SciPy

Solve optimization, statistics, signal processing, and linear algebra problems with SciPy recipes and ready-to-run code.

This skill appears coherent and low-risk: it generates SciPy-based Python code and does not ask for secrets or install anything. Before using: (1) confirm you have python3 and SciPy/NumPy installed (or install them in a virtualenv: pip install numpy scipy), (2) review any generated code before running it (check for unintended file or network access and for heavy computation that could strain your machine), and (3) if you prefer, run examples in an isolated environment (virtualenv or container). The skill source is listed as "unknown" in the registry metadata — that's common for third-party skills, but if provenance matters to you, consider verifying the homepage/owner or preferring skills from known publishers.

Type: OpenClaw Skill Name: scipy Version: 1.0.0 The OpenClaw SciPy skill bundle is benign. All code examples provided in `SKILL.md` are standard computational Python using SciPy and NumPy, without any risky functions like `os.system`, network calls, or file I/O. The `SKILL.md` explicitly states that the skill does not send data externally, create persistent files, or access network resources, which is consistent with the analyzed content. Instructions to the AI agent in `SKILL.md`, `setup.md`, and `memory-template.md` are focused on providing helpful code and understanding user needs, with no evidence of prompt injection or malicious intent.