k-dense-ai/opentrons-integration
Author, review, migrate, simulate, and troubleshoot official Opentrons Python Protocol API v2 protocols for Flex and OT-2 robots. Use for robot-specific liquid handling, deck and labware setup, pipettes, modules, runtime parameters, liquid classes, and Opentrons App analysis. Use pylabrobot instead when one workflow must support multiple robot vendors.
npx skills add https://github.com/K-Dense-AI/scientific-agent-skills --skill opentrons-integration
Create production-minded Python Protocol API v2 protocols for Opentrons Flex and
OT-2. This skill covers protocol structure, hardware and deck configuration,
liquid handling, runtime customization, module control, simulation, and safe
deployment.
The verified baseline as of 2026-07-23 is:
opentrons==9.1.1 for reproducible Flex simulation.opentrons==9.0.0 for local OT-2 API 2.28 compatibility simulation.2.29 in an OT-2 protocol.Read references/sources.md for the upstream documentation used for this
snapshot. Recheck the official versioning page before targeting newer robot
software.
Opentrons protocols control physical equipment. Never treat successful Python
syntax or local simulation as permission to run on a robot.
Before live execution:
opentrons version used for authoring.analysis.
definitions, deck fixtures, tip count, source volumes, dead volumes, and
destination capacity.
labware, partial tip pickup, or gripper moves are new.
chemical-safety, and contamination-control procedures.
Simulation cannot verify physical calibration, liquid properties, meniscus
behavior, labware manufacturing tolerances, cap or seal removal, tubing, or all
possible collisions.
Use this skill for Python files imported into the Opentrons App and run through
the Protocol API.
control is explicitly required, use the OpenAPI document served by the target
robot and do not infer endpoints from Protocol API methods.
Do not write final protocol code until these facts are known:
characteristics.
and total tips.
files.
plan.
If any physical configuration is uncertain, produce a parameterized draft and
an explicit assumptions list rather than guessing.
Flex:
uv run --with "opentrons==9.1.1" opentrons_simulate protocol.py
OT-2 API 2.28:
uv run --with "opentrons==9.0.0" opentrons_simulate protocol.py
The 9.1.1 package intentionally rejects OT-2 protocols after the Flex/OT-2
release-line split. Always complete OT-2 analysis in the current OT-2 App.
For a dedicated Flex environment:
uv venv --python 3.10
uv pip install --python .venv/bin/python -r skills/opentrons-integration/requirements-flex.txt
.venv/bin/opentrons_simulate protocol.py
Use requirements-ot2.txt instead for an OT-2 compatibility environment. On
Windows, invoke the executable from .venv\Scripts\opentrons_simulate.exe.
Local simulation is for Python protocols; import Protocol Designer JSON files
into the appropriate Opentrons App instead.
For Flex, requirements is mandatory. Put apiLevel only in requirements,
not in both metadata and requirements.
from opentrons import protocol_api
metadata = {
"protocolName": "Flex transfer",
"author": "Your Name",
"description": "Transfer buffer into a plate.",
}
requirements = {"robotType": "Flex", "apiLevel": "2.29"}
def run(protocol: protocol_api.ProtocolContext) -> None:
tips = protocol.load_labware(
"opentrons_flex_96_tiprack_200ul", "D1"
)
reservoir = protocol.load_labware("nest_12_reservoir_15ml", "D2")
plate = protocol.load_labware("nest_96_wellplate_200ul_flat", "C2")
protocol.load_trash_bin("A3")
pipette = protocol.load_instrument(
"flex_1channel_1000", "left", tip_racks=[tips]
)
pipette.transfer(
100,
reservoir["A1"],
plate["A1"],
new_tip="always",
)
For OT-2 API 2.15 and later, a requirements block is recommended. OT-2 has a
fixed trash in slot 12; do not call load_trash_bin().
from opentrons import protocol_api
metadata = {
"protocolName": "OT-2 transfer",
"author": "Your Name",
}
requirements = {"robotType": "OT-2", "apiLevel": "2.28"}
def run(protocol: protocol_api.ProtocolContext) -> None:
tips = protocol.load_labware("opentrons_96_tiprack_300ul", "1")
reservoir = protocol.load_labware("nest_12_reservoir_15ml", "2")
plate = protocol.load_labware("nest_96_wellplate_200ul_flat", "3")
pipette = protocol.load_instrument(
"p300_single_gen2", "left", tip_racks=[tips]
)
pipette.transfer(100, reservoir["A1"], plate["A1"])
Use the lowest API level that provides every required feature when a protocol
must run across a mixed software fleet. Use the current maximum only when the
workflow needs its behavior or capabilities.
Check the maximum supported API in the App under the robot's advanced settings.
Map every requested feature to its minimum API level using
references/api_reference.md.
Important gates:
nozzle layouts.
and tall-labware adjacency.
are part of the protocol's safety model.
See references/modules_and_deck.md.
Current load names are:
flex_1channel_50, flex_1channel_1000,flex_8channel_50, flex_8channel_1000,
flex_96channel_200, flex_96channel_1000.
p20_single_gen2, p20_multi_gen2,p300_single_gen2, p300_multi_gen2, p1000_single_gen2.
Check that every requested volume is within the configured pipette and tip
range. A 100 nL operation is not an Opentrons pipetting task.
aspirate(), dispense(), mix(), air_gap(), blow_out(), andtouch_tip() for explicit control.
transfer(), distribute(), and consolidate() for standard movements.transfer_with_liquid_class(),distribute_with_liquid_class(), or consolidate_with_liquid_class() for
Opentrons-verified aqueous, volatile, or viscous behavior.
dynamic_mix() only when API 2.27+ and thegeometry has been reviewed.
Model contamination boundaries before optimizing tips. Never reuse a tip across
unrelated samples merely to reduce consumables. See
references/liquid_handling.md.
Use define_liquid() and labware-level load_liquid() or
load_liquid_by_well() to improve setup visualization. Do not use deprecated
Well.load_liquid() in new API 2.22+ protocols.
Define operator-controlled values in add_parameters() and read them from
protocol.params. Validate ranges and use defaults that produce a safe,
meaningful simulation. CSV parameters have no default and only one CSV
parameter can be selected per run.
Before simulation, calculate:
volume + a justified reserve.
python -m py_compile protocol.py.locations.
setup, and labware offsets.
See references/validation_and_operations.md.
p300_single_flex; use current flex_* load names.apiLevel in both metadata and requirements.read(wavelengths=...) on the plate reader; call initialize() first,then read().
Well.load_liquid() instead of labware-level methods.clearances.
outside labware and cause a crash.
new_tip="once" across samples with incompatible contaminationrequirements.
| File | Purpose |
| --- | --- |
| scripts/basic_protocol_template.py | Minimal Flex 2.29 transfer with current names |
| scripts/ot2_basic_protocol_template.py | Minimal OT-2 2.28 transfer |
| scripts/serial_dilution_template.py | Full-plate 1:2 dilution with an 8-channel Flex pipette |
| scripts/pcr_setup_template.py | Flex PCR setup and Thermocycler cycling |
| scripts/runtime_parameters_template.py | Safe numeric and Boolean runtime parameters |
| scripts/absorbance_reader_template.py | Correct Flex plate-reader initialization and read workflow |
Templates are starting points, not validated assays. Replace volumes, labware,
liquids, timing, and tip policies only after checking hardware compatibility and
the wet-lab method.
| Reference | Use it for |
| --- | --- |
| references/api_reference.md | Current load names, version gates, and high-value methods |
| references/protocol_authoring.md | Requirements, labware, runtime parameters, and design workflow |
| references/liquid_handling.md | Command selection, liquid classes, sensing, and partial tips |
| references/modules_and_deck.md | Module compatibility, deck fixtures, gripper, and Stacker |
| references/validation_and_operations.md | Simulation, App analysis, dry runs, and troubleshooting |
| references/migration-api-2-19-to-2-29.md | Updating older protocols and this skill's former patterns |
| references/sources.md | Official documentation and release sources |
Take k-dense-ai/opentrons-integration from the repository into ~/.claude/skills for personal
use, or into .claude/skills inside a project.
The agent identifies a skill by the name field in its header. Two skills with the
same name cannot sit side by side — one of them will be ignored.
The instructions reference pip, uv.
Without those the skill loads but fails at the first command.