No red flags found in any of the 11 categories — no credential harvesting, no data exfiltration, no curl-pipe-shell installer. Scanned against the SlowMist agent-security taxonomy, refreshed every 8 hours. Full audit →
by HeshamFS · Agent Tool · ★ 68
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is materials-simulation-skills safe to install? View the security audit →
Materials Simulation Skills Give your AI coding agent real expertise in numerical methods, simulation best practices, and computational materials science — so it stops guessing. New to Agent Skills? A "skill" is a portable folder of instructions + small scripts that an AI coding agent discovers automatically and loads only when relevant. They follow the open Agent Skills standard and work across 20+ tools — Claude Code, Codex, Cursor, Antigravity, GitHub Copilot, and more. Nothing to wire up: drop them in and your agent gets smarter at the task. What it solves Simulation engineers repeat the same guidance to AI agents constantly: "Check the CFL number before running," "Use Richardson extrapolation for grid convergence," "Exit code 2
| Stars | 68 |
| Forks | 3 |
| Language | Python |
| Category | Agent Tool |
| License | Apache-2.0 |
| Quality Score | 69.6322385550449/100 |
| Last Updated | 2026-06-25 |
| Created | 2025-12-24 |
| Platforms | cli, python |
| Est. Tokens | ~15k |
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materials-simulation-skills is Agent Skills for computational materials science -- numerical stability, solvers, meshing, convergence, and simulation workflows.. It is categorized as a Agent Tool with 68 GitHub stars.
materials-simulation-skills is primarily written in Python. It covers topics such as agent-skills, agents, cli-tools.
You can find installation instructions and usage details in the materials-simulation-skills GitHub repository at github.com/HeshamFS/materials-simulation-skills. The project has 68 stars and 3 forks, indicating an active community.
materials-simulation-skills is released under the Apache-2.0 license, making it free to use and modify according to the license terms.
The top alternatives to materials-simulation-skills on Agent Skills Hub include brunnfeld-agentic-world, zypher-agent, science-superpowers. Each offers a different approach to the same problem space — compare them side-by-side by stars, quality score, and community activity.
Grades come from a rule-based scan built on the SlowMist agent-security taxonomy, covering 11 red-flag categories including credential harvesting, data exfiltration, and curl | sh installers. It is a first-layer scan, not a manual audit — we say so rather than overstate it.
The scale of the problem is documented independently: Liu et al. (2026), in a study of 31,132 agent skills, report that 26.1% contain security vulnerabilities. Our own full-catalog census is published as a citable open dataset.
Sources & who's responsible: