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Install in OpenClaw
/install numpy
Description
Write fast, memory-efficient numerical code with arrays, broadcasting, vectorization, and linear algebra.
Usage Guidance
This skill appears coherent and local: it needs python3 and will create ~/numpy/ to store preferences and code snippets and will write a preference into the agent's MAIN memory to remember when to activate. Before installing, confirm you’re comfortable with the skill saving code/snippets locally and adding activation preferences to the agent memory. Also ensure python3 is the intended interpreter on your system. There is no declared network activity or secret access, but remember the SKILL.md is a set of instructions the agent will follow — if you want stronger guarantees, inspect agent logs or the created ~/numpy/ files after first use.
Capability Analysis
Type: OpenClaw Skill
Name: numpy
Version: 1.0.0
The OpenClaw NumPy skill bundle is classified as benign. All files (SKILL.md, memory-template.md, setup.md) consistently describe a skill focused on assisting with NumPy operations, storing user preferences and code snippets locally within `~/numpy/`. The `SKILL.md` explicitly states that the skill does NOT send data externally, access files outside `~/numpy/`, or require network connectivity, and no other instructions contradict this. There is no evidence of prompt injection attempts, data exfiltration, persistence mechanisms, or other malicious behaviors.
Capability Assessment
Purpose & Capability
Name/description (NumPy helper) match the declared binary requirement (python3) and the content of SKILL.md: teaching and saving NumPy patterns and preferences. No extraneous credentials, config paths, or unrelated binaries are requested.
Instruction Scope
SKILL.md instructs the agent to create and read/write under ~/numpy/ (memory.md and snippets). That is coherent for a snippet/preference helper. It also mentions saving a preference to the agent's MAIN memory so the skill knows when to activate; this is a reasonable behavior but does extend beyond the skill's own folder into agent-level memory.
Install Mechanism
Instruction-only skill with no install spec and no code files — minimal risk because nothing is downloaded or written by an installer. It relies on an existing python3 binary, which is appropriate.
Credentials
No environment variables, secrets, or unrelated credentials are requested. Requested filesystem access is limited to a user-owned directory (~/numpy/) as documented.
Persistence & Privilege
always:false (normal) and disable-model-invocation:false (normal). The skill will persist data under ~/numpy/ and writes some preferences into MAIN memory per setup.md; persisting user preferences/snippets is expected, but users should be aware it will store code and preferences locally and record activation choices in agent memory.
How to Use
- Make sure OpenClaw is installed (local or Docker)
- Run the install command in chat:
/install numpy - After installation, invoke the skill by name or use
/numpy - Provide required inputs per the skill's parameter spec and get structured output
Version History
v1.0.0
Initial release
Metadata
Frequently Asked Questions
What is NumPy?
Write fast, memory-efficient numerical code with arrays, broadcasting, vectorization, and linear algebra. It is an AI Agent Skill for Claude Code / OpenClaw, with 646 downloads so far.
How do I install NumPy?
Run "/install numpy" in the OpenClaw or Claude Code chat to install it in one step — no extra setup required.
Is NumPy free?
Yes, NumPy is completely free (open-source). You can download, install and use it at no cost.
Which platforms does NumPy support?
NumPy is cross-platform and runs anywhere OpenClaw / Claude Code is available (linux, darwin, win32).
Who created NumPy?
It is built and maintained by Iván (@ivangdavila); the current version is v1.0.0.
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