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Rules, Skills & Agents for Java

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Goal

A curated collection of Rules, Skills, and Agents for Java Enterprise development, designed to streamline modern SDLC workflows.

The project add support for:

  • Agile: User Stories & Github Issues
  • Architecture: ADRs& UML / C4 / ER Diagrams`
  • Spec-Driven: AGENTS.md, AI Plan mode & OpenSpec
  • Java development: Build system based on Maven, Design, Coding, Testing, Observability, Refactoring & JMH Benchmarking, Performance testing with JMeter, Profiling with Async profiler/OpenJDK tools & Documentation
  • Java frameworks: Spring Boot, Quarkus & Micronaut.

Deliverables

The project generates a set of deliverables at the end of any iteration.

Deliverable Location
System prompts for Java Catalog (.cursor/rules)
Skills for Java https://skills.sh/jabrena/cursor-rules-java
Agents for Java Catalog (.cursor/agents)

Compatibility

This project is compatible with any Tool compatible with Skills, Agents or AGENTS.md like Cursor AI, Claude Code & Github Copilot.

Getting started

Read the following comprehensive guides to use this project today.

How to use them?

The SDLC has evolved with the arrival of this new set of AI tooling, enhancing the Software Engineering process. In the development of this project, it was identified 3 different workflows: Prompting Enginering Workflow, Pipelines Workflow & Agentic Workflow.

Prompting Enginering Workflow

In this workflow, the Software engineer interact with models using User prompts and in an incremental way you delegate a delegate completely a task or ask help in certain moments. You could use this project to refactor the code generated or delegate the task and associate a System prompt / Skills to that task.

Agent Workflow

Agents for Java Enterprise development were designed to help the Software engineer in the implementation phase. The software engineer define good Specs and that Specifications are delegated to Agents.

Pipelines Workflow

Adding AI tools to your pipeline can provide new opportunities to deliver more value (examples: automatic coding, code refactoring, continuous profiling, and others).

Limitations

Lack of determinism

From the outset, be aware that the results provided by interactions with the different Cursor rules are not deterministic due to the nature of the models, but this can be mitigated with clear goals and validation checkpoints.

Limits of interactions with models

Models are able to generate code, but they cannot run code with your local data. To address this limitation, some prompts provide scripts to bridge this gap on the model side.

Contribute

See CONTRIBUTING.md for conventions, generator workflows, tests, and how to open a pull request.

Examples

The repository includes a collection of examples where you can explore the possibilities of these system prompts designed for Java.

Architectural decision records, ADR

Date ID Name
2026-03-01 ADR-004 Skill Generation
2025-09-16 ADR-003 Website Generation
2025-07-10 ADR-002 Cursor Rules scope configuration
2025-07-08 ADR-001 Cursor Rules generation from XML Files

Changelog

Java JEPS from Java 8

Java uses JEPs as the vehicle to describe new features to be added to the language. The repository continuously reviews which JEPs could improve any of the cursor rules present in this repository.

Meetups, Conferences, Workshops & Articles

Codemotion / Madrid (2026/04/20 - 11:00 - 12:30)

W-JAX / Munich (2025/11/06 - 10:30 - 11:30)

Devoxx BE / Antwerp (2025/10/07 - 18:20 - 18:50)

Madrid Jug / Madrid (2025/05/06 - 19:00)

Blogs

References

Other developments

Powered by Cursor with ❤️ from Madrid