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An opinionated, AI-native development workflow for Java Enterprise — reusable Skills, Agents, Commands, and MCP servers
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An opinionated AI-native workflow for evolving modern Java Enterprise SDLC practices through reusable Skills, Agents, Commands & MCP servers.
Explore the latest published content on the project website and follow its evolution through new skills, improvements, and fixes in the CHANGELOG.
Install every skill for your preferred agent:
# Cursor
npx skills add jabrena/cursor-rules-java --skill '*' --agent cursor -y
# Claude Code
npx skills add jabrena/cursor-rules-java --skill '*' --agent claude-code -y
# Codex
npx skills add jabrena/cursor-rules-java --skill '*' --agent codex -y
# GitHub Copilot
npx skills add jabrena/cursor-rules-java --skill '*' --agent github-copilot -y
Ask your agent:
Use @110-java-maven-best-practices to review this Maven project.
Explain the findings, apply the approved improvements, and validate the build.
The skill guides the agent through a structured Maven review while keeping you in control of proposed changes.
Learn to use this project following the quick guide Getting Started in 5 minutes.
Current System prompts/rules are deprecated and will be removed in v0.16.0. If you still use them, review the release 0.14.0 article.
Turn an idea into an actionable change with user stories, GitHub Issues or Jira, ADRs, diagrams, AI plan mode, and OpenSpec.
| Resource | Available options |
|---|---|
| Commands | /create-issue · /update-issue · /explore-design · /create-adr · /create-diagram · /create-plan · /create-spec · /review-alignment |
| Agents | @robot-business-analyst · @robot-architect · @robot-tech-lead |
| Skills | 014-agile-user-story · 030-architecture-adr-general · 033-architecture-diagrams · 041-planning-plan-mode · 200-agents-md |
| MCP Servers | Jbang-Quarkus-JDBC · MongoDB · Serena-LSP |
Implement and improve Java applications with Maven, design, coding, testing, security, documentation, Spring Boot, Quarkus, Micronaut, OpenAPI, and WireMock guidance.
| Resource | Available options |
|---|---|
| Commands | /create-feature-branch · /create-worktree · /implement-issue · /kill-port |
| Agents | @robot-tech-lead · @robot-no-java · @robot-java-coder · @robot-java-spring-boot-coder · @robot-java-quarkus-coder · @robot-java-micronaut-coder |
| Skills | 110-java-maven-best-practices · 111-java-maven-dependencies · 121-java-object-oriented-design · 124-java-secure-coding · 143-java-functional-exception-handling |
| MCP Servers | Jbang-Quarkus-JDBC · MongoDB · JavaDocs · Serena-LSP |
Review Java systems, AI models, and how GenAI tools are used across applications and delivery pipelines for regulation-aware engineering controls, evidence, and qualified owner handoffs spanning AI, data, security, product, platform, market, and governance. These skills support engineering awareness and do not provide legal advice.
| Regulation | Skill |
|---|---|
| EU AI Act | 801-regulations-eu-ai-act |
| DORA | 802-regulations-dora |
| GDPR | 803-regulations-gdpr |
| NIS2 | 804-regulations-eu-nis2 |
| Cyber Resilience Act | 805-regulations-eu-cyber-resilience-act |
| Data Act | 806-regulations-eu-data-act |
| Digital Services Act | 807-regulations-eu-digital-services-act |
| Digital Markets Act | 808-regulations-eu-digital-markets-act |
Note: This set of skills could be a good complement for the future OWASP EU Compliance MCP.
Measure and improve production behavior through observability, profiling, benchmarking, and performance testing.
| Resource | Available options |
|---|---|
| Commands | /profile · /benchmark |
| Agents | @robot-java-performance |
| Skills | 151-java-performance-jmeter · 161-java-profiling-detect · 162-java-profiling-analyze · 163-java-profiling-refactor · 164-java-profiling-verify |
| MCP Servers | Jbang-Quarkus-JDBC · MongoDB · Serena-LSP · Grafana |
Explore the complete Commands, Agents, Skills, and MCP Servers inventories.
The project generates a set of deliverables at the end of any iteration.
| Inventory | Installation | Getting Started |
|---|---|---|
| 1. Commands | @004-commands-installation Install Commands in project | Commands |
| 2. Agents | @005-agents-installation Install Agents in Cursor/Claude | Agents |
| 3. Skills | npx skills add jabrena/cursor-rules-java --skill '*' --agent cursor -y | Skills |
This project is compatible with any tool that supports Commands, Agents, Skills, MCP Servers and AGENTS.md.
Every push runs the following validation checks in CI Builds to keep documentation and generated skills correct, consistent, and secure:
| Name | Purpose |
|---|---|
| 1. MarkdownValidator | Protects the documentation layer by catching Markdown parsing drift and remote link failures before skill-specific checks run. |
| 2. skill-check | Confirms every generated skill follows the expected packaging contract, complementing scanners that focus on behavior or security risk. |
| 3. cisco-ai-skill-scanner by Cisco | Adds behavior-oriented security coverage by looking for risky skill flows that structural validation cannot see. |
| 4. SkillSpector by NVIDIA | Provides an independent static quality and security review, useful for comparing findings against the other scanners. |
| 5. Snyk Agent Scan by SNYK | Focuses on agent-skill supply-chain and prompt-risk signals, adding another security perspective alongside Cisco and SkillSpector. |
From the outset, be aware that results from interactions with these Skills and agents are not deterministic because of how the models behave, but you can mitigate that with clear goals and validation checkpoints.
Some interactive skills require Premium models for interactive use; otherwise they follow a fixed sequence of steps.
Models can generate code, but they cannot execute it against your local data. To bridge that gap, some Skills include scripts you run locally.
This project supports software engineering work; it does not replace engineering judgment. A software engineer must review, guide, and validate AI-generated decisions, code, and outcomes before they are used.
Use caution when a problem involves corporate databases or other sensitive organizational data. Before granting an AI-assisted workflow access, assess authorization, privacy, data leakage, retention, and unintended modification risks. Apply least-privilege access, human review, validation, and monitoring. See OWASP GenAI Data Security Risks & Mitigations 2026, and the new set of skills about EU regulation.
Java uses JEPs (JDK Enhancement Proposals) to describe new language and platform features. This repository tracks which JEPs could improve the Skills and guidance here.
Talks, articles, reference links, skill portals, and related projects live in Project references.
Developed by humans with support from Cursor and Codex, with ❤️ from Madrid
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