Opentrons IntegrationSAFE

Kosmos: An AI Scientist for Autonomous Discovery - An implementation and adaptation to be driven by Claude Code or API - Based on the Kosmos AI Paper - https://arxiv.org/abs/2511.02824

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---
name: opentrons-integration
description: "Lab automation platform for Flex/OT-2 robots. Write Protocol API v2 protocols, liquid handling, hardware modules (heater-shaker, thermocycler), labware management, for automated pipetting workflows."
---

# Opentrons Integration

## Overview

Opentrons is a Python-based lab automation platform for Flex and OT-2 robots. Write Protocol API v2 protocols for liquid handling, control hardware modules (heater-shaker, thermocycler), manage labware, for automated pipetting workflows.

## When to Use This Skill

This skill should be used when:
- Writing Opentrons Protocol API v2 protocols in Python
- Automating liquid handling workflows on Flex or OT-2 robots
- Controlling hardware modules (temperature, magnetic, heater-shaker, thermocycler)
- Setting up labware configurations and deck layouts
- Implementing complex pipetting operations (serial dilutions, plate replication, PCR setup)
- Managing tip usage and optimizing protocol efficiency
- Working with multi-channel pipettes for 96-well plate operations
- Simulating and testing protocols before robot execution

## Core Capabilities

### 1. Protocol Structure and Metadata

Every Opentrons protocol follows a standard structure:

```python
from opentrons import protocol_api

# Metadata
metadata = {
    'protocolName': 'My Protocol',
    'author': 'Name <[email protected]>',
    'description': 'Protocol description',
    'apiLevel': '2.19'  # Use latest available API version
}

# Requirements (optional)
requirements = {
    'robotType': 'Flex',  # or 'OT-2'
    'apiLevel': '2.19'
}

# Run function
def run(protocol: protocol_api.ProtocolContext):
    # Protocol commands go here
    pass
```

**Key elements:**
- Import `protocol_api` from `opentrons`
- Define `metadata` dict with protocolName, author, description, apiLevel
- Optional `requirements` dict for robot type and API version
- Implement `run()` function receiving `ProtocolContext` as parameter
- All protocol logic goes inside the `run()` function

### 2. Loading Hardware

**Loading Instruments (Pipettes):**

```python
def run(protocol: protocol_api.ProtocolContext):
    # Load pipette on specific mount
    left_pipette = protocol.load_instrument(
        'p1000_single_flex',  # Instrument name
        'left',               # Mount: 'left' or 'right'
        tip_racks=[tip_rack]  # List of tip rack labware objects
    )
```

Common pipette names:
- Flex: `p50_single_flex`, `p1000_single_flex`, `p50_multi_flex`, `p1000_multi_flex`
- OT-2: `p20_single_gen2`, `p300_single_gen2`, `p1000_single_gen2`, `p20_multi_gen2`, `p300_multi_gen2`

**Loading Labware:**

```python
# Load labware directly on deck
plate = protocol.load_labware(
    'corning_96_wellplate_360ul_flat',  # Labware API name
    'D1',                                # Deck slot (Flex: A1-D3, OT-2: 1-11)
    label='Sample Plate'                 # Optional display label
)

# Load tip rack
tip_rack = protocol.load_labware('opentrons_flex_96_tiprack_1000ul', 'C1')

# Load labware on adapter
adapter = protocol.load_adapter('opentrons_flex_96_tiprack_adapter', 'B1')
tips = adapter.load_labware('opentrons_flex_96_tiprack_200ul')
```

**Loading Modules:**

```python
# Temperature module
temp_module = protocol.load_module('temperature module gen2', 'D3')
temp_plate = temp_module.load_labware('corning_96_wellplate_360ul_flat')

# Magnetic module
mag_module = protocol.load_module('magnetic module gen2', 'C2')
mag_plate = mag_module.load_labware('nest_96_wellplate_100ul_pcr_full_skirt')

# Heater-Shaker module
hs_module = protocol.load_module('heaterShakerModuleV1', 'D1')
hs_plate = hs_module.load_labware('corning_96_wellplate_360ul_flat')

# Thermocycler module (takes up specific slots automatically)
tc_module = protocol.load_module('thermocyclerModuleV2')
tc_plate = tc_module.load_labware('nest_96_wellplate_100ul_pcr_full_skirt')
```

### 3. Liquid Handling Operations

**Basic Operations:**

```python
# Pick up tip
pipette.pick_up_tip()

# Aspirate (draw liquid in)
pipette.aspirate(
    volume=100,           # Volume in μL
    location=source['A1'] # Well or location object
)

# Dispense (expel liquid)
pipette.dispense(
    volume=100,
    location=dest['B1']
)

# Drop tip
pipette.drop_tip()

# Return tip to rack
pipette.return_tip()
```

**Complex Operations:**

```python
# Transfer (combines pick_up, aspirate, dispense, drop_tip)
pipette.transfer(
    volume=100,
    source=source_plate['A1'],
    dest=dest_plate['B1'],
    new_tip='always'  # 'always', 'once', or 'never'
)

# Distribute (one source to multiple destinations)
pipette.distribute(
    volume=50,
    source=reservoir['A1'],
    dest=[plate['A1'], plate['A2'], plate['A3']],
    new_tip='once'
)

# Consolidate (multiple sources to one destination)
pipette.consolidate(
    volume=50,
    source=[plate['A1'], plate['A2'], plate['A3']],
    dest=reservoir['A1'],
    new_tip='once'
)
```

**Advanced Techniques:**

```python
# Mix (aspirate and dispense in same location)
pipette.mix(
    repetitions=3,
    volume=50,
    location=plate['A1']
)

# Air gap (prevent dripping)
pipette.aspirate(100, source['A1'])
pipette.air_gap(20)  # 20μL air gap
pipette.dispense(120, dest['A1'])

# Blow out (expel remaining liquid)
pipette.blow_out(location=dest['A1'].top())

# Touch tip (remove droplets on tip exterior)
pipette.touch_tip(location=plate['A1'])
```

**Flow Rate Control:**

```python
# Set flow rates (μL/s)
pipette.flow_rate.aspirate = 150
pipette.flow_rate.dispense = 300
pipette.flow_rate.blow_out = 400
```

### 4. Accessing Wells and Locations

**Well Access Methods:**

```python
# By name
well_a1 = plate['A1']

# By index
first_well = plate.wells()[0]

# All wells
all_wells = plate.wells()  # Returns list

# By rows
rows = plate.rows()  # Returns list of lists
row_a = plate.rows()[0]  # All wells in row A

# By columns
columns = plate.columns()  # Returns list of lists
column_1 = plate.columns()[0]  # All wells in column 1

# Wells by name (d

SAFEgrade B · trust 89/100 Nothing in the source contradicts what it says it does. Grade A is reserved for packages that have also passed the behavioural sandbox.

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