### Opentrons Integration
Works with
name: "opentrons-integration"
description: "Official Opentrons Protocol API for OT-2 and Flex robots. Use when writing protocols specifically for Opentrons hardware with full access to Protocol API v2 features. Best for production Opentrons pro..."
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node --versionopentrons-integrationExecute the skills CLI command in your project's root directory to begin installation:
Fetches opentrons-integration from K-Dense-AI/scientific-agent-skills and configures it for Cursor.
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Confirm successful installation by checking the skill directory location:
Restart Cursor to activate opentrons-integration. Access via /opentrons-integration in your agent's command palette.
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| name | opentrons-integration |
| description | Official Opentrons Protocol API for OT-2 and Flex robots. Use when writing protocols specifically for Opentrons hardware with full access to Protocol API v2 features. Best for production Opentrons protocols, official API compatibility. For multi-vendor automation or broader equipment control use pylabrobot. |
| license | Unknown |
| metadata | version: "1.0" skill-author: K-Dense Inc. |
Opentrons is a Python-based lab automation platform for Flex and OT-2 robots. Write Protocol API v2 protocols for liquid handling, control hardware modules (heater-shaker, thermocycler), manage labware, for automated pipetting workflows.
This skill should be used when:
Every Opentrons protocol follows a standard structure:
from opentrons import protocol_api
# Metadata
metadata = {
'protocolName': 'My Protocol',
'author': 'Name <[email protected]>',
'description': 'Protocol description',
'apiLevel': '2.19' # Use latest available API version
}
# Requirements (optional)
requirements = {
'robotType': 'Flex', # or 'OT-2'
'apiLevel': '2.19'
}
# Run function
def run(protocol: protocol_api.ProtocolContext):
# Protocol commands go here
pass
Key elements:
protocol_api from opentronsmetadata dict with protocolName, author, description, apiLevelrequirements dict for robot type and API versionrun() function receiving ProtocolContext as parameterrun() functionLoading Instruments (Pipettes):
def run(protocol: protocol_api.ProtocolContext):
# Load pipette on specific mount
left_pipette = protocol.load_instrument(
'p1000_single_flex', # Instrument name
'left', # Mount: 'left' or 'right'
tip_racks=[tip_rack] # List of tip rack labware objects
)
Common pipette names:
p50_single_flex, p1000_single_flex, p50_multi_flex, p1000_multi_flexp20_single_gen2, p300_single_gen2, p1000_single_gen2, p20_multi_gen2, p300_multi_gen2Loading Labware:
# Load labware directly on deck
plate = protocol.load_labware(
'corning_96_wellplate_360ul_flat', # Labware API name
'D1', # Deck slot (Flex: A1-D3, OT-2: 1-11)
label='Sample Plate' # Optional display label
)
# Load tip rack
tip_rack = protocol.load_labware('opentrons_flex_96_tiprack_1000ul', 'C1')
# Load labware on adapter
adapter = protocol.load_adapter('opentrons_flex_96_tiprack_adapter', 'B1')
tips = adapter.load_labware('opentrons_flex_96_tiprack_200ul')
Loading Modules:
# Temperature module
temp_module = protocol.load_module('temperature module gen2', 'D3')
temp_plate = temp_module.load_labware('corning_96_wellplate_360ul_flat')
# Magnetic module
mag_module = protocol.load_module('magnetic module gen2', 'C2')
mag_plate = mag_module.load_labware('nest_96_wellplate_100ul_pcr_full_skirt')
# Heater-Shaker module
hs_module = protocol.load_module('heaterShakerModuleV1', 'D1')
hs_plate = hs_module.load_labware('corning_96_wellplate_360ul_flat')
# Thermocycler module (takes up specific slots automatically)
tc_module = protocol.load_module('thermocyclerModuleV2')
tc_plate = tc_module.load_labware('nest_96_wellplate_100ul_pcr_full_skirt')
Basic Operations:
# Pick up tip
pipette.pick_up_tip()
# Aspirate (draw liquid in)
pipette.aspirate(
volume=100, # Volume in µL
location=source['A1'] # Well or location object
)
# Dispense (expel liquid)
pipette.dispense(
volume=100,
location=dest['B1']
)
# Drop tip
pipette.drop_tip()
# Return tip to rack
pipette.return_tip()
Complex Operations:
# Transfer (combines pick_up, aspirate, dispense, drop_tip)
pipette.transfer(
volume=100,
source=source_plate['A1'],
dest=dest_plate['B1'],
new_tip='always' # 'always', 'once', or 'never'
)
# Distribute (one source to multiple destinations)
pipette.distribute(
volume=50,
source=reservoir['A1'],
dest=[plate['A1'], plate['A2'], plate['A3']],
new_tip='once'
)
# Consolidate (multiple sources to one destination)
pipette.consolidate(
volume=50,
source=[plate['A1'], plate['A2'], plate['A3']],
dest=reservoir['A1'],
new_tip='once'
)
Advanced Techniques:
# Mix (aspirate and dispense in same location)
pipette.mix(
repetitions=3,
volume=50,
location=plate['A1']
)
# Air gap (prevent dripping)
pipette.aspirate(100, source['A1'])
pipette.air_gap(20) # 20µL air gap
pipette.dispense(120, dest['A1'])
# Blow out (expel remaining liquid)
pipette.blow_out(location=dest['A1'].top())
# Touch tip (remove droplets on tip exterior)
pipette.touch_tip(location=plate['A1'])
Flow Rate Control:
# Set flow rates (µL/s)
pipette.flow_rate.aspirate = 150
pipette.flow_rate.dispense = 300
pipette.flow_rate.blow_out = 400
Well Access Methods:
# By name
well_a1 = plate['A1']
# By index
first_well = plate.wells()[0]
# All wells
all_wells = plate.wells() # Returns list
# By rows
rows = plate.rows() # Returns list of lists
row_a = plate.rows()[0] # All wells in row A
# By columns
columns = plate.columns() # Returns list of lists
column_1 = plate.columns()[0] # All wells in column 1
# Wells by name (dictionary)
wells_dict = plate.wells_by_name() # {'A1': Well, 'A2': Well, ...}
Location Methods:
# Top of well (default: 1mm below top)
pipette.aspirate(100, well.top())
pipette.aspirate(100, well.top(z=5)) # 5mm above top
# Bottom of well (default: 1mm above bottom)
pipette.aspirate(100, well.bottom())
pipette.aspirate(100, well.bottom(z=2)) # 2mm above bottom
# Center of well
pipette.aspirate(100, well.center())
Temperature Module:
# Set temperature
temp_module.set_temperature(celsius=4)
# Wait for temperature
temp_module.await_temperature(celsius=4)
# Deactivate
temp_module.deactivate()
# Check status
current_temp = temp_module.temperature # Current temperature
target_temp = temp_module.target # Target temperature
Magnetic Module:
# Engage (raise magnets)
mag_module.engage(height_from_base=10) # mm from labware base
# Disengage (lower magnets)
mag_module.disengage()
# Check status
is_engaged = mag_module.status # 'engaged' or 'disengaged'
Heater-Shaker Module:
# Set temperature
hs_module.set_target_temperature(celsius=37)
# Wait for temperature
hs_module.wait_for_temperature()
# Set shake speed
hs_module.set_and_wait_for_shake_speed(rpm=500)
# Close labware latch
hs_module.close_labware_latch()
# Open labware latch
hs_module.open_labware_latch()
# Deactivate heater
hs_module.deactivate_heater()
# Deactivate shaker
hs_module.deactivate_shaker()
Thermocycler Module:
# Open lid
tc_module.open_lid()
# Close lid
tc_module.close_lid()
# Set lid temperature
tc_module.set_lid_temperature(celsius=105)
# Set block temperature
tc_module.set_block_temperature(
temperature=95,
hold_time_seconds=30,
hold_time_minutes=0.5,
block_max_volume=50 # µL per well
)
# Execute profile (PCR cycling)
profile = [
{'temperature': 95, 'hold_time_seconds': 30},
{'temperature': 57, 'hold_time_seconds': 30},
{'temperature': 72, 'hold_time_seconds': 60}
]
tc_module.execute_profile(
steps=profile,
repetitions=30,
block_max_volume=50
)
# Deactivate
tc_module.deactivate_lid()
tc_module.deactivate_block()
Absorbance Plate Reader:
# Initialize and read
result = plate_reader.read(wavelengths=[450, 650])
# Access readings
absorbance_data = result # Dict with wavelength keys
Define Liquids:
# Define liquid types
water = protocol.define_liquid(
name='Water',
description='Ultrapure water',
display_color='#0000FF' # Hex color code
)
sample = protocol.define_liquid(
name='Sample',
description='Cell lysate sample',
display_color='#FF0000'
)
Load Liquids into Wells:
# Load liquid into specific wells
reservoir['A1'].load_liquid(liquid=water, volume=50000) # µL
plate['A1'].load_liquid(liquid=sample, volume=100)
# Mark wells as empty
plate['B1'].load_empty()
Execution Control:
# Pause protocol
protocol.pause(msg='Replace tip box and resume')
# Delay
protocol.delay(seconds=60)
protocol.delay(minutes=5)
# Comment (appears in logs)
protocol.comment('Starting serial dilution')
# Home robot
protocol.home()
Conditional Logic:
# Check if simulating
if protocol.is_simulating():
protocol.comment('Running in simulation mode')
else:
protocol.comment('Running on actual robot')
Rail Lights (Flex only):
# Turn lights on
protocol.set_rail_lights(on=True)
# Turn lights off
protocol.set_rail_lights(on=False)
When using multi-channel pipettes:
# Load 8-channel pipette
multi_pipette = protocol.load_instrument(
'p300_multi_gen2',
'left',
tip_racks=[tips]
)
# Access entire column with single well reference
multi_pipette.transfer(
volume=100,
source=source_plate['A1'], # Accesses entire column 1
dest=dest_plate['A1'] # Dispenses to entire column 1
)
# Use rows() for row-wise operations
for row in plate.rows():
multi_pipette.transfer(100, reservoir['A1'], row[0])
Serial Dilution:
def run(protocol: protocol_api.ProtocolContext):
# Load labware
tips = protocol.load_labware('opentrons_flex_96_tiprack_200ul', 'D1')
reservoir = protocol.load_labware('nest_12_reservoir_15ml', 'D2')
plate = protocol.load_labware('corning_96_wellplate_360ul_flat', 'D3')
# Load pipette
p300 = protocol.load_instrument('p300_single_flex', 'left', tip_racks=[tips])
# Add diluent to all wells except first
p300.transfer(100, reservoir['A1'], plate.rows()[0][1:])
# Serial dilution across row
p300.transfer(
100,
plate.rows()[0][:11], # Source: wells 0-10
plate.rows()[0][1:], # Dest: wells 1-11
mix_after=(3, 50), # Mix 3x with 50µL after dispense
new_tip='always'
)
Plate Replication:
def run(protocol: protocol_api.ProtocolContext):
# Load labware
tips = protocol.load_labware('opentrons_flex_96_tiprack_1000ul', 'C1')
source = protocol.load_labware('corning_96_wellplate_360ul_flat', 'D1')
dest = protocol.load_labware('corning_96_wellplate_360ul_flat', 'D2')
# Load pipette
p1000 = protocol.load_instrument('p1000_single_flex', 'left', tip_racks=[tips])
# Transfer from all wells in source to dest
p1000.transfer(
100,
source.wells(),
dest.wells(),
new_tip='always'
)
PCR Setup:
def run(protocol: protocol_api.ProtocolContext):
# Load thermocycler
tc_mod = protocol.load_module('thermocyclerModuleV2')
tc_plate = tc_mod.load_labware('nest_96_wellplate_100ul_pcr_full_skirt')
# Load tips and reagents
tips = protocol.load_labware('opentrons_flex_96_tiprack_200ul', 'C1')
reagents = protocol.load_labware('opentrons_24_tuberack_nest_1.5ml_snapcap', 'D1')
# Load pipette
p300 = protocol.load_instrument('p300_single_flex', 'left', tip_racks=[tips])
# Open thermocycler lid
tc_mod.open_lid()
# Distribute master mix
p300.distribute(
20,
reagents['A1'],
tc_plate.wells(),
new_tip='once'
)
# Add samples (example for first 8 wells)
for i, well in enumerate(tc_plate.wells()[:8]):
p300.transfer(5, reagents.wells()[i+1], well, new_tip='always')
# Run PCR
tc_mod.close_lid()
tc_mod.set_lid_temperature(105)
# PCR profile
tc_mod.set_block_temperature(95, hold_time_seconds=180)
profile = [
{'temperature': 95, 'hold_time_seconds': 15},
{'temperature': 60, 'hold_time_seconds': 30},
{'temperature': 72, 'hold_time_seconds': 30}
]
tc_mod.execute_profile(steps=profile, repetitions=35, block_max_volume=25)
tc_mod.set_block_temperature(72, hold_time_minutes=5)
tc_mod.set_block_temperature(4)
tc_mod.deactivate_lid()
tc_mod.open_lid()
protocol.comment() for debugging and loggingnew_tip='once' when appropriate to save tipsCommon Issues:
For detailed API documentation, see references/api_reference.md in this skill directory.
For example protocol templates, see scripts/ 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
Solid pick for teams standardizing on skills: opentrons-integration is focused, and the summary matches what you get after install.
Keeps context tight: opentrons-integration is the kind of skill you can hand to a new teammate without a long onboarding doc.
opentrons-integration has been reliable in day-to-day use. Documentation quality is above average for community skills.
opentrons-integration reduced setup friction for our internal harness; good balance of opinion and flexibility.
opentrons-integration is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.
Useful defaults in opentrons-integration — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.
opentrons-integration is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.
opentrons-integration reduced setup friction for our internal harness; good balance of opinion and flexibility.
We added opentrons-integration from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.
Registry listing for opentrons-integration matched our evaluation — installs cleanly and behaves as described in the markdown.
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