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AD-SDLAD-SDLOfficial·2 Agent Skills Included

MADSci

Modular framework for autonomous laboratory automation and experiments

Automates scientific laboratories by connecting instruments, robots, and sensors through a common node standard. Coordinates workflows, experiments, resources, locations, data, and events across distributed lab services. Eliminates manual lab tracking and one-off instrument scripts with ready-made managers, clients, templates, and a monitoring dashboard.
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npx skills add AD-SDL/MADSci --all -g -y
Available:

Tells the AI agent how the MADSci monorepo is structured, which commands to run for testing and services, and which coding patterns (ULIDs, Pydantic models, settings discovery) to follow when working on lab automation code.

All Skills in This Repository (2)

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code-ratchets

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galahad

Enforce strict tests, types, lints, and coverage standards across TypeScript and Python projects.

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Frequently Asked Questions

FAQPage Schema
How to install MADSci?▼

Run `npx skills add AD-SDL/MADSci --all -g -y` in your terminal to install all skills in this suite globally.

What is MADSci used for?▼

MADSci is a Python framework for building autonomous laboratories. It connects lab instruments as nodes, schedules multi-step workflows, tracks samples and consumables, and stores experimental data in one coordinated system.

How do I connect a lab instrument to MADSci?▼

You create a node module by subclassing RestNode and marking instrument actions with the @action decorator. The node then exposes a standard REST API that the workcell manager can schedule and control.

Does MADSci work with Docker?▼

Yes. MADSci ships pre-built Docker images and compose files, so you can start a full example lab with all manager services using a single docker compose command.

Can I monitor my lab in real time?▼

Yes. MADSci includes a web dashboard and a terminal UI that show live node status, running workflows, resource inventory, and event logs across the whole lab.

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