AtlasAI-CLI Roadmap

[FredyRivera-dev]

Immediate Fixes Needed

1. Fix Rich library formatting issues - There are inconsistencies in how rich text formatting tags are closed (e.g., [/bold] vs [/bold red]), causing errors in the interactive mode
2. Command security improvements - Current approach allows all safe commands without considering context; needs more granular security control
3. Error handling standardization - Different parts of the code handle errors differently; should standardize error handling patterns
4. Configuration validation - Add validation when loading AI configurations to prevent runtime errors

AtlasAI-CLI Roadmap

Phase 1: Stability and Core Improvements

• 1.1 Task System Implementation

  • Implement task parser for markdown files
  • Create task dependency graph execution engine
  • Add task template generator
  • Implement task status tracking

• 1.2 Error Handling & Stability

  • Standardize error handling across modules
  • Implement better exception reporting with stack traces
  • Add proper logging with configurable verbosity levels
  • Create self-diagnosis tool for troubleshooting

• 1.3 Code Quality Improvements

  • Refactor duplicate code in command handlers
  • Add comprehensive unit tests (target 80% coverage)
  • Implement CI pipeline for automated testing
  • Standardize docstring format across codebase

Phase 2: Feature Enhancements

• 2.1 Advanced AI Integrations

  • Add support for additional AI providers (Anthropic, local LLMs, Gemini, etc.)
  • Implement model caching to reduce API costs
  • Add fine-tuning capabilities for project-specific models
  • Create model fallback chain for reliability

• 2.2 Enhanced Project Analysis

  • Improve framework detection accuracy
  • Add support for more frameworks and project types
  • Implement deeper dependency analysis
  • Add performance optimization suggestions

• 2.3 Interactive Experience

  • Enhance chat session with command history and context management
  • Add autocompletion for CLI commands
  • Implement code editor integration plugins (VSCode, PyCharm) (Maybe)
  • Create TUI (Text User Interface) for better visualization

Phase 3: Advanced Automation

• 3.1 Advanced Task Workflows

  • Implement parallel task execution
  • Add conditional task branching
  • Create task templates library
  • Support for task scheduling and automation triggers

• 3.2 Project Management Integration

  • Implement Git integration for workflow automation
  • Add CI/CD pipeline generation
  • Create project scaffolding capabilities
  • Support for project templating

• 3.3 Collaborative Features

  • Add team sharing for AI configurations
  • Implement workflow sharing and versioning
  • Create multi-user task coordination
  • Support for task delegation and assignment

Phase 4: Ecosystem Expansion

• 4.1 Plugin System

  • Design extensible plugin architecture
  • Create plugin registry and discovery mechanism
  • Implement plugin management commands
  • Develop SDK for third-party developers

• 4.2 Enterprise Features

  • Add team management and permissions
  • Implement audit logging
  • Create enterprise authentication integrations
  • Add compliance and governance features

• 4.3 API and Service Integration

  • Create HTTP API for programmatic access
  • Add webhooks for event-driven automation
  • Implement service mesh for microservices architecture
  • Create containerized version for cloud deployments