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Agent Skill · 研究检索

pylabrobot(pylabrobot 搜索)

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。

pylabrobot 是研究检索类 Agent Skill,可用宿主为 Codex、Claude、Cursor、Gemini CLI,通过GitHub 仓库获取,权限为操作浏览器;许可证为 MIT,第三方扫描已通过,按安装量在研究检索类的 73,675 个 Skill 里排第 53,392。

总安装 535周安装 23GitHub Stars 14下载 188核验 2026-05-01

安装说明

本站只整理中文说明,不托管安装包,也不代用户安装。
GitHub
许可证
MIT

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/jackspace/claudeskillz
仓库路径:skills/pylabrobot
安装命令:
npx skills add https://github.com/jackspace/claudeskillz --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/jackspace/claudeskillz --skill pylabrobot

这个 Skill 是做什么的

研究检索类 Skill 主要解决「找资料、核对事实、把来源整理清楚」的问题,通常会让助手先检索再总结。

pylabrobot 用于查找、检索和筛选相关信息,适合在 Codex、Claude、Cursor、Gemini CLI 中快速定位候选结果。适用于需要根据关键词或任务场景进行信息检索的研究与数据分析场景。通过关键词、来源仓库或原始 README 核验具体用法,结合宿主环境灵活调用。

安装命令为 npx skills add https://github.com/jackspace/claudeskillz --skill pylabrobot。使用前需确认权限范围、维护状态,注意是否触发联网、命令执行或文件读写操作。

来源仓库内路径:skills/pylabrobot

上手步骤

4 步
  1. 1

    确认自己的宿主工具

    公开资料标注支持 Codex、Claude、Cursor、Gemini CLI;先确认自己用的是其中之一,再按对应工具的 Skills 目录放置。

  2. 2

    拿到安装命令

    可以直接复制的命令是 npx skills add https://github.com/jackspace/claudeskillz --skill pylabrobot;命令里的占位符换成自己的路径或密钥再执行。

  3. 3

    安装后重启宿主

    命令执行完要完全退出宿主工具再打开,让新装的 Skill 被重新扫描到,否则列表里可能看不到。

  4. 4

    按最小权限试用

    它需要操作浏览器,先在测试目录或测试账号里跑,确认没问题再放到正式项目。

常见问题

6 条

pylabrobot 怎么安装?

在终端执行 npx skills add https://github.com/jackspace/claudeskillz --skill pylabrobot。装完完全退出宿主工具再打开,让它重新扫描本地 Skill。

pylabrobot 支持哪些 AI 工具?

公开资料标注支持 Codex、Claude、Cursor、Gemini CLI。其他工具只要能读取本地 Skill 目录,一般也能手动放进去,但要自己确认触发方式是否一致。

pylabrobot 需要什么权限?

权限级别是操作浏览器。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。

pylabrobot 是免费的吗?

来源标注的许可证是 MIT。本站不代收任何费用,也不托管安装包;能否商用、要不要署名,以许可证原文为准。

pylabrobot 用的人多吗?

公开数据是累计安装 535 次,近一周安装 23 次,下载 188 次,GitHub 14 星。这些数字来自第三方目录统计,只能当作热度参考,不代表质量或安全性。

pylabrobot 安全吗?

第三方扫描结果为通过,但这只覆盖已知的静态检查项,不能替代自己读一遍源码和安装命令。

值得选的地方和要先想清楚的地方

值得选的地方

  • 同时适配 4 种工具,换客户端不用重新找替代品。
  • 3 个目录同时收录,说明这个 Skill 流传比较广。
  • 许可证明确为 MIT,商用和分发边界好判断。
  • 第三方扫描已通过,常见的高风险行为没有命中。

先想清楚的地方

  • 第三方目录整理,版本更新和行为细节以来源仓库为准。

适不适合你

更适合

  • 已经在用 Codex,想直接扩展它能力的人。
  • 需要处理研究检索类任务、又不想每次都手写提示词的人。
  • 需要许可证清楚、并且有第三方扫描结果的团队项目。

不太适合

  • 需要厂商级技术支持和 SLA 的生产系统。

研究检索类 Skill 对比

6 个同类
Skill总安装GitHub 星权限许可证扫描
find-skills

寻找技能 · Codex、Claude

31,199,81316,486操作浏览器MIT有提醒
self-improving-agent

自我改进 Agent · OpenClaw

16,464,0023,396接触敏感数据MIT-0通过
soultrace

灵魂追踪 · Codex、Claude

7,588,94412需要联网未明确有提醒
self-improving

自我完善 · OpenClaw

6,829,2841,046需要联网MIT-0通过
microsoft-foundry

微软代工厂 · Codex、Claude

6,614,144764调用外部服务未明确有提醒
pylabrobot

pylabrobot 搜索 · 本页

53514操作浏览器MIT通过

按安装量取同分类前几名;数字来自第三方目录统计,只作热度参考,不代表质量结论。

SKILL.md 原文

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
# 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.

平台分布

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3.75%
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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。

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