Token导航 LogoToken导航TokenDH.com
研究检索操作浏览器github未标认证来源可访问clear审计通过

pylabrobotpylabrobot 搜索

Agent Skill

pylabrobot 用于查找、检索和筛选相关信息,适合在 Codex、Claude、Cursor、Gemini CLI 中需要根据关键词、任务场景或来源线索快速定位候选结果时使用。可结合来源仓库、安装命令和原始 README 继续核验具体用法。安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。

总安装

5,541

周安装

238

GitHub Stars

26,434

下载量

1,942
CodexClaudeCursorGemini CLI

安装说明

本站只整理中文说明和来源信息,不托管安装包,也不代用户安装。

GitHub

来源数

3

许可证

MIT

最后核验

2026-05-01

来源状态

来源可访问

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:pylabrobot(pylabrobot 搜索)
来源仓库:https://github.com/davila7/claude-code-templates
仓库路径:skills/pylabrobot
安装命令:
npx skills add https://github.com/davila7/claude-code-templates --skill pylabrobot
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。不同来源提供的安装方式可能略有差异;本站展示可直接复制的安装命令,安装前请核对来源页面。

skills.shnpx skills
npx skills add https://github.com/davila7/claude-code-templates --skill pylabrobot

简介

pylabrobot 是面向自动化实验室的纯 Python SDK,支持跨平台控制各类实验设备。

  • 适用于编程液体处理机器人、自动化样本制备及分析流程集成等场景。
  • 可通过统一接口操控 Hamilton、Opentrons 等设备,实现 pipetting 和分析仪器联动。
  • 使用前需确认硬件兼容性、操作系统权限及实验流程安全规范,防止误操作损坏设备。
  • pylabrobot 属于研究检索类 Skill,可作为该场景下的辅助能力补充。

SKILL.md

PyLabRobot

Overview

PyLabRobot is a hardware-agnostic, pure Python Software Development Kit for automated and autonomous laboratories. Use this skill to control liquid handling robots, plate readers, pumps, heater shakers, incubators, centrifuges, and other laboratory automation equipment through a unified Python interface that works across platforms (Windows, macOS, Linux).

When to Use This Skill

Use this skill when:

  • Programming liquid handling robots (Hamilton STAR/STARlet, Opentrons OT-2, Tecan EVO)
  • Automating laboratory workflows involving pipetting, sample preparation, or analytical measurements
  • Managing deck layouts and laboratory resources (plates, tips, containers, troughs)
  • Integrating multiple lab devices (liquid handlers, plate readers, heater shakers, pumps)
  • Creating reproducible laboratory protocols with state management
  • Simulating protocols before running on physical hardware
  • Reading plates using BMG CLARIOstar or other supported plate readers
  • Controlling temperature, shaking, centrifugation, or other material handling operations
  • Working with laboratory automation in Python

Core Capabilities

PyLabRobot provides comprehensive laboratory automation through six main capability areas, each detailed in the references/ directory:

1. Liquid Handling (references/liquid-handling.md)

Control liquid handling robots for aspirating, dispensing, and transferring liquids. Key operations include:

  • Basic Operations: Aspirate, dispense, transfer liquids between wells
  • Tip Management: Pick up, drop, and track pipette tips automatically
  • Advanced Techniques: Multi-channel pipetting, serial dilutions, plate replication
  • Volume Tracking: Automatic tracking of liquid volumes in wells
  • Hardware Support: Hamilton STAR/STARlet, Opentrons OT-2, Tecan EVO, and others

2. Resource Management (references/resources.md)

Manage laboratory resources in a hierarchical system:

  • Resource Types: Plates, tip racks, troughs, tubes, carriers, and custom labware
  • Deck Layout: Assign resources to deck positions with coordinate systems
  • State Management: Track tip presence, liquid volumes, and resource states
  • Serialization: Save and load deck layouts and states from JSON files
  • Resource Discovery: Access wells, tips, and containers through intuitive APIs

3. Hardware Backends (references/hardware-backends.md)

Connect to diverse laboratory equipment through backend abstraction:

  • Liquid Handlers: Hamilton STAR (full support), Opentrons OT-2, Tecan EVO
  • Simulation: ChatterboxBackend for protocol testing without hardware
  • Platform Support: Works on Windows, macOS, Linux, and Raspberry Pi
  • Backend Switching: Change robots by swapping backend without rewriting protocols

4. Analytical Equipment (references/analytical-equipment.md)

Integrate plate readers and analytical instruments:

  • Plate Readers: BMG CLARIOstar for absorbance, luminescence, fluorescence
  • Scales: Mettler Toledo integration for mass measurements
  • Integration Patterns: Combine liquid handlers with analytical equipment
  • Automated Workflows: Move plates between devices automatically

5. Material Handling (references/material-handling.md)

Control environmental and material handling equipment:

  • Heater Shakers: Hamilton HeaterShaker, Inheco ThermoShake
  • Incubators: Inheco and Thermo Fisher incubators with temperature control
  • Centrifuges: Agilent VSpin with bucket positioning and spin control
  • Pumps: Cole Parmer Masterflex for fluid pumping operations
  • Temperature Control: Set and monitor temperatures during protocols

6. Visualization & Simulation (references/visualization.md)

Visualize and simulate laboratory protocols:

  • Browser Visualizer: Real-time 3D visualization of deck state
  • Simulation Mode: Test protocols without physical hardware
  • State Tracking: Monitor tip presence and liquid volumes visually
  • Deck Editor: Graphical tool for designing deck layouts
  • Protocol Validation: Verify protocols before running on hardware

Quick Start

To get started with PyLabRobot, install the package and initialize a liquid handler:

# Install PyLabRobot
# uv pip install pylabrobot

# Basic liquid handling setup
from pylabrobot.liquid_handling import LiquidHandler
from pylabrobot.liquid_handling.backends import STAR
from pylabrobot.resources import STARLetDeck

# Initialize liquid handler
lh = LiquidHandler(backend=STAR(), deck=STARLetDeck())
await lh.setup()

# Basic operations
await lh.pick_up_tips(tip_rack["A1:H1"])
await lh.aspirate(plate["A1"], vols=100)
await lh.dispense(plate["A2"], vols=100)
await lh.drop_tips()

Working with References

This skill organizes detailed information across multiple reference files. Load the relevant reference when:

  • Liquid Handling: Writing pipetting protocols, tip management, transfers
  • Resources: Defining deck layouts, managing plates/tips, custom labware
  • Hardware Backends: Connecting to specific robots, switching platforms
  • Analytical Equipment: Integrating plate readers, scales, or analytical devices
  • Material Handling: Using heater shakers, incubators, centrifuges, pumps
  • Visualization: Simulating protocols, visualizing deck states

All reference files can be found in the references/ directory and contain comprehensive examples, API usage patterns, and best practices.

Best Practices

When creating laboratory automation protocols with PyLabRobot:

  1. Start with Simulation: Use ChatterboxBackend and the visualizer to test protocols before running on hardware
  2. Enable Tracking: Turn on tip tracking and volume tracking for accurate state management
  3. Resource Naming: Use clear, descriptive names for all resources (plates, tip racks, containers)
  4. State Serialization: Save deck layouts and states to JSON for reproducibility
  5. Error Handling: Implement proper async error handling for hardware operations
  6. Temperature Control: Set temperatures early as heating/cooling takes time
  7. Modular Protocols: Break complex workflows into reusable functions
  8. Documentation: Reference official docs at https://docs.pylabrobot.org for latest features

Common Workflows

Liquid Transfer Protocol

# Setup
lh = LiquidHandler(backend=STAR(), deck=STARLetDeck())
await lh.setup()

# Define resources
tip_rack = TIP_CAR_480_A00(name="tip_rack")
source_plate = Cos_96_DW_1mL(name="source")
dest_plate = Cos_96_DW_1mL(name="dest")

lh.deck.assign_child_resource(tip_rack, rails=1)
lh.deck.assign_child_resource(source_plate, rails=10)
lh.deck.assign_child_resource(dest_plate, rails=15)

# Transfer protocol
await lh.pick_up_tips(tip_rack["A1:H1"])
await lh.transfer(source_plate["A1:H12"], dest_plate["A1:H12"], vols=100)
await lh.drop_tips()

Plate Reading Workflow

# Setup plate reader
from pylabrobot.plate_reading import PlateReader
from pylabrobot.plate_reading.clario_star_backend import CLARIOstarBackend

pr = PlateReader(name="CLARIOstar", backend=CLARIOstarBackend())
await pr.setup()

# Set temperature and read
await pr.set_temperature(37)
await pr.open()
# (manually or robotically load plate)
await pr.close()
data = await pr.read_absorbance(wavelength=450)

Additional Resources

For detailed usage of specific capabilities, refer to the corresponding reference file in the references/ directory.

适合场景

01

用户想查找某类 Agent Skill 时

02

需要根据任务场景推荐可安装能力包时

03

需要对比不同来源的安装命令和来源信息时

04

需要参考平台分布和安装热度时

能力概览

能力 1

按任务关键词查找相关 Skills

能力 2

展示可复制的安装命令

能力 3

保留来源站点、仓库和原始说明,方便继续核验

能力 4

补充不同宿主或平台的使用分布数据

能力 5

展示第三方安全扫描或审计结果

安装后应在对应宿主中按原始 README 的触发条件使用;具体调用方式请以来源页面和 README 为准。

平台分布

Claude Code

28.86%
按下载量换算560

OpenCode

22.14%
按下载量换算430

Cursor

19.35%
按下载量换算376

Gemini CLI

12.34%
按下载量换算240

Antigravity

8.45%
按下载量换算164

windsurf

3.51%
按下载量换算68

安全审计

Gen Agent Trust Hub

通过

Socket

通过

Snyk

通过

权限和风险

操作浏览器

该 Skill 可能涉及浏览器控制能力,使用时可能读取或操作网页内容,需要在受控环境中确认权限边界。

安装前确认

本站仅展示第三方公开信息,不托管安装包,不提供自动安装或运行环境。安装前应自行审查源码、依赖和命令行为。

来源信息

继续浏览同类 Skills