ML Research

OpenScience co-scientist for ML: literature loop, one concrete experiment, train/eval scaffold, methods draft — as files. Bring your own Anthropic key.

NewNew10.4 KB snapshotPro VM

What's inside

Harness

OpenScience

Plan

Pro

vCPU

2

Memory

6 GiB

Snapshot

10.4 KB

Setup prompt + walkthrough

The AI Co-Scientist for ML Research setup prompt + walkthrough

Paste this into any capable agent and it walks you through the connections, the trigger, and a supervised first run — the whole setup, in your own words. Or skip the setup and run this exact agent hosted.

Set up an agent for me, in its own chat, that does the work of a AI Co-Scientist for ML Research. Work from the files and facts I actually give it, rank what matters by impact rather than by how many items it found, and stop short of sending, filing, posting, or changing anything live unless I ask for that in the same run. Walk me through connecting Anthropic, Gemini, OpenAI, and OpenRouter. Have it run whenever I hand it the work, and every weekday morning on whatever I left unfinished. Ask me where the source material lives, who should receive the output, and what good enough looks like for a first pass. Run one pass while I watch, then save it.

Already built, running in ~3 min · 30-day money-back on first purchase

How it works · ~3 minutes

  1. 01 · Fork

    New isolated microVM on your subdomain — creator agent state included.

  2. 02 · Your keys

    Log into OpenScience with your own model credentials (BYOK).

  3. 03 · Ask it to work

    Open the terminal and give the agent a real job. You keep what ships.

Example first ask

Pull my open PRs, summarize risk, and draft a review checklist.

30-day money-back on your first purchase · no free trial · keys never leave the VM

About this template

From a pile of PDFs to a methods draft

If you start ML research with forty open tabs and an empty repo, this OpenScience template hands you the co-scientist loop already wired: literature, hypothesis, experiment scaffold, methods write-up.

Files come out. Not a chat monologue.

What the ML co-scientist loop does

Two skills carry the work.

ml-lit-loop runs the literature side — survey, shortlist, notes you can return to. ml-experiment-scaffold turns that shortlist into one concrete experiment: a train/eval scaffold plus the methods section that describes it. Output lands as files under the workspace layout, so tomorrow's session picks up where this one stopped.

You still decide which experiment is worth running.

What lands in your fork

  • The OpenScience ml agent, oriented for research co-scientist work
  • ml-lit-loop — the literature loop
  • ml-experiment-scaffold — experiment scaffold and methods draft
  • A layout for lit notes, the scaffold, and the write-up
  • Browser workspace entry via Open OpenScience

What you supply (BYOK)

One model key gets you moving.

ANTHROPIC_API_KEY is the documented path; OPENAI_API_KEY, GEMINI_API_KEY and OPENROUTER_API_KEY are read too. Export it in the VM shell:

export ANTHROPIC_API_KEY=sk-ant-...

Keys stay on your microVM. Nothing is baked into the template.

Your first five minutes

Fork, open the VM, click Open OpenScience.

Then give the ml agent one full instruction:

Survey diffusion models for medical imaging. Propose one experiment. Scaffold train/eval. Draft a methods section.

You should end up with a paper shortlist, one concrete experiment plan, a code scaffold, and a methods draft you can edit — not a transcript.

Honest limits

This is a research desk, not a training cluster.

There is no GPU in the box and no managed fleet behind it: the scaffold gets written here, the heavy training runs wherever you run training. Nobody else holds your API keys. It is ML-shaped, so for pure biology take the comp-bio OpenScience template instead. Two skills and a layout is the honest surface area — the depth comes from what you ask it.

Model usage is yours. 30-day money-back on your first jurniti purchase.

Fork it. Open OpenScience. Run one survey-to-scaffold pass.

Inside this fork

Forking copies this template into a brand-new, fully isolated microVM on your own subdomain. Here's exactly what lands in it.

  • OpenScience agent

    The upstream harness, pre-installed — same version the creator ran.

  • Pro VM

    2 vCPU · 6 GiB RAM · 50 GiB disk.

  • Creator's /persist data

    The captured persist volume is copied byte-for-byte into your fork.

  • BYOK — your keys, your VM

    Add your model API keys after forking; they live only inside your microVM.

What this agent can do

2 skills

  • ml-experiment-scaffold

    Experiment scaffold + methods

  • ml-lit-loop

    ML literature loop

What you'll configure after forking

Secrets are scrubbed from shared templates — these are the names you supply in your agent's terminal once it boots.

Environment variables

  • ANTHROPIC_API_KEY
  • GEMINI_API_KEY
  • OPENAI_API_KEY
  • OPENROUTER_API_KEY

Your turn

Your own AI Co-Scientist for ML Research, live in about 3 minutes.

Copy the setup prompt and build it yourself — or let this exact OpenScienceagent run hosted, already built, on a brand-new, fully isolated microVM on your own subdomain. Add your own keys after it boots; they never leave the box. Don't love it? Your first jurniti purchase comes with 30 days to get every cent back.

New paid VM · BYOK · 30-day money-back on your first purchase · ~3 min to provision

Needs 4 of your own API keys