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Misc51k · #1949

pylabrobot

Helps your agent plan and review lab automation tasks. It's useful for those using robots in labs to ensure processes work well.

What it does

This tool helps create and review plans for lab automation using the PyLabRobot library. It allows simulating how lab robots handle liquids and interact with equipment, ensuring everything is done safely.

When to use it

  • ✓When planning experiments that require precise liquid handling by robots.
  • ✓To simulate and verify if a lab automation plan works before physically running it.
  • ✓When needing help understanding how to use the PyLabRobot library's functions to control lab equipment.

Example of what to ask your AI

“Create a lab automation plan to transfer 100 microliters from a tube to a plate well, using a simulated robot.”

Want more? Open the sections below.

How to use

The easiest way: copy the message below and paste it into Claude, ChatGPT, Cursor or any AI. It reads the skill and follows the instructions.

Skill link

https://github.com/K-Dense-AI/scientific-agent-skills/blob/main/skills/pylabrobot/SKILL.md

Ready-to-paste message

Use this skill to help me: https://github.com/K-Dense-AI/scientific-agent-skills/blob/main/skills/pylabrobot/SKILL.md Read the SKILL.md file at that link and follow its instructions for my task.
How it works

The tool uses the PyLabRobot library to define the equipment, containers (like tubes and plates), and actions to be performed. It can simulate these actions in a virtual environment or generate detailed instructions for a real robot, always prioritizing operator safety.

Installation

Easiest way: copy the skill link and paste it into Claude, ChatGPT or Cursor asking it to follow the instructions.

In the terminal (Claude Code, Codex, Cursor), in your project folder:

npx skills add K-Dense-AI/scientific-agent-skills --skill pylabrobot

Or download just the file:

curl -L https://raw.githubusercontent.com/K-Dense-AI/scientific-agent-skills/main/skills/pylabrobot/SKILL.md -o SKILL.md
Technical content (original SKILL.md)

Original text by the author, straight from GitHub.

PyLabRobot

Use PyLabRobot's hardware-agnostic frontends, resource tree, trackers, and device-specific backends to develop laboratory automation. Default to local manifest validation, bookkeeping, and the software-only chatterbox backend.

Verified snapshot

  • PyPI stable: PyLabRobot==0.2.2, released 2026-07-30.
  • Upstream requirement: Python >=3.9; runtime checks here used Python 3.13.
  • Hosted /stable/ pages mix 0.2.1 API pages with development documentation. GitHub has no v0.2.2 tag and its changelog has no 0.2.2 section. Use the released wheel/source distribution for the tested contract, not the URL label.
  • Released liquid-handler backends include STARBackend, VantageBackend, EVOBackend, OpentronsOT2Backend, and the software-only LiquidHandlerChatterboxBackend.
  • MicroSpin and Plate.stacking_z_height are present in 0.2.2, despite being listed under Unreleased in the current changelog. Newer development APIs, including the track= Hamilton deck keyword, are not this release.
  • See the release and transport review for source hashes, tested behavior, and the known OT-2 cancellation mismatch.

Non-negotiable hardware boundary

Never connect to, initialize, home, move, heat, shake, spin, pump, open/close, or otherwise command physical equipment automatically. Do not turn a simulation plan into a live backend merely by changing an environment variable, config value, or import.

Before any separately authorized live run, require a trained human to:

  1. Explicitly confirm the exact backend, device identity, firmware, transport, deck, and protocol revision.
  2. Reconcile the physical deck against the resource tree, including carriers, adapters, lids, plates, tip racks, waste, labware orientation, barcodes, and every occupied coordinate.
  3. Verify calibration, teaching, motion envelopes, collision risks, gripper or channel clearances, and all aspiration/dispense coordinates.
  4. Review source identity and actual fill volume, dead volume, destination capacity, tip type/capacity/filter compatibility, channel mapping, units, heights, rates, liquid class, blowout/mixing, and contamination boundaries.
  5. Confirm guards, doors, waste capacity, containment, emergency stop readiness, PPE, biosafety/chemical controls, and a safe abort/recovery procedure.
  6. Approve a slow dry run or nonhazardous commissioning run when anything is new or changed.

Tracker state is bookkeeping, not sensing. It cannot prove that liquid or a tip is physically present. After a backend error, tracker rollback describes software state; it does not reverse a physical aspiration, dispense, or tip movement that partly completed. Preserve the error/channel details and have the operator reconcile tips and source/destination volumes before resuming. Do not blindly retry the failed operation from the pre-error plan. The 0.2.2 liquid-handler implementation commits or rolls back trackers according to reported operation success. The Visualizer renders resource/tracker events; it does not model physics. Chatterbox prints planned operations; it does not prove calibration, reachability, collision freedom, liquid behavior, or device state.

Required intake

Do not guess any of these:

  • Exact device model, installed options, firmware, computer/OS, and transport.
  • Stable PyLabRobot version and required extras.
  • Deck/deck origin, carriers, adapters, resource definitions, dimensions, coordinates, orientations, and motion clearances.
  • Plate/tube/reservoir capacities and dead volumes; initial physical volumes.
  • Tip model, filter, fitting, capacity, rack state, channel count, and channel mapping.
  • Transfer units (uL, mm, uL/s, s), heights, rates, mixing, air gaps, blowout, liquid properties, and validated vendor liquid class.
  • Contamination policy, controls, waste handling, operator interventions, acceptance criteria, and recovery procedure.

If information is missing, produce an assumptions/blockers list and an offline draft only.

Reproducible install

For offline API inspection and chatterbox simulation:

uv venv --python 3.13 .venv-pylabrobot
uv pip install --python .venv-pylabrobot/bin/python "PyLabRobot==0.2.2"

On Windows, use .venv-pylabrobot\Scripts\python.exe. Do not install hardware extras until the user names the device and explicitly approves its transport

…

FAQ

What is PyLabRobot?

PyLabRobot is a software library that helps program laboratory robots to automate tasks, such as liquid handling.

Can I use this tool to control a real robot?

The tool is designed for simulation and planning first. To run on a real robot, a trained human operator must explicitly review and approve all safety steps.

What information do I need to provide?

You need to provide details about the equipment, containers (plates, tubes), liquids, quantities, and desired actions. The more details, the more accurate the simulation or plan will be.

Details

Original description by the author

Develops and reviews PyLabRobot lab-automation resources, liquid-handling plans, offline simulations, and supported-device integrations. Supports PyLabRobot protocols and API questions; keep physical execution behind an explicit operator safety gate.

repo: K-Dense-AI/scientific-agent-skills

Popularity

GitHub stars
51k
Ranking position
#1949
License
MIT
Updated
10/15/2026

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