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🎉 Recognition: Open Science Desktop ranks #1 by scored-task average on ResearchClawBench, an end-to-end benchmark for autonomous scientific research agents (Pass@1 leaderboard, July 9, 2026).

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Contents

• ✨ What it does
• 🎬 See it in action
• 🧪 Current capabilities
• 🔌 Skills and connectors
• 📦 Install
• 🚀 Build from source
• 🔒 Safety and privacy
• 🗂️ Repository layout
• 📌 Status
• 🤝 Contributing
• 📖 Citation
• ⚖️ License

What it does

Runs the whole research loop — from a broad direction to a finished paper: exploration, literature survey, hypothesis, experiment code, analysis, figures, and write-up, in one continuous, auditable session.

• Autonomous research agents — the bundled ai4s-agent chains specialist skills

end to end (explore → survey → experiment → write), and each stage drops a real, inspectable artifact into your workspace, not just a chat reply.

• Everything traces back — figures, tables, reports, notebooks, and run outputs

link to the exact code, inputs, environment, model output, and conversation that produced them.

• Local-first and yours — sessions, data, provenance, notebooks, and run records

live in local folders on your machine. Nothing leaves by default.

• Model-agnostic runtime — the UI talks through packages/sdk to a bundled,

pinned OpenCode sidecar. Bring your own model; providers, skills, and MCP servers stay pluggable.

• Reproducible by construction — local, SSH/Slurm, Modal, and notebook-batch runs

are captured as reproducible run records, not loose terminal scrollback.

• Extensible — agent skills, MCP servers and one-click science connectors,

/ commands, ! shell mode, and a model-agnostic SDK.

See it in action

One prompt -> a complete, traceable analysis. Simulate data, fit a model, save a publication-grade figure, and write a report where every number traces to the code.

Every artifact traces back to its code, inputs, and conversation.

Literature -> verifiable report. Search papers, draft a manuscript rendered as a PDF, and audit citations, unsourced numbers, and figure/code consistency.

More screenshots

Current capabilities

The research loop, as skills. One meta-skill runs the full pipeline; each stage is a self-contained skill that produces a real, gradeable artifact — runnable on any model OpenCode supports:

| Skill | Role | Primary output | | --- | --- | --- | | ai4s-agent | Runs the four skills below, in order | The full research package | | research-explorer | Turn a broad direction into concrete topics | researchexploration.md, topicmatrix.md, literaturepresurvey.md | | literature-survey | Write a literature survey | 6–20 pp PDF, 60+ real citations, LaTeX source, taxonomy figures | | experiment-suite | Build an experiment package | Design doc, runnable code, results.json with provenance, figures, report | | paper-writer | Write a research paper | 8–14 pp PDF, 200+ citations, 4–8 figures, tables | | mindmap-render | Render a mindmap | Image generated from a topic_matrix.md | | integrity-auditor | Audit a paper's integrity | Image / numerical / logical findings, 4-level evidence grading, audit_report.md |

These ship in the ai4s-skills pack alongside first-party review skills and the office/document skills below.

Platform

| Area | Current state | | --- | --- | | Desktop shell | Tauri 2 + React + TypeScript + Vite, with macOS, Windows, and Linux desktop builds. | | Runtime | Bundled OpenCode sidecar, auto-started by the app, isolated from the user's own OpenCode config/data. | | Sessions | Multi-session chat/history, dated workspace folders, global history across workspaces, / commands, and ! shell mode. | | Files | Global and per-session file browsing, context menu actions, external open/reveal, copy path, and local preview server. | | Notebooks | Real .ipynb files, Python and R notebook creation, local kernel execution, managed Jupyter environment via bundled uv, and an Open JupyterLab action. | | Runs | Append-only run logs, global SQLite run index, search/facets/pagination, local/remote surfaces, output links, logs, and reproduce prompts. | | Provenance | .openscience/provenance.jsonl tracks file versions and links produced artifacts back to the run or edit that created them. | | Review | Traceability, statistics-integrity, domain-check, large-file, publication-figure, remote-compute, and Modal run skills are bundled as first-party skills. | | Viewers | PDF, image, video, HTML, Markdown, code, CSV/TSV tables with charts, DOCX, XLSX, PPTX, molecules, 3D meshes, genome tracks, FITS, DOS/DOSCAR, EIGENVAL bands, qcode, anomaly maps, and phase files. | | Models | OpenCode provider catalog, OAuth/API-key provider flows, custom OpenAI-compatible endpoints, and local/provider-specific options supported by OpenCode. | | Interface languages | English, Simplified Chinese, Japanese, Spanish, German, French, and Korean. Portuguese (Brazil) and Arabic are registered but not selectable yet. |

Skills and connectors

Bundled skills are fetched for builds and releases instead of being committed into git history:

• ai4s-skills pack from ai4s-research/ai4s-skills.
• Office/document skills from the Apache-2.0 anthropics/skills repository:

docx, pdf, pptx, and xlsx.

• First-party core skills in runtime/skills/core/:

traceability-review, stats-integrity, domain-check, large-file, publication-figures, remote-compute, and modal-run.

One-click science MCP connectors currently include:

• Literature search: arXiv, PubMed, Crossref, Semantic Scholar, bioRxiv/medRxiv.
• Biomedical databases: PubMed, ClinicalTrials.gov, MyVariant/ClinVar.
• Materials Project.
• FRED economic data.
• Space weather.
• Open-Meteo weather and climate.
• USGS water data.

You can also add any local or remote MCP server from Settings. See docs/CONNECTYOUR_TOOLS.md.

For a neutral positioning note, see Open Science Desktop vs OpenScience.

Install

Download the latest installer from the Releases page.

• macOS: .dmg / .app, Apple Silicon and Intel, macOS 13 Ventura or later.
• Windows: NSIS .exe and .msi, Windows 10/11 x64.
• Linux: .deb and .rpm on x86_64 Linux.

Builds are not code-signed or notarized yet.

macOS: if Gatekeeper says the app is damaged or from an unidentified developer, install it into Applications and run:

xattr -cr "/Applications/Open Science.app"

Windows: if SmartScreen appears, choose More info -> Run anyway.

Linux:

sudo apt install ./OpenScience_*.deb
or
sudo rpm -i OpenScience_*.rpm

Build from source

Prerequisites:

• Node.js >= 20
• pnpm 9
• Rust toolchain
• macOS, Windows, or Linux system dependencies required by Tauri

git clone https://github.com/ai4s-research/open-science
cd open-science
pnpm install
Fetch pinned sidecars and bundled skills. These are git-ignored.
bash scripts/dev/fetch-opencode.sh
bash scripts/dev/fetch-uv.sh
bash scripts/dev/fetch-skills.sh
Run in development or build installers.
pnpm --filter @ai4s/desktop tauri dev
pnpm --filter @ai4s/desktop tauri build

Useful checks:

pnpm test
pnpm typecheck
pnpm lint

Safety and privacy

• Workspace files, raw data, session history, provenance, notebooks, and run records

stay local by default.

• Command execution, file deletion, dependency installation, and remote connections

are human-approved flows in the desktop app.

• Provider credentials are written to app-private runtime config, not to the

workspace, provenance, git, exports, or global OpenCode config.

• Settings includes a plain-language data-flow view explaining what can be sent to

the selected model provider.

Repository layout

| Path | Purpose | | --- | --- | | apps/desktop/ | Tauri + React desktop app. | | packages/sdk/ | OpenCodeClient; keeps the UI from calling OpenCode directly. | | packages/shared/ | Shared domain types and chart palette. | | packages/ui/ | Shared UI package. | | runtime/skills/core/ | First-party scientific skills. | | runtime/skills/external/ | Build-fetched external skills. | | runtime/harness/ | Runtime harness knowledge and operator context. | | runtime/mcp/ | MCP runtime notes/configuration. | | examples/ | Built-in example workspaces. | | scripts/dev/ | Sidecar, uv, skill fetchers, and focused regression probes. | | docs/ | Product, technical, operator, connector, and research notes. |

Status

The project is a working desktop MVP in active development. The most reliable current implementation log is PROGRESS.md. Product and architecture notes live in docs/PRD.md and docs/TECHNICAL_DESIGN.md, but those documents include target design as well as historical status notes.

Near-term work is focused on signed/notarized releases, broader Windows/Linux verification, auto-update, richer connector hardening, and continued reproducibility review.

Contributing

Issues and PRs are welcome. Keep changes minimal and verifiable, follow AGENTS.md, and run the checks before opening a PR. For discussion, join the Open Science Discord or the linux.do community.

Citation

If you use Open Science Desktop in your research, please cite it:

@software{opensciencedesktop,
  author  = {{The Open Science Desktop Contributors}},
  title   = {Open Science Desktop: a local-first, model-agnostic AI research workbench},
  year    = {2026},
  version = {0.1.9},
  url     = {https://github.com/ai4s-research/open-science},
  license = {MIT}
}

GitHub's "Cite this repository" button (top of the repo page, generated from CITATION.cff) provides the same reference in APA and BibTeX.

License

MIT. Bundled third-party skills and connectors keep their own licenses.

Open Science Desktop is beta research tooling. Treat outputs as drafts: verify numbers,

citations, code, and conclusions before publication or decision-making.