
Opentrons Integration
FreeStreamline protocol authoring for Opentrons robots.
Free · Opens the source repo
What Opentrons Integration does
The Opentrons Integration skill enables developers and researchers to create and manage Python Protocol API v2 protocols specifically for Opentrons Flex and OT-2 robots. This skill provides a comprehensive framework for protocol structure, hardware configuration, liquid handling, and runtime customization. With built-in support for simulation and deployment, users can ensure their protocols are production-ready before executing them on physical robots.
This skill is designed for those working in laboratory automation, particularly in life sciences and research environments where precision liquid handling is crucial. It offers a systematic approach to protocol authoring, allowing users to define robot specifications, pipette configurations, and labware setups with clarity. The skill emphasizes safety by requiring thorough simulation and verification processes before any live execution, ensuring that users can trust their protocols to perform as intended.
The Opentrons Integration skill also includes detailed references and templates that guide users through the protocol creation process. Users can leverage these resources to understand the nuances of different API levels and adapt their protocols accordingly. The skill is particularly useful for those who need to migrate protocols between different versions of the Opentrons API or require specific configurations for various labware and modules. By providing a structured environment for protocol development, this skill helps reduce errors and improve the efficiency of laboratory workflows.
When to use it
Use this skill when you need to create, simulate, and troubleshoot protocols for Opentrons Flex and OT-2 robots, particularly in a laboratory setting.
When not to use it
This skill is not suitable for users looking for a no-code solution or those needing to integrate protocols across multiple robot vendors; consider using PyLabRobot for broader compatibility.
What you can build with it
Creating a New Protocol
Use the skill to develop a new liquid handling protocol for an Opentrons robot, ensuring all parameters are correctly defined.
Simulating Protocols
Before executing a protocol on the robot, simulate it locally to verify its functionality and identify potential issues.
Migrating Existing Protocols
Leverage the skill to update and migrate existing protocols to comply with newer API versions, ensuring continued compatibility.
How to install Opentrons Integration
View source1. Install with the skills CLI
npx skills add k-dense-ai/scientific-agent-skills/opentrons-integration --agent claude-code2. Or install it manually
Download the skill folder and drop it into ~/.claude/skills/ for all projects, or .claude/skills/ to scope it to one repo. Restart Claude Code so it picks up the new skill.
Anthropic's agentic coding CLI, and the reference implementation of Agent Skills. Drop a skill folder into ~/.claude/skills and Claude Code loads it automatically whenever a task matches the skill's description. Claude Code docs
Inside SKILL.md
Written by k-dense-aiOpentrons Integration
Overview
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==9.1.1for reproducible Flex simulation.opentrons==9.0.0for local OT-2 API 2.28 compatibility simulation.- Flex supports API levels 2.15 through 2.29 on current software.
- OT-2 supports API levels 2.0 through 2.28 on current software.
- API 2.29 is Flex-only at this baseline. Do not put
2.29in 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.
Safety Boundary
Opentrons protocols control physical equipment. Never treat successful Python syntax or local simulation as permission to run on a robot.
Before live execution:
- Simulate locally with the same pinned
opentronsversion used for authoring. - Import the protocol into the correct Opentrons App and require successful analysis.
- Verify robot model, software, pipettes, mounts, modules, adapters, labware definitions, deck fixtures, tip count, source volumes, dead volumes, and destination capacity.
- Review the run preview and deck map with the operator.
- Perform a slow dry run with nonhazardous liquid when geometry, custom labware, partial tip pickup, or gripper moves are new.
- Keep the emergency stop accessible and follow site-specific biosafety, 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.
Choose the Right Interface
Use this skill for Python files imported into the Opentrons App and run through the Protocol API.
- Use Protocol Designer for supported no-code workflows.
- Use PyLabRobot for a hardware-agnostic workflow spanning vendors.
- Treat the robot's HTTP API as a separate integration surface. If direct HTTP control is explicitly required, use the OpenAPI document served by the target robot and do not infer endpoints from Protocol API methods.
Required Intake
Do not write final protocol code until these facts are known:
- Robot: Flex or OT-2, plus installed robot software.
- Pipette model, volume range, channel count, and mount.
- Modules and generations; Flex Gripper or Stacker availability.
- Exact labware API load names and custom definition files, if any.
- Deck fixtures: Flex trash bin, waste chute, staging slots, or Stackers.
- Source volumes, destination volumes, dead volume, mixing needs, and liquid characteristics.
- Tip policy: contamination boundaries, reuse policy, filters, partial pickup, and total tips.
- Operator interventions, incubation timing, runtime parameters, and output files.
- Acceptance criteria: tolerated volume error, required controls, and dry-run plan.
If any physical configuration is uncertain, produce a parameterized draft and an explicit assumptions list rather than guessing.
Install and Simulate
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.
Protocol Skeletons
Flex, API 2.29
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",
)
OT-2, API 2.28
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.
Authoring Workflow
1. Select robot and API level
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:
- 2.20: CSV runtime parameters, liquid presence detection, expanded partial nozzle layouts.
- 2.21: Absorbance Plate Reader.
- 2.22: current labware-level liquid loading methods.
- 2.23: meniscus locations and labware lids.
- 2.24: liquid classes and liquid-class complex commands.
- 2.25: Flex Stacker and Flex 96-Channel 200 µL pipette.
- 2.27: dynamic pipetting and concurrent module actions.
- 2.28: 20 µL Flex tips, improved partial-tip return, and thermocycler ramp rate.
- 2.29: step grouping; Flex only at the verified baseline.
2. Build the deck explicitly
- Use exact load names from the official Labware Library.
- Load Flex trash bins or the waste chute explicitly.
- Account for module footprints, staging slots, Stacker shuttles, gripper paths, and tall-labware adjacency.
- Load labware on adapters or module contexts in the documented order.
- Never substitute a similarly named labware definition; geometry and offsets are part of the protocol's safety model.
See references/modules_and_deck.md.
3. Select pipettes and tips
Current load names are:
- Flex:
flex_1channel_50,flex_1channel_1000,flex_8channel_50,flex_8channel_1000,flex_96channel_200,flex_96channel_1000. - OT-2 GEN2:
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.
4. Choose a liquid-handling layer
- Use
aspirate(),dispense(),mix(),air_gap(),blow_out(), andtouch_tip()for explicit control. - Use
transfer(),distribute(), andconsolidate()for standard movements. - On Flex, consider
transfer_with_liquid_class(),distribute_with_liquid_class(), orconsolidate_with_liquid_class()for Opentrons-verified aqueous, volatile, or viscous behavior. - Use dynamic start/end locations or
dynamic_mix()only when API 2.27+ and the geometry 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.
5. Add setup information and runtime controls
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.
6. Budget resources
Before simulation, calculate:
- Tips or tip sets required under every branch.
- Source volume = delivered volume + mixing loss + disposal volume + dead volume + a justified reserve.
- Maximum destination volume after every addition and mix.
- Number of module, adapter, trash, and staging positions.
- Incubation and module timing, including concurrent tasks.
7. Validate in layers
- Compile:
python -m py_compile protocol.py. - Simulate with the pinned package.
- Inspect the run log for command count, tip changes, pauses, and unexpected locations.
- Import into the appropriate App and require successful analysis.
- Check protocol visualization, runtime parameter defaults, deck map, module setup, and labware offsets.
- Perform an operator-reviewed dry run before first use.
See references/validation_and_operations.md.
Common Failure Modes
- Using old names such as
p300_single_flex; use currentflex_*load names. - Declaring
apiLevelin bothmetadataandrequirements. - Using API 2.29 for OT-2.
- Forgetting a Flex trash bin or waste chute.
- Loading a Magnetic Module on Flex; use supported Flex magnetic hardware.
- Calling
read(wavelengths=...)on the plate reader; callinitialize()first, thenread(). - Using deprecated
Well.load_liquid()instead of labware-level methods. - Assuming simulation verifies calibration, liquid height, or physical clearances.
- Passing an unsafe well to a partial-nozzle pipette, which can place tips outside labware and cause a crash.
- Using
new_tip="once"across samples with incompatible contamination requirements.
Bundled Templates
| 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 Guide
| 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 |
Frequently asked questions about Opentrons Integration
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