A high-performance numerical computing skill for writing fast, memory-efficient Python code using arrays and vectorization.
Install & Download
1. ClawHub CLI
The fastest way to install a skill directly from the registry.
npx clawhub@latest install numpy
2. Manual Installation
Copy the skill folder to one of these locations
~/.openclaw/skills/ <project>/skills/ Priority: Workspace > Local > Bundled
3. Prompt Installation
Copy this prompt to OpenClaw to install it automatically.
Help me install numpy 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 NumPy?
The NumPy skill provides AI agents with the specialized knowledge required to perform high-speed numerical computations. By prioritizing vectorization over traditional Python loops, this skill enables the creation of code that is significantly more efficient. As part of the Openclaw Skills ecosystem, it allows agents to handle complex mathematical tasks, multi-dimensional array manipulations, and sophisticated linear algebra with ease, ensuring your data processing pipelines are both fast and scalable.
NumPy Use Cases
- Developing high-speed data processing scripts using vectorized operations.
- Implementing complex linear algebra solutions for engineering or scientific projects.
- Optimizing memory usage in Python applications through precise dtype management.
- Creating reusable snippets for common numerical patterns and broadcasting logic.
How NumPy Works
- The agent configures a local workspace in the user home directory to maintain persistent memory.
- It analyzes the specific numerical task to determine if vectorization or broadcasting is required.
- The agent applies optimized NumPy functions instead of standard Python loops to maximize performance.
- It manages array shapes and memory views to prevent common pitfalls like silent type coercion.
- Custom patterns and frequently used code blocks are stored in a dedicated snippets folder for future retrieval.
NumPy Setup
To get started with this skill, use the following commands in your terminal:
# Install the NumPy skill
clawhub install numpy
# Sync with the latest updates
clawhub sync
Upon the first execution, the system will initialize a ~/numpy/ directory to store your personal coding preferences.
NumPy Data Schema & Taxonomy
The skill maintains a structured local directory to ensure privacy and organization. All data remains on your local machine.
| File/Folder | Purpose |
|---|---|
| ~/numpy/memory.md | Persistent storage for user preferences and common numerical patterns. |
| ~/numpy/snippets/ | Repository for saved Python code snippets involving complex NumPy logic. |
NumPy Advanced Features
- Advanced shape mismatch detection and resolution using reshape and newaxis patterns.
- Automatic optimization of memory through view-based slicing instead of unnecessary copies.
- Intelligent broadcasting alignment for multi-dimensional array operations.
- Seamless integration with other Openclaw Skills for end-to-end data science workflows.
SKILL.md
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