plinth
jabrena · jabrena/plinth
Provides an AI-native engineering toolkit with 125 skills, agents, and commands for modern Java enterprise SDLC workflows across various agents.
Plinth is an AI-native engineering toolkit for modern Java enterprise SDLC, built around reusable Commands, Agents, Skills, and MCP Servers.
Preview
What you can do with it
- Automate and standardize Java enterprise software development lifecycle practices.
- Leverage pre-built agents and commands for specific Java development tasks.
- Integrate an opinionated AI-native workflow into existing Java projects.
Safety check
No risky patterns found in the files we scanned.
Automated scan of the repo files. Always review code you run.
From the README
Plinth for Java
Help this project grow: Become a sponsor
Goal
An opinionated AI-native workflow for evolving modern Java Enterprise SDLC practices through reusable Skills, Agents, Commands & MCP servers.
What is a Plinth?
A
plinthrepresents the solid foundation or platform used to support statues or artworks in art and sculpture. It served as a structural and symbolic foundation for columns, statues, and entire temple podiums. Romans inherited the idea from Greek architecture but expanded its use to emphasize monumentality, hierarchy, and imperial power.
Project at a glance
- 14 Commands
- 9 Agents
- 125 Skills
Latest Updates
Explore the latest published content on https://jabrena.github.io/plinth/ and follow its evolution through new skills, improvements, and fixes in the CHANGELOG.
Start in 60 seconds
Install every skill for your preferred agent:
npx skills add jabrena/plinth --skill '*' --agent cursor -y
npx skills add jabrena/plinth --skill '*' --agent claude-code -y
npx skills add jabrena/plinth --skill '*' --agent codex -y
npx skills add jabrena/plinth --skill '*' --agent github-copilot -y
Install every command for your prefered agent:
install @004-commands-installation cursor
install @004-commands-installation claude-code
install @004-commands-installation codex
install @004-commands-installation github-copilot
Install every agent for your prefered agent:
install @005-agents-installation cursor
install @005-agents-installation claude-code
install @005-agents-installation codex
install @005-agents-installation github-copilot
See it in action
You can use the project in 2 ways:
- Use the AI-Native development workflow
- Refactor your code with Skills
Using the AI-Native development workflow
Prepare the repository with /onboarding, then identify an issue in your Kanban dashboard from Atlasian Jira, Github Issues or Azure DevOps and apply the following workflow:
/onboarding
|
v
Issue
|
v
/update-issue --> /explore-problem --> /create-acceptance-criteria
|
v
/create-spec --> /explore-design
|
v
/implement-spec --> /close-spec
/onboarding establishes root AGENTS.md and one unambiguous OpenSpec project before issue selection. It preserves existing prerequisites; when OpenSpec is missing, you select its result path with documentation/openspec as the default.
Analysis & Design
Turn an idea into an actionable change with user stories, GitHub Issues or Jira, ADRs, diagrams, AI plan mode, and OpenSpec.
Functional Specification:
Command
Explanation
<code>/onboarding</code>
Establish root repository guidance and one unambiguous OpenSpec project before issue work.
<code>/update-issue</code>
Update an existing GitHub or Jira issue with a structured user story, acceptance criteria, and resource content.
<code>/explore-problem</code>
Evaluate an issue from five perspectives and post a Functional Specification comment on the issue.
<code>/create-acceptance-criteria</code>
Derive Gherkin acceptance criteria from a Functional Specification and post them as a separate issue comment.
Technical Specification:
Command
Explanation
<code>/create-adr</code> (Optional)
Record an architectural decision, its alternatives, rationale, and consequences.
<code>/create-diagram</code> (Optional)
Create a focused architecture or design diagram from approved artifacts.
<code>/create-spec</code> (OpenSpec)
Create or update one or more validated OpenSpec changes.
<code>/explore-design</code>
Compare technical approaches and obtain an approved design direction.
Build
Implement and improve Java applications with Maven, design, coding, testing, security, documentation, Spring Boot, Quarkus, Micronaut, OpenAPI, and WireMock guidance.
Command
Explanation
<code>/implement-spec</code>
Deliver an approved plan or validated OpenSpec task list through framework-aware delegation.
<code>/close-spec</code>
Archive an OpenSpec change by name using the OpenSpec CLI.
Operate
Measure and improve production behavior through observability, profiling, benchmarking, and performance testing.
Command
Explanation
<code>/profile</code>
Coordinate Java profiling from baseline detection through verified optimization.
<code>/benchmark</code>
Select and coordinate JMeter, Gatling, or JMH performance workflows.
Compliance (Alpha)
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-reg |