Protocol Authoring

Opentrons Protocol Authoring

Behavior Defaults — READ FIRST

This skill is primarily used by developers, SDETs, and QA who need protocols for testing and development. Follow these defaults unless the user explicitly says otherwise:

1. Don't ask unnecessary questions. Pick reasonable labware, volumes, and pipettes. Just produce a valid, working protocol.
2. Keep protocols minimal. Use the fewest steps needed to demonstrate the requested behavior. Don't generate dozens of repeated transfers — 2–4 operations are enough to validate a feature.
3. Always define liquids with protocol.define_liquid() and well.load_liquid() for all source wells.
4. Default to liquid class functions (transfer_with_liquid_class, distribute_with_liquid_class, consolidate_with_liquid_class) on Flex with API >= 2.24. Fall back to plain transfer/distribute/consolidate only for OT-2 or when the user explicitly asks.
5. Default to Flex unless the user specifies OT-2.
6. Use the latest API version unless the user specifies otherwise. Look up MAX_SUPPORTED_VERSION in api/src/opentrons/protocols/api_support/definitions.py to get the current value.
7. Default liquid class: water. Use glycerol_50 or ethanol_80 if the protocol context calls for viscous or volatile liquids.
8. Reasonable defaults: flex_1channel_1000 pipette, opentrons_flex_96_tiprack_1000ul tip rack, nest_96_wellplate_2ml_deep plate, 100 µL transfer volume.

Quick Start — Flex Protocol (Default)

from opentrons import protocol_api

metadata = {
    "protocolName": "Liquid Class Transfer Demo",
    "author": "Opentrons",
    "description": "Minimal transfer using liquid classes",
}

requirements = {"robotType": "Flex", "apiLevel": "<MAX_SUPPORTED_VERSION>"}
# ^^^ Replace <MAX_SUPPORTED_VERSION> with the value from
# api/src/opentrons/protocols/api_support/definitions.py

def run(protocol: protocol_api.ProtocolContext) -> None:
    trash = protocol.load_trash_bin("A3")

    tiprack = protocol.load_labware("opentrons_flex_96_tiprack_1000ul", "D2")
    source_plate = protocol.load_labware("nest_96_wellplate_2ml_deep", "D1")
    dest_plate = protocol.load_labware("nest_96_wellplate_2ml_deep", "C1")

    pipette = protocol.load_instrument(
        "flex_1channel_1000", mount="left", tip_racks=[tiprack]
    )

    # Define and load liquids
    sample = protocol.define_liquid(
        name="Sample", description="Aqueous sample", display_color="#0088FF"
    )
    source_plate["A1"].load_liquid(liquid=sample, volume=500)
    source_plate["A2"].load_liquid(liquid=sample, volume=500)

    # Use liquid class transfer (default: water)
    water = protocol.get_liquid_class(name="water")
    pipette.transfer_with_liquid_class(
        liquid_class=water,
        volume=100,
        source=[source_plate["A1"], source_plate["A2"]],
        dest=[dest_plate["A1"], dest_plate["A2"]],
        new_tip="always",
    )

Quick Start — OT-2 Protocol

from opentrons import protocol_api

metadata = {
    "protocolName": "OT-2 Transfer Demo",
    "author": "Opentrons",
    "description": "Minimal transfer for OT-2",
}

requirements = {"robotType": "OT-2", "apiLevel": "<MAX_SUPPORTED_VERSION>"}

def run(protocol: protocol_api.ProtocolContext) -> None:
    tiprack = protocol.load_labware("opentrons_96_tiprack_300ul", "1")
    source_plate = protocol.load_labware("nest_96_wellplate_2ml_deep", "2")
    dest_plate = protocol.load_labware("nest_96_wellplate_2ml_deep", "3")

    pipette = protocol.load_instrument(
        "p300_single_gen2", mount="left", tip_racks=[tiprack]
    )

    sample = protocol.define_liquid(
        name="Sample", description="Aqueous sample", display_color="#0088FF"
    )
    source_plate["A1"].load_liquid(liquid=sample, volume=500)

    pipette.transfer(100, source_plate["A1"], dest_plate["A1"])

Required Elements

1. requirements dict — robotType ("Flex" or "OT-2") and apiLevel
2. def run(protocol): — entry point receiving ProtocolContext
3. Flex only: must load trash bin or waste chute before any drop_tip

metadata dict is optional but recommended. apiLevel goes in metadata OR requirements, not both.

Look up the current max API version from MAX_SUPPORTED_VERSION in api/src/opentrons/protocols/api_support/definitions.py. Flex requires >= 2.15.

Liquid Classes (Default for Flex)

Available liquid classes (Flex, API >= 2.24):

water = protocol.get_liquid_class(name="water")

# Transfer (1-to-1)
pipette.transfer_with_liquid_class(
    liquid_class=water, volume=100,
    source=[plate["A1"]], dest=[plate["B1"]],
    new_tip="always",
)

# Distribute (1-to-many)
pipette.distribute_with_liquid_class(
    liquid_class=water, volume=50,
    source=reservoir["A1"], dest=plate.rows()[0][:4],
    new_tip="once",
)

# Consolidate (many-to-1)
pipette.consolidate_with_liquid_class(
    liquid_class=water, volume=50,
    source=plate.rows()[0][:4], dest=reservoir["A1"],
    new_tip="once",
)

Defining Liquids (Always Do This)

sample = protocol.define_liquid(
    name="Sample", description="Aqueous sample", display_color="#0088FF"
)
buffer = protocol.define_liquid(
    name="Buffer", description="Wash buffer", display_color="#00CC66"
)
reagent = protocol.define_liquid(
    name="Reagent", description="Reaction reagent", display_color="#FF4444"
)

source_plate["A1"].load_liquid(liquid=sample, volume=500)
reservoir["A1"].load_liquid(liquid=buffer, volume=10000)

Common display colors: #0088FF (blue/sample), #00CC66 (green/buffer), #FF4444 (red/reagent), #FFB800 (yellow/media), #9933FF (purple/enzyme), #FF6B35 (orange/beads).

OT-2 vs Flex Key Differences

Flex Deck Layout

     1        2        3        4 (staging)
A  [ A1 ]  [ A2 ]  [ A3 ]  [ A4 ]
B  [ B1 ]  [ B2 ]  [ B3 ]  [ B4 ]
C  [ C1 ]  [ C2 ]  [ C3 ]  [ C4 ]
D  [ D1 ]  [ D2 ]  [ D3 ]  [ D4 ]

OT-2 Deck Layout

 10    11    12(trash)
  7     8     9
  4     5     6
  1     2     3

Pipettes

Flex

OT-2

Common Labware

Flex tip racks: opentrons_flex_96_tiprack_50ul, opentrons_flex_96_tiprack_200ul, opentrons_flex_96_tiprack_1000ul

OT-2 tip racks: opentrons_96_tiprack_20ul, opentrons_96_tiprack_300ul, opentrons_96_tiprack_1000ul

Plates: nest_96_wellplate_2ml_deep, corning_96_wellplate_360ul_flat, opentrons_96_wellplate_200ul_pcr_full_skirt, nest_96_wellplate_200ul_flat

Reservoirs: nest_12_reservoir_15ml, nest_1_reservoir_195ml, nest_1_reservoir_290ml

Tube racks: opentrons_24_tuberack_nest_1.5ml_snapcap, opentrons_6_tuberack_nest_50ml_conical

Modules Quick Reference

temp_mod = protocol.load_module("temperature module gen2", "D1")
tc = protocol.load_module("thermocycler module gen2")        # A1+B1 on Flex
hs = protocol.load_module("heaterShakerModuleV1", "C1")
mag_block = protocol.load_module("magneticBlockV1", "C1")    # Flex only
mag_mod = protocol.load_module("magnetic module gen2", "1")   # OT-2 only
apr = protocol.load_module("absorbanceReaderV1", "B3")        # Flex, API 2.21+
stacker = protocol.load_module("flexStackerModuleV1", "D4")   # Flex, API 2.25+

For detailed module operations, see reference-modules.md.

Runtime Parameters (API 2.18+)

def add_parameters(parameters: protocol_api.Parameters) -> None:
    parameters.add_int(variable_name="sample_count", display_name="Samples",
                       default=8, minimum=1, maximum=96)
    parameters.add_bool(variable_name="dry_run", display_name="Dry Run", default=False)

def run(protocol: protocol_api.ProtocolContext) -> None:
    count = protocol.params.sample_count

For complete RTP guide, see reference-rtp.md.

Working Directories (Monorepo Root)

All local dev artifacts live in these gitignored directories:

Custom Labware

Custom labware JSON files go in tmp-custom-labware/. The parameters.loadName in the JSON is the string passed to load_labware().

Creating a Custom Labware Definition

The easiest starting point is copying an existing definition from shared-data/labware/definitions/2/<name>/<version>.json and modifying the key fields:

{
  "namespace": "custom",
  "version": 1,
  "parameters": {
    "loadName": "my_custom_plate"
  },
  "metadata": {
    "displayName": "My Custom Plate"
  }
  ...
}

Required changes when deriving from an existing definition:

• parameters.loadName → your unique load name (no spaces, underscores OK)
• namespace → "custom" (must not be "opentrons")
• version → 1
• metadata.displayName → human-readable name

Save as tmp-custom-labware/<loadName>.json (file name convention matches loadName).

Using Custom Labware in a Protocol

plate = protocol.load_labware("my_custom_plate", "D1")

No special import needed — the CLI handles loading the definition at run time.

For a proper custom labware definition from scratch, use the Opentrons Labware Creator

CSV Runtime Parameters

CSV files go in tmp-csv/. They are used exclusively via the add_csv_file RTP type (API 2.20+).

Defining a CSV Parameter

def add_parameters(parameters: protocol_api.Parameters) -> None:
    parameters.add_csv_file(
        variable_name="transfer_map",
        display_name="Transfer Map",
        description="CSV with columns: source_well, dest_well, volume_ul",
    )

Using the CSV in run()

rows = protocol.params.transfer_map.parse_as_csv()
# rows is a list of lists; rows[0] is the header row
for row in rows[1:]:
    src, dst, vol = row[0].strip(), row[1].strip(), float(row[2].strip())
    pipette.transfer(vol, source[src], dest[dst])

Example CSV (tmp-csv/transfer_map.csv)

source_well,dest_well,volume_ul
A1,A1,100
A2,A2,150
A3,A3,75

Note: opentrons_simulate cannot accept RTP files. Protocols with CSV RTPs must be verified with opentrons analyze. See the protocol-verification skill.

Additional References

Skill Reference Files (in this directory)

AI Server Source Docs (read on demand)

Located in opentrons-ai-server/api/storage/docs/. Use reference-examples-index.md to decide which file to read. Do not read all of them — they total ~10,000 lines. Read only what the current task needs.

Keeping This Skill Current

Update this skill whenever you discover something new. These files are the team's shared knowledge base — stale information hurts everyone.

How to update: use the Write or StrReplace tools on the relevant skill file. Keep edits focused — fix only what changed. Don't rewrite sections that are still accurate.

Common Mistakes

• Forgetting load_trash_bin() on Flex
• Using OT-2 pipette names on Flex or vice versa
• Putting apiLevel in both metadata and requirements
• Using numeric slots on Flex or alpha on OT-2
• Exceeding pipette volume range
• Using transfer with new_tip="never" without calling pick_up_tip() first
• Forgetting to define_liquid / load_liquid for source wells
• Using plain transfer on Flex when transfer_with_liquid_class is available
• Calling apr.initialize() without apr.close_lid() first (APR lid must be closed before init)
• Passing only the top well (e.g. plate["A1"]) to 8-channel *_with_liquid_class — must pass full column or set group_wells=False
• Using f-strings or variable references in metadata dict — the parser requires static literals only (no f"...", no {var}, no function calls)
• Wrapping transfer() in a for loop over wells — transfer() handles iteration internally; pass lists instead
• Using 8-channel pipette with wells() instead of columns() — 8-channel picks up an entire column at once
• Not accounting for 8-channel tip math: one pick_up_tip() = 8 tips; a single 96-well rack supports only 12 column operations
• Loading a 96-channel pipette without adapter="opentrons_flex_96_tiprack_adapter" for full (ALL) tip pickup
• Using start="A1" for 96-channel COLUMN mode — always use start="A12" to avoid deck edge collision
• Placing a tube rack in a staging area slot (A4–D4) — gripper cannot safely move tube racks
• Loading the Heater-Shaker or Temperature Module in column 2 slots (A2, B2, C2, D2) — forbidden on Flex