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 AsiaOstrich · Claude Skill · ★ 74
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is universal-dev-standards safe to install? View the security audit →
Universal Development Standards Language: English 简体中文 Version: 5.17.0 License: Dual License (CC BY 4.0 + MIT) Language-agnostic, framework-agnostic development standards for software projects. Ensure consistency, quality, and maintainability across diverse technology stacks with AI-native workflows. 🚀 Quick Start Install via npm (Recommended) Looking for beta or RC versions? See Pre-release Versions. Or use npx (No installation required) Note: Copying standards alone won't enable AI assistance. Use to automatically configure your AI tool or manually reference standards in your tool's configuration file. 🗺️ What's Next? /re
| Stars | 74 |
| Forks | 13 |
| Language | JavaScript |
| Category | Claude Skill |
| Quality Score | 65.2623796871528/100 |
| Open Issues | 1 |
| Last Updated | 2026-09-18 |
| Created | 2025-12-24 |
| Platforms | claude-code, node |
| Est. Tokens | ~14k |
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universal-dev-standards is Universal, language-agnostic development standards for software projects. Includes coding standards, git workflows, testing guidelines, documentation structure, and AI collaboration rules.. It is categorized as a Claude Skill with 74 GitHub stars.
universal-dev-standards is primarily written in JavaScript. It covers topics such as ai-collaboration, best-practices, claude-code.
You can find installation instructions and usage details in the universal-dev-standards GitHub repository at github.com/AsiaOstrich/universal-dev-standards. The project has 74 stars and 13 forks, indicating an active community.
The top alternatives to universal-dev-standards on Agent Skills Hub include claude-night-market, code-abyss, cortex-tms. 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: