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 fdhhhdjd · Agent Tool · ★ 261
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is Class-AI-Agent safe to install? View the security audit →
AI Agent Project — Production-Grade Configuration Production-ready AI Agent configuration for Claude Code Structured workflows, specialized agents, mandatory rules, and best practices Inspired by addyosmani/agent-skills Overview This repository provides a production-grade configuration for Claude Code AI agents. It includes: Structured development workflow (Spec → Plan → Build → Test → Review → Ship) 10 specialized agents for different development roles 13 mandatory rules covering code quality, architecture, and operations 8 slash commands for common workflows 4 reference checklists for security, testing, performance, and accessibility Development Workflow
| Stars | 261 |
| Forks | 164 |
| Category | Agent Tool |
| Quality Score | 63.8671316709352/100 |
| Open Issues | 1 |
| Last Updated | 2026-04-18 |
| Created | 2026-03-28 |
| Platforms | claude-code |
| Est. Tokens | ~5k |
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Class-AI-Agent is A modular framework for building intelligent AI agents powered by Claude, with rule-based workflows, skill management, and clean JS, TS architecture.. It is categorized as a Agent Tool with 261 GitHub stars.
You can find installation instructions and usage details in the Class-AI-Agent GitHub repository at github.com/fdhhhdjd/Class-AI-Agent. The project has 261 stars and 164 forks, indicating an active community.
The top alternatives to Class-AI-Agent on Agent Skills Hub include awesome-android-agent-skills, agent-skills, claude-code-skill-factory. 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: