AIUP Plugins and Extensions
Overview
AIUP plugins are specialized extensions that integrate with Claude Code to implement the AIUP methodology within AI-powered development environments. The plugin architecture enables both explicit commands and autonomous behaviors, allowing developers to leverage AI-assisted development following requirements-driven principles.
Plugin Architecture
AIUP Tools leverage multiple plugin component types to integrate with Claude Code:
Core Plugin Components
Slash-invoked instructions
- Markdown-defined commands with
/plugin-name:commandsyntax - Guide Claude through specific tasks explicitly
- User-initiated workflow triggers
Autonomous behaviors
- Claude automatically invokes when recognizing matching tasks
- No explicit command required
- Integrated into workflow detection
External services
- Integrations providing access to specialized tools and documentation
- API integrations
- Browser automation capabilities
Specialized AI assistants
- Task-specific assistants operating in isolated context windows
- Enable autonomous delegation for complex tasks
- Maintain focus and scope control
Event handlers
- Automated execution in response to Claude Code events
- Custom workflow automation
- Integration with development environment events
Current Implementations
Vaadin + jOOQ Plugin for Java
Technology Stack:
- Vaadin: Modern Java UI framework
- jOOQ: Type-safe database access layer
Capabilities:
- Generate Vaadin UI components and layouts
- Create jOOQ database queries with type safety
- Integrate requirements into Java web application development
- Maintain consistency between data models and UI
Use Cases:
- Java web application scaffolding
- Full-stack feature generation
- Database-driven UI development
Plugin Ecosystem Expansion
AIUP explicitly welcomes community contributions for technology-specific plugins beyond the current Java/Vaadin offering.
Potential Plugin Categories
Frontend Frameworks
- React/Vue/Angular plugins
- Next.js/SvelteKit plugins
- Mobile framework plugins
Backend/Database
- Node.js/Python/Go plugins
- PostgreSQL/MongoDB specific plugins
- ORM-specific plugins (Prisma, SQLAlchemy, etc.)
Cloud/Infrastructure
- AWS/Azure/GCP deployment plugins
- Kubernetes/Docker plugins
- Infrastructure-as-Code plugins
Domain-Specific
- Mobile development plugins
- Game development plugins
- Data science/ML pipeline plugins
Integration with AIUP Workflow
Plugins integrate at key points in the AIUP development workflow:
- Requirements to Specifications - Transform business requirements into technical specifications
- Specifications to Models - Generate entity models and architecture diagrams
- Models to Code - Transform use case specifications into production-ready code
- Code to Tests - Generate test suites ensuring behavior consistency
Plugin Execution Model
Explicit Invocation
/plugin-name:command-name <parameters>
Autonomous Invocation
- Claude recognizes need for plugin capabilities
- Automatically invokes without user command
- Maintains context and decision-making
Service Integration
- Access external documentation and references
- Call specialized services and tools
- Integrate with broader development ecosystem
Benefits of Plugin Architecture
✓ Methodology enforcement: Ensures AIUP principles are followed
✓ Technology expertise: Domain-specific knowledge for each tech stack
✓ Consistency: Standardized approach to code generation
✓ Extensibility: New plugins for emerging technologies
✓ Maintainability: Specialized plugins enable better output quality
Development and Contribution
The AIUP plugin ecosystem is open to community contributions. Plugin developers can create specialized implementations for:
- New technology stacks
- Domain-specific workflows
- Industry-specific requirements
- Organizational best practices
Related Tools
- Claude Code - Host environment for plugins
- AI Unified Process - Parent methodology
- Model Context Protocol - Extensibility framework
- IDE extensions and integrations
Last updated: 2026-01-23