### Pylabrobot
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name: "pylabrobot"
description: "Vendor-agnostic lab automation framework. Use when controlling multiple equipment types (Hamilton, Tecan, Opentrons, plate readers, pumps) or needing unified programming across different vendors. Best..."
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Before installing skills in Cursor, ensure your development environment meets these requirements:
node --versionpylabrobotExecute the skills CLI command in your project's root directory to begin installation:
Fetches pylabrobot from K-Dense-AI/scientific-agent-skills and configures it for Cursor.
The CLI shows a list of agents. Use arrow keys and space to select Cursor:
Confirm successful installation by checking the skill directory location:
Restart Cursor to activate pylabrobot. Access via /pylabrobot in your agent's command palette.
We perform automated surface-level scans (Gen AI Scanner, Socket, Snyk) during installation. These checks detect common vulnerabilities but do not guarantee complete security. Always review skill source code and verify the publisher's reputation before production use.
Skills execute code in your environment. Always review source, verify the publisher, and test in isolation before production.
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| name | pylabrobot |
| description | Vendor-agnostic lab automation framework. Use when controlling multiple equipment types (Hamilton, Tecan, Opentrons, plate readers, pumps) or needing unified programming across different vendors. Best for complex workflows, multi-vendor setups, simulation. For Opentrons-only protocols with official API, opentrons-integration may be simpler. |
| license | MIT license |
| metadata | version: "1.0" skill-author: K-Dense Inc. |
PyLabRobot is a hardware-agnostic, pure Python Software Development Kit for automated and autonomous laboratories. Use this skill to control liquid handling robots, plate readers, pumps, heater shakers, incubators, centrifuges, and other laboratory automation equipment through a unified Python interface that works across platforms (Windows, macOS, Linux).
Use this skill when:
PyLabRobot provides comprehensive laboratory automation through six main capability areas, each detailed in the references/ directory:
references/liquid-handling.md)Control liquid handling robots for aspirating, dispensing, and transferring liquids. Key operations include:
references/resources.md)Manage laboratory resources in a hierarchical system:
references/hardware-backends.md)Connect to diverse laboratory equipment through backend abstraction:
references/analytical-equipment.md)Integrate plate readers and analytical instruments:
references/material-handling.md)Control environmental and material handling equipment:
references/visualization.md)Visualize and simulate laboratory protocols:
To get started with PyLabRobot, install the package and initialize a liquid handler:
# Install PyLabRobot
# uv pip install pylabrobot
# Basic liquid handling setup
from pylabrobot.liquid_handling import LiquidHandler
from pylabrobot.liquid_handling.backends import STAR
from pylabrobot.resources import STARLetDeck
# Initialize liquid handler
lh = LiquidHandler(backend=STAR(), deck=STARLetDeck())
await lh.setup()
# Basic operations
await lh.pick_up_tips(tip_rack["A1:H1"])
await lh.aspirate(plate["A1"], vols=100)
await lh.dispense(plate["A2"], vols=100)
await lh.drop_tips()
This skill organizes detailed information across multiple reference files. Load the relevant reference when:
All reference files can be found in the references/ directory and contain comprehensive examples, API usage patterns, and best practices.
When creating laboratory automation protocols with PyLabRobot:
# Setup
lh = LiquidHandler(backend=STAR(), deck=STARLetDeck())
await lh.setup()
# Define resources
tip_rack = TIP_CAR_480_A00(name="tip_rack")
source_plate = Cos_96_DW_1mL(name="source")
dest_plate = Cos_96_DW_1mL(name="dest")
lh.deck.assign_child_resource(tip_rack, rails=1)
lh.deck.assign_child_resource(source_plate, rails=10)
lh.deck.assign_child_resource(dest_plate, rails=15)
# Transfer protocol
await lh.pick_up_tips(tip_rack["A1:H1"])
await lh.transfer(source_plate["A1:H12"], dest_plate["A1:H12"], vols=100)
await lh.drop_tips()
# Setup plate reader
from pylabrobot.plate_reading import PlateReader
from pylabrobot.plate_reading.clario_star_backend import CLARIOstarBackend
pr = PlateReader(name="CLARIOstar", backend=CLARIOstarBackend())
await pr.setup()
# Set temperature and read
await pr.set_temperature(37)
await pr.open()
# (manually or robotically load plate)
await pr.close()
data = await pr.read_absorbance(wavelength=450)
For detailed usage of specific capabilities, refer to the corresponding reference file in the references/ directory.
Prerequisites
Time Estimate
15-45 minutes depending on use case complexity
Steps
Common Pitfalls
✓ Do
✗ Don't
💡 Pro Tips
✓ Use when
Use when skill capabilities match your task, clear ROI on time saved, and you can validate outputs. Best for repetitive tasks, learning, and quality improvement.
✗ Avoid when
Avoid when task requires deep expertise you can't validate, involves sensitive decisions, or when learning process is more valuable than speed of completion.
K-Dense-AI/scientific-agent-skills
K-Dense-AI/scientific-agent-skills
K-Dense-AI/scientific-agent-skills
K-Dense-AI/scientific-agent-skills
google-deepmind/science-skills
google-deepmind/science-skills
pylabrobot reduced setup friction for our internal harness; good balance of opinion and flexibility.
Solid pick for teams standardizing on skills: pylabrobot is focused, and the summary matches what you get after install.
Registry listing for pylabrobot matched our evaluation — installs cleanly and behaves as described in the markdown.
Useful defaults in pylabrobot — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.
We added pylabrobot from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.
pylabrobot is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.
Registry listing for pylabrobot matched our evaluation — installs cleanly and behaves as described in the markdown.
pylabrobot has been reliable in day-to-day use. Documentation quality is above average for community skills.
pylabrobot reduced setup friction for our internal harness; good balance of opinion and flexibility.
We added pylabrobot from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.
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