Quantum Lab for Openclaw

A dedicated execution environment for running Qiskit-based quantum simulations and mathematical research scripts.

bramdo
v1.0.0
Feb 6, 2026
0
2.6k
0

Install & Download

1. ClawHub CLI

The fastest way to install a skill directly from the registry.

npx clawhub@latest install quantumlab

2. Manual Installation

Copy the skill folder to one of these locations

Global
~/.openclaw/skills/
Workspace
<project>/skills/

Priority: Workspace > Local > Bundled

3. Prompt Installation

Copy this prompt to OpenClaw to install it automatically.

Help me install quantumlab using Clawhub. If Clawhub is not installed, install it first (npm i -g clawhub).

Prefer to download?

Get the raw skill files in a ZIP archive.

What is Quantum Lab?

Quantum Lab is a specialized technical skill designed to streamline the execution of quantum computing workflows within an AI agent environment. It provides a standardized wrapper for interacting with the quantum_lab repository, ensuring that all scripts, demos, and notebooks run inside a consistent Qiskit virtual environment. By leveraging Openclaw Skills, developers can automate the testing of quantum algorithms and manage complex research environments without manual shell configuration.

This skill is particularly valuable for researchers and developers who need to bridge the gap between high-level AI orchestration and low-level quantum simulation tools. It handles environment activation, repository pathing, and dependency management automatically, allowing users to focus on quantum logic rather than infrastructure setup.

Quantum Lab Use Cases

  • Running complex quantum mathematical experiments using the quant_math_lab.py utility.
  • Executing Qiskit simulations within a isolated and pre-configured virtual environment.
  • Launching and managing Jupyter notebooks for quantum computation visualization.
  • Hosting local quantum application servers for testing web-based quantum interfaces.
  • Performing automated self-tests and playground experiments on quantum software repositories.

How Quantum Lab Works

  1. The user provides a command or shorthand request through an interface powered by Openclaw Skills.
  2. The skill resolves the command using internal helper scripts located in the scripts directory.
  3. The system automatically identifies the correct virtual environment (defaulting to qiskit) and activates it.
  4. The command is executed within the specified repository root, ensuring all relative paths and imports remain valid.
  5. Output and logs from the quantum simulation or script are captured and returned to the agent for analysis or display.

Quantum Lab Setup

To set up the environment for this skill, ensure your repository and virtual environment paths are correctly configured. Use the following commands for initial setup:

# Define custom paths if different from defaults
export QUANTUM_LAB_ROOT="$HOME/work/quantum_lab"
export VENV_PATH="~/.venvs/qiskit"

# Install necessary dependencies within the environment
bash <SKILL_DIR>/scripts/qexec.sh pip install -r requirements.txt

Quantum Lab Data Schema & Taxonomy

The skill organizes its operations around a specific directory structure and environment variables to ensure portability.

Property Description Default Value
Repository Root The primary directory containing quantum scripts $HOME/work/quantum_lab
Virtual Env The path to the Python environment with Qiskit ~/.venvs/qiskit
Script Wrapper Central execution script for environment isolation scripts/qexec.sh
Command Aliases Shorthand triggers for rapid execution gl or ql

Quantum Lab Advanced Features

  • Intelligent shorthand expansion for gl and ql commands to minimize typing and latency.
  • Support for running local web servers for quantum apps with configurable host and port settings.
  • Seamless integration with Jupyter notebook workflows for interactive research.
  • Automated environment variable overrides for multi-project quantum research setups.
  • Robust error handling for missing dependencies within the Openclaw Skills framework.

SKILL.md


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