Open Science: The open-source AI workbench for scientific research

The open-source AI workbench for scientific research.

Give it a goal. It reads the literature, writes and runs the code, runs the experiments, and writes up what it found, with every step on the record.

Download · Quickstart · Documentation · Changelog · Contributing

OpenScience is a research agent with a workbench around it. You describe the task in plain language; it plans, gathers evidence, runs code and experiments, and hands back results you can check. It runs as a desktop app, a browser workspace, or a terminal command, on your machine, against your files.

It is built for the parts of research that are real work but not the idea: pulling and cleaning data, reproducing a claim, sweeping a parameter, drafting the methods section, checking a reference. You keep the idea and the judgment.

Desktop app. Download for macOS, Windows or Linux. It updates itself.

npm install -g @synsci/openscience openscience

Or run it without installing:

npx synsci

Or with the standalone installer on macOS and Linux:

curl -fsSL https://openscience.sh/install | bash

Then open Customize → Models and connect a provider, or from the terminal:

openscience keys add # your own API key openscience local add # Ollama, LM Studio, or another local endpoint

The installation guide covers platform details, updates and uninstalling.

Open a project folder and describe the work:

openscience ~/research/my-project

Inspect data/samples.csv for missing values and inconsistent labels. Keep the original data unchanged. Save a quality report and a plot in results/, with the code needed to reproduce them.

Start with /plan when you want to agree on the method first. For a single turn from a script or a pipeline:

openscience run "Review the analysis plan in this project" openscience run --continue "Suggest checks for the assumptions you identified"

Review sources, assumptions, code and outputs before relying on a scientific conclusion. The agent shows you what it did so that you can.

Task What happens

Review literature Search scientific sources, compare findings, save cited evidence.

Analyze data Inspect inputs, write and run analysis code, produce figures and reports.

Reproduce experiments Agree on a claim, prerequisites and budget, then compare measured results.

Run compute Local kernels for everyday work; Modal, SSH hosts, or Slurm and PBS clusters for GPUs and long jobs, approved before they run.

Reuse procedures Browse the bundled skills or add a workflow specific to your lab.

Extend it MCP servers, custom agents and commands, plugins, or the TypeScript SDK.

A skill describes a procedure; it does not mean every tool or service it references is installed. Check availability in Customize before a substantial task.

OpenScience ships ten bring-your-own-key adapters for NVIDIA BioNeMo NIM endpoints: Boltz-2, DiffDock, Evo 2, GenMol, MolMIM, MSA Search, OpenFold2, OpenFold3, ProteinMPNN and RFdiffusion. Each has a strict request schema, one approval per dispatch, and hashed artifacts written into the session; they are marked experimental and need your own NVIDIA API key under NVIDIA's service terms. The protein-binder-design skill is adapted from the NVIDIA BioNeMo Agent Toolkit (CC-BY-4.0 skills, Apache-2.0 code), pinned at commit 0e67a61. See Scientific tools and Service credentials.

your request → Research agent plans, then works step by step → tools: shell, Python/R kernels, files, search, connectors, compute → workers for bounded parallel tasks (explore, general, and five domain specialists) → answer, with the trace and the files it produced

Permissions. Choose how much to ask: always, only for risky actions, or full access. Network commands ask once per destination host. Files outside the project are read or written only with an explicit grant.

Working folder. A conversation works in the project's connected folder; caches and throwaway output stay in a per-session scratch space.

Publishing stays with you. git push, releases and uploads run from the lead session with this machine's own GitHub and Hugging Face logins; no token is ever asked for in chat.

The capability map, Explore tools and the skills directory list what is available and how to set it up.

Benchmark OpenScience

Terminal-Bench Science (70 tasks) 53/70 (75.7)

BiomniBench-DA (public 50) 82.2

Terminal-Bench 4.0, science subset (14 tasks) 0.714 (10/14)

GPT-6 Astra and GPT-6 Sol on Harbor, with each benchmark's native environments, verifiers and judge. The results, with the trace of every counted trial, are in benchmarks-openscience.

Option Setup Cost

Your provider An API key or a supported sign-in. Your provider's billing.

Local model Ollama, LM Studio or any compatible endpoint. Your hardware.

Ace Sign in, choose a workspace, fund its Wallet. Pay as you go at the Wallet rate shown for each model.

Ace has no subscription. Direct provider routes add no fee; models served through OpenRouter include its funding fee (5.5% by default), already counted in the displayed rate. The card processing fee is shown at checkout.

First-run setup asks you to sign in to an OpenScience account; headless openscience run does not. Model usage through your own keys or a local model is never charged to an Ace Wallet. Details are in Models, Local models and Pricing.

Topic Guides

First use Quickstart, Workspace, Workflow cookbook

Research Literature reviews, Data analysis, Reproduction, Writing

Capabilities Skills, Databases, Connectors

Control Permissions, Files, Project instructions, Configuration

Automate CLI reference, JSON output, SDK and editors

Help Troubleshooting, FAQ

The documentation is also available as plain text for agents: llms.txt and llms-full.txt.

backend/cli The openscience CLI and local server: sessions, tools, providers, skills frontend/workspace The browser workspace (SolidJS), embedded into the CLI at build time frontend/ui Shared components, themes and icons frontend/desktop The Electron shell and its signed self-updater frontend/docs The documentation site tooling/sdk The TypeScript SDK, generated from the server's OpenAPI contract tooling/plugin The plugin runtime docs/notes Engineering notes: verification, releases, how to add a skill, tool or connector

bun run setup # verify Bun, install, embed the workspace UI bun dev # run from source bun run check # format, typecheck and every unit suite

ARCHITECTURE.md explains how the pieces fit. CONTRIBUTING.md has the development loops, the checks that gate a pull request, and how to add a skill, connector, tool or plugin. AGENTS.md holds the conventions the code follows.

Stable releases are cut from main by the publish workflow after a full rehearsal at the same commit: packaged end-to-end tests, operating-system smokes and scientific capability canaries on every native platform. GitHub Releases carries the desktop installers, CLI archives and checksums; the changelog records what changed for users.

The desktop app updates itself. For the CLI, run openscience upgrade, or npm install -g @synsci/openscience@latest for an npm installation.

Bugs and feature requests: GitHub Issues. Use the templates; a good report has a reproduction.

Security: SECURITY.md. Please report vulnerabilities privately.

Conduct: CODE_OF_CONDUCT.md.

Billing and account questions: use the account support channel rather than a public issue.

Acknowledgements

OpenScience is inspired by OpenCode by Anomaly and shares its commitment to excellent open-source agents. We want to bring strong, open-source scientific agents to everyone.

Most of the bundled skills come from open collections written by other people:

backend/cli/skills/ATTRIBUTION.md lists every derived skill with its upstream path and license, and each skill's frontmatter names its original author. NOTICE carries the license texts.

Apache License 2.0. See LICENSE and NOTICE.

OpenScience is an independent project. It is not affiliated with, endorsed by, or sponsored by any model provider. Provider and model names are used only to describe compatibility.