opentrons-integration

opentrons-integration is a skill for Claude Code, Codex from Zaoqu-Liu/ScienceClaw. It costs 66 tokens per session (4,089 once invoked), scanned A, a copy of opentrons-integration, MIT.

A Python toolkit for programming Opentrons OT-2 and Flex laboratory robots, which automate tasks such as moving liquids between containers.

In plain words
What is it for?
Use it to write, simulate, and test automated laboratory protocols such as serial dilutions, PCR setup, and plate replication.
Why use it?
It provides the documented structure needed to describe robot actions, labware, pipettes, and temperature or mixing modules.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one.

Good fit Use it to write, simulate, and test automated laboratory protocols such as serial dilutions, PCR setup, and plate replication.

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Install with agentmods
npx agentmods add skills/zaoqu-liu/scienceclaw/opentrons-integration
Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

Any agent
npx skills add Zaoqu-Liu/ScienceClaw --skill opentrons-integration
Clone the repo
git clone --depth 1 https://github.com/Zaoqu-Liu/ScienceClaw

Made for: Claude Code, Codex.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for opentrons-integration

README.md
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Your own site
<a href="https://agentmods.dev/skills/zaoqu-liu/scienceclaw/opentrons-integration"><img src="https://agentmods.dev/badge/skills/zaoqu-liu/scienceclaw/opentrons-integration/github.svg" alt="Measured on agentmods" height="20"></a>

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agentmods 80×15 button for opentrons-integration

Your own site · 80×15
<a href="https://agentmods.dev/skills/zaoqu-liu/scienceclaw/opentrons-integration"><img src="https://agentmods.dev/badge/skills/zaoqu-liu/scienceclaw/opentrons-integration.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 66 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 4,089 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin 88% copy Near-identical to another mod in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5.1 $0.00066 $0.04089
Opus 5 $0.00033 $0.02044
Sonnet 5 $0.00013 $0.00818
Haiku 4.5 $0.00007 $0.00409

Measured 6d ago against content hash ca8416042eb8, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-09, from the pricing page.

Security

Grade A, and why

opentrons-integration scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 6d ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

Origin

This is a copy

88% identical to opentrons-integration — 6 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.

skills/opentrons-integration/SKILL.md · 573 lines

How it starts

The opening of the file, as written. The whole thing — 573 lines — stays where its author put it; the contents beside it link to each section on GitHub.

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:

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):

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
    )

Read the full file on GitHub · 573 lines

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 6d ago First seen · 573 lines · 66 tokens per session scan A ca8416042eb8

Subscribe to this mod's changes

opentrons-integration is a skill published in the GitHub repository Zaoqu-Liu/ScienceClaw (60 stars, last pushed 5mo ago), licensed MIT. It adds 66 tokens to every session and 4,089 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it A with 0 findings. It is 88% identical to opentrons-integration, differing in 6 lines, and is treated as a copy.

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