This roadmap outlines the planned development path for the GhostForge project. It is subject to change based on community feedback and evolving priorities.
While we have comprehensive unit tests, we should now create integration tests that verify the components work together properly:
- Test the full workflow from file indexing to search to analysis
- Test the interaction between the CLI, shell, and analysis components
- Test with various real-world projects to ensure robustness
Create comprehensive documentation for:
- Installation and setup instructions
- User guide for each command and functionality
- Configuration options and customization
- API documentation for developers wanting to extend GhostForge
- Example use cases and tutorials
Improve the effectiveness of the analysis by:
- Refining the existing prompts based on test results
- Creating specialized prompts for specific technologies and vulnerabilities
- Adding more detailed remediation suggestions
- Optimizing token usage for better performance
Expand GhostForge's capabilities:
- Implement Tiny LLM Filesystem Tool for secure file operations and command execution
- Add support for cloud infrastructure analysis (AWS, Azure, GCP)
- Implement cost optimization analysis
- Add performance optimization suggestions
- Implement dependency vulnerability scanning
- Add custom rule sets for specific enterprise requirements
Enhance user experience:
- Create a web UI for visualizing analysis results
- Implement interactive reporting dashboards
- Add export functionality to common formats (PDF, HTML, JSON)
- Create a VS Code/IDE extension for in-editor analysis
Prepare for wider distribution:
- Ensure proper packaging with setuptools
- Create Docker images for containerized usage
- Set up CI/CD for the GhostForge project itself
- Prepare for PyPI publication
- Create installation scripts for various platforms
Improve speed and efficiency:
- Profile the application to identify bottlenecks
- Optimize database queries and indexing
- Implement caching for common operations
- Parallelize operations where possible
- Reduce memory footprint
Establish a community around the project:
- Create a project website
- Set up communication channels (Discord, forums)
- Define contribution guidelines
- Create roadmap for future development
- Establish governance model for the project
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Short-term (1-2 months):
- Complete integration tests
- Create basic documentation
- Refine LLM prompts
- Implement Tiny LLM Filesystem Tool (phase 1-3)
- Package for PyPI
-
Medium-term (3-6 months):
- Complete Tiny LLM Filesystem Tool (phase 4-5)
- Add cloud infrastructure analysis
- Implement dependency scanning
- Create a web UI
- Performance optimization
-
Long-term (6+ months):
- VS Code/IDE extensions
- Community building
- Enhanced reporting and visualization
- Custom enterprise integrations
The implementation will proceed in 5 phases:
-
Phase 1 (1 week): Core Functionality
- Implement file read/write operations with path validation
- Implement directory listing and navigation
- Basic logging infrastructure
-
Phase 2 (1 week): Sandbox & Execution
- Implement Docker-based sandboxing
- Command execution with security controls
- User confirmation system
-
Phase 3 (1 week): Git & Advanced Features
- Git repository operations
- Dependency management
- Diffing and patching support
-
Phase 4 (1 week): GhostForge Integration
- Add custom commands to GhostForge shell
- Configure LLM prompting for tool usage
- GUI confirmation dialogs (if applicable)
-
Phase 5 (1 week): Production Readiness
- Comprehensive testing and security review
- Documentation and examples
- Performance optimization