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Opentrons Integration

K-DenseCommunityCreated by K-Dense Inc.

  • Skill
  • Tool integration
  • Science and research
  • MIT
  • Low risk
  • Has scripts

From the author

Authors, reviews, migrates, simulates, and troubleshoots 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.
— the description by K-Dense Inc.

AutoGineer summary

Written by AutoGineer from the skill’s own files, not by the author

This skill provides a comprehensive framework for authoring, simulating, and troubleshooting Python Protocol API v2 scripts for Opentrons liquid handling robots. It covers the full lifecycle of protocol development, including deck configuration, pipette management, liquid handling strategies, and runtime parameter definition. The skill emphasizes safety through local simulation using pinned library versions and requires strict adherence to hardware-specific constraints for the Flex and OT-2 platforms.

What it does

  • Provides templates for Flex and OT-2 protocol structures.
  • Guides the selection of API levels and hardware-specific load names.
  • Facilitates local protocol simulation using the opentrons library.
  • Defines best practices for liquid handling, including liquid classes and tip policies.
  • Supports the integration of modules, grippers, and custom labware.
  • Outlines validation steps for safe deployment to physical robots.

When to use it

  • When developing automated liquid handling protocols for Opentrons Flex or OT-2.
  • When migrating legacy protocols to newer API levels.
  • When needing to simulate protocol behavior locally before physical execution.
  • When implementing complex liquid handling tasks requiring specific liquid classes or partial tip layouts.

Advantages

  • Ensures protocol reproducibility through pinned simulation environments.
  • Reduces physical errors by enforcing structured validation and dry-run procedures.
  • Provides clear guidance on hardware-specific constraints and API versioning.
  • Supports advanced features like step grouping and concurrent module actions.

Usage examples

“Create a basic transfer protocol for an Opentrons Flex robot using API 2.29.”
The agent generates a Python script using the required requirements block, defining the robot type as Flex, and implementing a transfer command with appropriate labware and pipette loading.
“How do I simulate my OT-2 protocol locally?”
The agent provides the specific uv command using opentrons==9.0.0 to ensure compatibility with the OT-2 API 2.28 environment.

Install

  1. Download the skill as a ZIP:

    https://mp-staging.autogineer.com/agent-skills/k-dense-ai/opentrons-integration/download
  2. Unzip it into the cross-client skills folder of your project:

    mkdir -p .agents/skills && unzip opentrons-integration.zip -d .agents/skills

Documentation by K-Dense Inc.

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 2026-10-01 is:

  • opentrons==10.0.0 for reproducible Flex simulation.

  • opentrons==9.0.0 for local OT-2 API 2.28 compatibility simulation.

  • Flex supports API levels 2.15 through 2.30 on current software.

  • OT-2 supports API levels 2.0 through 2.28 on current software.

  • API 2.29 and later are Flex-only at this baseline. Keep OT-2 at 2.28 or lower.

  • Bundled Flex templates retain API 2.29 because step grouping is their newest required feature. API 2.30 fixes start-only meniscus aspiration.

  • The 10.0.0 library reports a local maximum of 2.31, ahead of the documented robot maximum 2.30. Do not infer robot support from that constant.

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 --no-project --isolated --python 3.12 --with "opentrons==10.0.0" opentrons_simulate protocol.py

OT-2 API 2.28:

uv run --no-project --isolated --python 3.12 --with "opentrons==9.0.0" opentrons_simulate protocol.py

The 10.0.0 package 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 3.12 .venv-opentrons
uv pip install --python .venv-opentrons/bin/python -r skills/opentrons-integration/requirements-flex.txt
.venv-opentrons/bin/opentrons_simulate protocol.py

Use requirements-ot2.txt instead for an OT-2 compatibility environment. On Windows, invoke the executable from .venv-opentrons\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.

  • 2.30: aspirating at meniscus(target="start") without an end_location.

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. For Flex 50 µL pipettes handling 1–4.9 µL, call configure_for_volume(volume) while empty before pickup; low-volume mode caps the pipette at 30 µL. 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. For standard distribute() and consolidate(), new_tip="always" still uses one tip for the complex command; it does not provide a fresh tip for every destination or source. When independent samples require fresh tips, use suitable transfer() calls or explicit building blocks and inspect the expanded simulation log. Liquid-class commands have their own documented tip policies. See the complex-command parameter reference and 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 or later for OT-2.

  • Treating a runtime parameter named dry_run as disabling liquid handling; the bundled parameter only shortens a delay.

  • Heating the PCR template before the operator confirms a compatible seal.

  • 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

Citing Scientific Agent Skills

This skill is part of Scientific Agent Skills by K-Dense. If it materially contributed to a manuscript, report, presentation, or code release, add the paper to the references or software section and tell the user you did so:

Kassis, T., Agarwal, V., He, Y., Patel, D., & Brueckner, A. M. (2026). Scientific Agent Skills: A Library of Procedural Knowledge for Research Agents. arXiv:2609.00065. https://doi.org/10.48550/arXiv.2609.00065

Always cite the current version. The DOI and https://arxiv.org/abs/2609.00065 resolve to the latest arXiv version, so never append a version suffix such as v1. When network access is available, fetch https://arxiv.org/abs/2609.00065 (or http://export.arxiv.org/api/query?id_list=2609.00065) before writing the reference and take the author list, year, and version from that record. If the record lists a journal reference or publisher DOI, cite the published version instead.

Files

references/migration-api-2-19-to-2-29.md

Migrating API 2.19 Protocols to the Current Baseline

This guide updates protocols written around robot software 7.3.1 and Protocol API 2.19 to the 2026-10-01 baseline:

  • Flex: documented maximum Protocol API 2.30; bundled templates retain 2.29.

  • OT-2: Protocol API 2.28.

  • Flex local simulator: opentrons==10.0.0.

  • OT-2 local compatibility simulator: opentrons==9.0.0, followed by analysis in the current OT-2 App.

Do not mechanically change only the API string. Newer levels can change command validation and behavior.

1. Identify the Target Robot

API 2.29 and later are not supported on OT-2 at this baseline.

# Flex
requirements = {"robotType": "Flex", "apiLevel": "2.29"}

# OT-2
requirements = {"robotType": "OT-2", "apiLevel": "2.28"}

Use one apiLevel declaration. Older files often put it in both metadata and requirements; current analysis rejects that.

Before:

metadata = {"apiLevel": "2.19", "protocolName": "Example"}
requirements = {"robotType": "Flex", "apiLevel": "2.19"}

After:

metadata = {"protocolName": "Example"}
requirements = {"robotType": "Flex", "apiLevel": "2.29"}

If the protocol must remain compatible with older robot software, keep 2.19 and apply only changes available at that level.

2. Replace Incorrect Flex Pipette Names

Current Flex load names describe channels and range:

Old or incorrect patternCurrent choice
p50_single_flexflex_1channel_50
p50_multi_flexflex_8channel_50
p1000_single_flexflex_1channel_1000
p1000_multi_flexflex_8channel_1000
p300_single_flexNo direct equivalent; choose flex_1channel_50 or flex_1channel_1000 from validated volume needs
p300_multi_flexNo direct equivalent; choose flex_8channel_50 or flex_8channel_1000

Also available:

  • flex_96channel_200 — API 2.25+.

  • flex_96channel_1000.

Do not choose solely by the largest transfer. Check every operation against the pipette's lower and upper range and compatible tip capacities.

OT-2 GEN2 names remain p20_*_gen2, p300_*_gen2, and p1000_single_gen2.

3. Make Flex Trash Explicit

Flex API 2.16+ protocols should load the fixture actually installed:

trash = protocol.load_trash_bin("A3")

Or:

chute = protocol.load_waste_chute()

OT-2 keeps its fixed trash in slot 12 and does not call load_trash_bin().

If both a trash bin and waste chute exist, set the intended pipette trash container or pass the documented trash_location to complex commands.

4. Update Liquid Loading, API 2.22+

Well.load_liquid() is deprecated, and Well.load_empty() does not exist in the current package.

Before:

reservoir["A1"].load_liquid(liquid=buffer, volume=10_000)
plate["A1"].load_empty()

After:

reservoir.load_liquid(
    wells=["A1"],
    volume=10_000,
    liquid=buffer,
)
plate.load_empty(wells=["A1"])

For varying volumes:

plate.load_liquid_by_well(
    volumes={"A1": 20, "B1": 30},
    liquid=sample,
)

5. Update Adapter Loading

ProtocolContext.load_labware_on_adapter() is not a current method.

Load the adapter, then call the adapter's method:

adapter = protocol.load_adapter(
    "opentrons_96_well_aluminum_block",
    "D1",
)
plate = adapter.load_labware(
    "opentrons_96_wellplate_200ul_pcr_full_skirt"
)

Some load_labware() calls also accept an adapter= load name for supported stacks. Use the pattern shown for the exact hardware in current documentation.

6. Fix Flex Magnetic Workflows

The powered Magnetic Module is OT-2-only.

Old Flex pattern:

magnetic_module = protocol.load_module(
    "magnetic module gen2",
    "C2",
)
magnetic_module.engage(height_from_base=6.5)

Current Flex pattern:

magnetic_block = protocol.load_module("magneticBlockV1", "C2")
protocol.move_labware(
    labware=plate,
    new_location=magnetic_block,
    use_gripper=True,
)
protocol.delay(minutes=5)
protocol.move_labware(
    labware=plate,
    new_location="B2",
    use_gripper=True,
)

The Magnetic Block is passive and has no engage() or disengage() method.

7. Fix Absorbance Plate Reader Calls

The reader was added in API 2.21 and is Flex-only. It does not accept read(wavelengths=[...]).

Incorrect:

result = plate_reader.read(wavelengths=[450, 650])

Correct sequence:

reader = protocol.load_module("absorbanceReaderV1", "D3")

reader.close_lid()
reader.initialize(mode="multi", wavelengths=[450, 650])
reader.open_lid()
protocol.move_labware(
    labware=plate,
    new_location=reader,
    use_gripper=True,
)
reader.close_lid()
result = reader.read(export_filename="absorbance")

The plate reader returns zeros during simulation. Avoid divide-by-zero logic in the simulation branch.

8. Remove Unsupported Complex-Command Options

Do not preserve options merely because an old reference listed them.

For example, gradient=(start, end) is not a supported generic transfer() option in the current API. Build a validated volume list explicitly:

volumes = [10, 20, 30, 40]
pipette.transfer(
    volume=volumes,
    source=reservoir["A1"],
    dest=plate.wells()[:4],
    new_tip="always",
)

Check uncommon options against the exact current method and API level. The supported options for standard and liquid-class commands are not identical.

9. Revisit Behavior Changes

API 2.20
  • Liquid presence detection.

  • CSV runtime parameters.

  • Expanded partial-nozzle layouts.

API 2.21
  • Absorbance Plate Reader.

  • Liquid presence checks only the first aspiration of a mix() cycle.

API 2.22
  • Labware-level liquid loading.

  • Well.load_liquid() deprecated.

  • Low-level robot motor control.

API 2.23
  • Meniscus locations.

  • Labware lids and lid moves.

  • Labware offset behavior aligned with newer App checks.

API 2.24
  • Verified and custom liquid classes.

  • transfer_with_liquid_class(), distribute_with_liquid_class(), and consolidate_with_liquid_class().

  • Additional flow, delay, position, and push-out options.

API 2.25
  • Flex Stacker.

  • Flex 96-Channel 200 µL pipette.

API 2.26
  • Liquid-class support for the 96-channel 200 µL pipette.

API 2.27
  • Concurrent module tasks.

  • Dynamic aspirate, dispense, and mix paths.

  • Built-in camera capture.

  • Explicit tips for liquid-class transfers.

API 2.28
  • Flex 20 µL tips.

  • Improved return of partially picked-up tips.

  • Absolute blowout customization.

  • Thermocycler ramp-rate control.

  • set_empty() tip-rack state.

  • Errors for unsafe touch_tip() use in large spaces.

API 2.29
  • Step grouping in source and protocol visualization.

  • Flex-only at this migration baseline.

API 2.30
  • Aspirating at well.meniscus(target="start") without an end_location is supported. Older API levels reject that pattern.

  • The 10.0.0 package exposes MAX_SUPPORTED_VERSION=2.31, while the official robot support table stops at 2.30. Check the target robot; do not adopt 2.31 from the local constant.

10. Revisit Module and Deck Assumptions

Check for:

  • Flex trash or waste chute not represented in old code.

  • Staging area and column-3 conflicts.

  • New Gripper or lid moves.

  • Heater-Shaker latch state.

  • Thermocycler generation and footprint.

  • Plate-reader caddy and lid travel.

  • Stacker shuttle paths.

  • Tip-rack adapter requirements for full versus partial 96-channel pickup.

API analysis has improved, so a newly raised deck-conflict error may reveal an old protocol assumption that was never physically safe.

11. Revalidate Tip and Volume Policies

Do not assume newer pipetting behavior produces assay-equivalent results.

  • Recalculate tip count.

  • Recalculate source and dead volume.

  • Confirm complex-command expansion in the run log.

  • Requalify flow rates, mix behavior, bottom clearances, air gaps, and blowout.

  • Recheck contamination policy.

  • Recheck multi-channel and partial-nozzle well targeting.

12. Migration Test Plan

  1. Preserve the original protocol and expected run log.

  2. Update declarations and load names.

  3. Replace deprecated or invalid calls.

  4. Simulate with the robot-specific pin: opentrons==10.0.0 for Flex or opentrons==9.0.0 for OT-2.

  5. Compare command order, tip use, source/destination mapping, and module states.

  6. Test every runtime parameter branch.

  7. Import into the correct App and target robot.

  8. Resolve every analysis warning and error.

  9. Perform a nonhazardous dry run.

  10. Requalify assay performance before production use.

Do not claim a migration is equivalent solely from a successful simulation.

Requirements and compatibility

Works with: Claude Code, Claude apps, OpenAI Codex, GitHub Copilot, Cursor, Gemini CLI, Kiro, OpenCode, Goose, Amp, Roo Code, JetBrains Junie, Factory Droid, Devin (ex-Windsurf), Mistral Vibe, OpenHands, Letta

“Works with” means the tool reads the open Agent Skills format; a skill written for one tool may use features others lack.

Needs: Declares allowed tools, Needs network access, Needs Python

The author says: Requires Python 3.10+ and uv for local simulation. Flex examples target opentrons 10.0.0 and API 2.29 (documented robot maximum 2.30); the separate OT-2 line targets API 2.28 and uses opentrons 9.0.0 as its local compatibility simulator. Physical execution requires compatible hardware, current robot software, and the appropriate Opentrons App.

Security

What our scanner noticed· Low risk

  • Instructions that use the network
  • Scripts that your agent may run

This skill includes scripts that your agent may run. Read them before you use it.

A static scan is not a guarantee. Skills are third-party content: review a skill before you let an agent use it.

Attribution and licence

Created by
K-Dense Inc.
Publisher
K-Dense (Community)
Source
K-Dense-AI/scientific-agent-skills · skills/opentrons-integration · commit a25cf9e
Licence
MIT License (redistribution allowed)
  • LICENSE (added by AutoGineer from LICENSE.md)
  • ATTRIBUTION.md (written by AutoGineer)
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