Source profileQuality 91/100Review permissions

K-Dense-AI/scientific-agent-skills/skills/opentrons-integration/SKILL.md

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.

Source repository stars
31,966
Declared platforms
0
Static risk flags
1
Last source update
2026-07-28
Source checked
2026-07-28

Decision brief

What it does—and where it fits

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.

Best for

    Not for

    • Tasks that require unconfirmed production actions or broad system permissions.
    • Environments where the pinned source and install steps cannot be inspected.

    Compatibility matrix

    Platform support, with evidence labels

    PlatformStatusEvidenceWhat to check
    CodexNot declaredNo explicit evidencePortability before use
    Claude CodeNot declaredNo explicit evidencePortability before use
    CursorNot declaredNo explicit evidencePortability before use
    Gemini CLINot declaredNo explicit evidencePortability before use
    Open the compatibility checker

    Installation

    Inspect first. Install second.

    The source command is displayed only when detected. A safe inspection prompt is always available so your agent can explain every action before execution.

    Source-detected install commandSource
    npx skills add https://github.com/K-Dense-AI/scientific-agent-skills --skill "skills/opentrons-integration"
    Safe inspection promptEditorial

    Inspect the Agent Skill "opentrons-integration" from https://github.com/K-Dense-AI/scientific-agent-skills/blob/e7ac42510774624f327003c95b6650e2883bc01d/skills/opentrons-integration/SKILL.md at commit e7ac42510774624f327003c95b6650e2883bc01d. List every install step, command, network request, credential, file read/write, external action, and rollback step. Explain whether it fits my task. Do not install or execute anything until I approve.

    Workflow

    What the source asks the agent to do

    1. 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.

      2.20: CSV runtime parameters, liquid presence detection, expanded partial2.21: Absorbance Plate Reader.2.22: current labware-level liquid loading methods.
    2. 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.

      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…
    3. 03

      Safety Boundary

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

      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
    4. 04

      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
    5. 05

      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.

    Permission review

    Static risk signals and limitations

    Runs scripts

    medium · line 260

    The documentation asks the agent to run terminal commands or scripts.

    Inspect the run log for command count, tip changes, pauses, and unexpected

    Evidence record

    Why each signal appears

    EvidenceSourceComputedTestedEditorial
    SignalValueEvidence typeMeaning
    Quality score91/100ComputedDocumentation, specificity, maintenance, and trust rules
    Repository stars31,966SourceRepository attention, not individual Skill quality
    Compatibility0 platformsSourceDeclared in the catalog source record
    Usage guideautomated source guideEditorialGenerated or reviewed according to the visible evidence level

    Pinned source

    Provenance and original SKILL.md

    Repository
    K-Dense-AI/scientific-agent-skills
    Skill path
    skills/opentrons-integration/SKILL.md
    Commit
    e7ac42510774624f327003c95b6650e2883bc01d
    License
    MIT
    Collected
    2026-07-28
    Default branch
    main
    View the original SKILL.md

    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

    Alternatives

    Compare before choosing