feat: Add Deep Research System v4.2.0 - Autonomous web research capabilities
## Overview
Comprehensive implementation of Deep Research framework aligned with DR Agent architecture, enabling autonomous, adaptive, and intelligent web research capabilities.
## Key Features
### 🔬 Deep Research Agent
- 15th specialized agent for comprehensive research orchestration
- Adaptive planning strategies: Planning-Only, Intent-Planning, Unified Intent-Planning
- Multi-hop reasoning with genealogy tracking (up to 5 hops)
- Self-reflective mechanisms with confidence scoring (0.0-1.0)
- Case-based learning for cross-session intelligence
### 🎯 New /sc:research Command
- Intelligent web research with depth control (quick/standard/deep/exhaustive)
- Parallel-first execution for optimal performance
- Domain filtering and time-based search options
- Automatic report generation in claudedocs/
### 🔍 Tavily MCP Integration
- 7th MCP server for real-time web search
- News search with time filtering
- Content extraction from search results
- Multi-round searching with iterative refinement
- Free tier available with optional API key
### 🎨 MODE_DeepResearch
- 7th behavioral mode for systematic investigation
- 6-phase workflow: Understand → Plan → TodoWrite → Execute → Track → Validate
- Evidence-based reasoning with citation management
- Parallel operation defaults for efficiency
## Technical Changes
### Framework Updates
- Updated agent count: 14 → 15 agents
- Updated mode count: 6 → 7 modes
- Updated MCP server count: 6 → 7 servers
- Updated command count: 24 → 25 commands
### Configuration
- Added RESEARCH_CONFIG.md for research settings
- Added deep_research_workflows.md with examples
- Standardized file naming conventions (UPPERCASE for Core)
- Removed multi-source investigation features for simplification
### Integration Points
- Enhanced MCP component with remote server support
- Added check_research_prerequisites() in environment.py
- Created verify_research_integration.sh script
- Updated all documentation guides
## Requirements
- TAVILY_API_KEY environment variable (free tier available)
- Node.js and npm for Tavily MCP execution
## Documentation
- Complete user guide integration
- Workflow examples and best practices
- API configuration instructions
- Depth level explanations
🤖 Generated with Claude Code
Co-authored-by: moshe_anconina <moshe_a@ituran.com>
Co-authored-by: Claude <noreply@anthropic.com>
## Version Management & Consistency
- Update to version 4.0.0b1 (proper beta versioning for PyPI)
- Add __version__ attribute to SuperClaude/__init__.py
- Ensure version consistency across pyproject.toml, __main__.py, setup/__init__.py
## Enhanced Package Configuration
- Improve pyproject.toml with comprehensive PyPI classifiers
- Add proper license specification and enhanced metadata
- Configure package discovery with inclusion/exclusion patterns
- Add development and test dependencies
## Publishing Scripts & Tools
- scripts/build_and_upload.py: Advanced Python script for building and uploading
- scripts/publish.sh: User-friendly shell wrapper for common operations
- scripts/validate_pypi_ready.py: Comprehensive validation and readiness checker
- All scripts executable with proper error handling and validation
## GitHub Actions Automation
- .github/workflows/publish-pypi.yml: Complete CI/CD pipeline
- Automatic publishing on GitHub releases
- Manual workflow dispatch for TestPyPI uploads
- Package validation and installation testing
## Documentation & Security
- PUBLISHING.md: Comprehensive PyPI publishing guide
- scripts/README.md: Detailed script usage documentation
- .env.example: Environment variable template
- Secure token handling with both .pypirc and environment variables
## Features
✅ Version consistency validation across all files
✅ Comprehensive PyPI metadata and classifiers
✅ Multi-environment publishing (TestPyPI + PyPI)
✅ Automated GitHub Actions workflow
✅ Security best practices for API token handling
✅ Complete documentation and troubleshooting guides
✅ Enterprise-grade validation and error handling
The SuperClaude Framework is now fully prepared for PyPI publication
with professional-grade automation, validation, and documentation.
🤖 Generated with [Claude Code](https://claude.ai/code)
Co-Authored-By: Claude <noreply@anthropic.com>
