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 jabrena · MCP Server · ★ 412
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
🔒 Is cursor-rules-java safe to install? View the security audit →
Commands, Agents & Skills for Java Languages: Español · 中文 Website: https://jabrena.github.io/cursor-rules-java/ Support the project: Sponsor to pay tokens Goal An opinionated AI-native workflow for evolving modern Java Enterprise practices through reusable , , & . It helps you answer the Five whys when your team needs to evolve a Java-based product or service:
| Stars | 412 |
| Forks | 82 |
| Language | Java |
| Category | MCP Server |
| License | Apache-2.0 |
| Quality Score | 64.3279781047197/100 |
| Open Issues | 17 |
| Last Updated | 2026-06-29 |
| Created | 2025-02-08 |
| Platforms | claude-code, codex, java, mcp |
| Est. Tokens | ~19k |
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cursor-rules-java is An opinionated, AI-native development workflow for Java Enterprise — reusable Skills, Agents, Commands, and MCP servers combined with a human-in-the-loop model to modernize real-world SDLC practices.. It is categorized as a MCP Server with 412 GitHub stars.
cursor-rules-java is primarily written in Java. It covers topics such as agent-skills, ai-skills, claude.
You can find installation instructions and usage details in the cursor-rules-java GitHub repository at github.com/jabrena/cursor-rules-java. The project has 412 stars and 82 forks, indicating an active community.
cursor-rules-java is released under the Apache-2.0 license, making it free to use and modify according to the license terms.
The top alternatives to cursor-rules-java on Agent Skills Hub include awesome-ai-agent-skills, getspecstory, ok-skills. 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: