K-Dense-AI/scientific-agent-skills

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.

91CollectingRuns scripts
See how to use itView GitHub source
npx skills add https://github.com/K-Dense-AI/scientific-agent-skills --skill "skills/opentrons-integration"
Automated source guideReview and auditDeep source

Source checked Jul 28, 2026·Refresh due Oct 26, 2026

Reorganized from the pinned upstream SKILL.md

Source-grounded review guide: 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.

npx skills add https://github.com/K-Dense-AI/scientific-agent-skills --skill "skills/opentrons-integration"
Check the pinned source

The pinned source contains enough sections and task detail for a source-grounded deep guide; automated content is still not an independent test.

1,529 source words · 18 usable sections

Review inputs

  • Use defineliquid() and labware-level loadliquid() or loadliquidbywell() to improve setup visualization. Do not use deprecated Well.loadliquid() in new API 2.22+ protocols.
  • Define operator-controlled values in addparameters() 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 param…

Review workflow

Read opentrons-integration through these 5 source sections

Sections are extracted automatically from the pinned SKILL.md and link back to the source.

01

Authoring Workflow

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/apireference.md.

SKILL.md · Authoring Workflow
2.20: CSV runtime parameters, liquid presence detection, expanded partial2.21: Absorbance Plate Reader.2.22: current labware-level liquid loading methods.
02

5. Add setup information and runtime controls

Use defineliquid() and labware-level loadliquid() or loadliquidbywell() to improve setup visualization. Do not use deprecated Well.loadliquid() in new API 2.22+ protocols.

SKILL.md · 5. Add setup information and runtime controls
Use defineliquid() and labware-level loadliquid() or loadliquidbywell() to improve setup visualization. Do not use deprecated Well.loadliquid() in new API 2.22+ protocols.Define operator-controlled values in addparameters() 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 param…
03

Safety Boundary

Opentrons protocols control physical equipment. Never treat successful Python syntax or local simulation as permission to run on a robot.

SKILL.md · Safety Boundary
Simulate locally with the same pinned opentrons version used for authoring.Import the protocol into the correct Opentrons App and require successfulVerify robot model, software, pipettes, mounts, modules, adapters, labware
04

Choose the Right Interface

Use this skill for Python files imported into the Opentrons App and run through the Protocol API.

SKILL.md · Choose the Right Interface
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
05

Required Intake

Do not write final protocol code until these facts are known:

SKILL.md · Required Intake
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.

SkillSignal prompt templates

Provide the task, context, and acceptance criteria

These prompts were written by SkillSignal from the source structure; they are not upstream text.

Source-grounded prompt

Use for a review or audit task while explicitly checking the source sections.

Use opentrons-integration for this review or audit task: [task]. Inputs and constraints: [details]. Work through these pinned SKILL.md sections: “Authoring Workflow”, “5. Add setup information and runtime controls”, “Safety Boundary”, “Choose the Right Interface”, “Required Intake”. Cite the concrete requirements that shape each step, do not invent capabilities absent from the source, and verify the result against: [acceptance criteria].

Review checklist

Verify each item before delivery

The source section “Authoring Workflow” has been checked.

The source section “5. Add setup information and runtime controls” has been checked.

The source section “Safety Boundary” has been checked.

The source section “Choose the Right Interface” has been checked.

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Inspect the exact source lines that triggered a signal

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FAQ

What does the opentrons-integration source document cover?

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.

How do I install opentrons-integration?

The source record exposes this install command: npx skills add https://github.com/K-Dense-AI/scientific-agent-skills --skill "skills/opentrons-integration". Inspect the command and pinned source before running it.

Which permission-related actions were detected?

Static rules flagged exec-script in the source; the page lists the matching lines and excerpts.

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91/100
Documentation30/30
Specificity20/25
Maintenance20/20
Trust signals21/25

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View original Skill.mdThis page is parsed directly from the repository SKILL.md without editorial rewriting. Collected: Jul 28, 2026 · about 7 min

Opentrons 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==9.1.1 for reproducible Flex simulation.
  • opentrons==9.0.0 for 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 2.29 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.

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:

  1. Simulate locally with the same pinned opentrons version used for authoring.
  2. Import the protocol into the correct Opentrons App and require successful analysis.
  3. Verify robot model, software, pipettes, mounts, modules, adapters, labware definitions, deck fixtures, tip count, source volumes, dead volumes, and destination capacity.
  4. Review the run preview and deck map with the operator.
  5. Perform a slow dry run with nonhazardous liquid when geometry, custom labware, partial tip pickup, or gripper moves are new.
  6. 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(), and touch_tip() for explicit control.
  • Use transfer(), distribute(), and consolidate() for standard movements.
  • On Flex, consider transfer_with_liquid_class(), distribute_with_liquid_class(), or consolidate_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

  1. Compile: python -m py_compile protocol.py.
  2. Simulate with the pinned package.
  3. Inspect the run log for command count, tip changes, pauses, and unexpected locations.
  4. Import into the appropriate App and require successful analysis.
  5. Check protocol visualization, runtime parameter defaults, deck map, module setup, and labware offsets.
  6. 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 current flex_* load names.
  • Declaring apiLevel in both metadata and requirements.
  • 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; call initialize() first, then read().
  • 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

FilePurpose
scripts/basic_protocol_template.pyMinimal Flex 2.29 transfer with current names
scripts/ot2_basic_protocol_template.pyMinimal OT-2 2.28 transfer
scripts/serial_dilution_template.pyFull-plate 1:2 dilution with an 8-channel Flex pipette
scripts/pcr_setup_template.pyFlex PCR setup and Thermocycler cycling
scripts/runtime_parameters_template.pySafe numeric and Boolean runtime parameters
scripts/absorbance_reader_template.pyCorrect 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

ReferenceUse it for
references/api_reference.mdCurrent load names, version gates, and high-value methods
references/protocol_authoring.mdRequirements, labware, runtime parameters, and design workflow
references/liquid_handling.mdCommand selection, liquid classes, sensing, and partial tips
references/modules_and_deck.mdModule compatibility, deck fixtures, gripper, and Stacker
references/validation_and_operations.mdSimulation, App analysis, dry runs, and troubleshooting
references/migration-api-2-19-to-2-29.mdUpdating older protocols and this skill's former patterns
references/sources.mdOfficial documentation and release sources
Skill path
skills/opentrons-integration/SKILL.md
Commit SHA
e7ac42510774
Repository license
MIT
Data collected