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 manuelescobar-dev · LLM Plugin · ★ 183
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is LLM-Tools safe to install? View the security audit →
[![Contributors][contributors-shield]][contributors-url] [![Forks][forks-shield]][forks-url] [![Stargazers][stars-shield]][stars-url] [![Issues][issues-shield]][issues-url] [![MIT License][license-shield]][license-url] LLM Tools Useful tools for LLM development! Available on https://llm-dev-tools.streamlit.app Table of Contents About The Project Memory Requirements Calculator Roadmap Getting Started Contributing License Contact Acknowledgments About The Project The LLM Tools is an open-source project designed
| Stars | 183 |
| Forks | 30 |
| Language | Python |
| Category | LLM Plugin |
| License | MIT |
| Quality Score | 72.4407100099811/100 |
| Open Issues | 4 |
| Last Updated | 2024-12-18 |
| Created | 2024-04-24 |
| Platforms | python |
| Est. Tokens | ~6k |
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LLM-Tools is Open-source calculator for LLM system requirements.. It is categorized as a LLM Plugin with 183 GitHub stars.
LLM-Tools is primarily written in Python. It covers topics such as artificial-intelligence, deep-learning, large-language-models.
You can find installation instructions and usage details in the LLM-Tools GitHub repository at github.com/manuelescobar-dev/LLM-Tools. The project has 183 stars and 30 forks, indicating an active community.
LLM-Tools is released under the MIT license, making it free to use and modify according to the license terms.
The top alternatives to LLM-Tools on Agent Skills Hub include free-ai-resources-x, VideoGraphAI, LLM-VM. 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: