A curated collection of Skills and Agents to be used in modern SDLC workflows for Java Enterprise development.
| QUESTION | ROLE | AREA | SUPPORT |
|---|---|---|---|
| WHAT / WHEN | PO, BA, EA, SA, TL | Agile & Planning | User Stories, GitHub Issues & Jira |
| WHY | EA, SL, TL | Architecture | ADRs & UML / C4 / ER Diagrams |
| HOW | SA, TL, SWE | Spec-Driven | AI Plan mode & OpenSpec |
| HOW | TL, SWE | 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, Spring Boot, Quarkus, Micronaut, OpenAPI, Wiremock & AGENTS.md |
The project generates a set of deliverables at the end of any iteration.
| Deliverable | Installation | Getting Started |
|---|---|---|
| 1. Skills for Java | npx skills add jabrena/cursor-rules-java --all --agent cursor |
Skills for Java |
| 2. Agents for Java | @003-agents-installation Install Agents in Cursor |
Agents for Java |
Note: After you install the skills, you can install the agents easily for Cursor or Claude.
This project is compatible with any tool that supports Skills, Agents, AGENTS.md, and MCP servers.
The SDLC has evolved with this new wave of AI tooling, which enhances the software engineering process. While building this project, we identified three workflows: Prompting Engineering Workflow, Pipelines Workflow, and Agentic Workflow.
In this workflow, the software engineer interacts with models using User prompts. In an incremental way, you delegate a whole task or ask for help at specific points. You can use this project to refactor generated code, or delegate the task and attach a system prompt or Skills to it.
Agents for Java Enterprise development were designed to help the software engineer in the implementation phase. The engineer defines solid Specs, and those specifications are delegated to Agents.
Adding AI tools to your pipeline can provide new opportunities to deliver more value (examples: automatic coding, code refactoring, continuous profiling, and others).
Further information here.
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.
See CONTRIBUTING.md for conventions, generator workflows, tests, and how to open a pull request.
The repository includes a collection of examples where you can explore what these Skills and workflows enable for Java.
- Review the ADR index for the complete list.
- Review the CHANGELOG for further details
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.
- Delegating Java tasks to Supervised AI Dev Pipelines
- https://vibekode.it/blog/cursor-ai-developer-cloud-platform/
- https://www.linkedin.com/pulse/september-rest-story-jvm-weekly-vol-146-artur-skowro%C5%84ski-82lif/?trackingId=wbWPSL65TpCCbdg5ksAWjw%3D%3D
- https://virtuslab.com/blog/ai/providing-library-documentation/
- https://www.cursor.com/
- https://cursor.com/cli
- https://www.anthropic.com/claude-code
- https://github.com/features/copilot
- https://cursor.com/docs/cli/github-actions
- https://code.claude.com/docs/en/github-actions
- https://agents.md/
- https://agentskills.io/home
- https://microsoft.github.io/language-server-protocol/
- https://openspec.dev/
- https://skills.sh/jabrena/cursor-rules-java
- https://tessl.io/registry/skills/github/jabrena/cursor-rules-java
- https://github.com/vercel-labs/skills/issues
- https://openjdk.org/jeps/0
- https://jbake.org/docs/latest/