feat: Add Deep Research System v4.2.0 (#380)

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>

Docs/User-Guide/agents.md

@@ -1,6 +1,6 @@
 # SuperClaude Agents Guide 🤖
 
-SuperClaude provides 14 domain specialist agents that Claude Code can invoke for specialized expertise.
+SuperClaude provides 15 domain specialist agents that Claude Code can invoke for specialized expertise.
 
 
 ## 🧪 Testing Agent Activation
@@ -243,6 +243,48 @@ Task Analysis →
 
 **Works Best With**: system-architect (infrastructure planning), security-engineer (compliance), performance-engineer (monitoring)
 
+---
+
+### deep-research-agent 🔬
+**Expertise**: Comprehensive research with adaptive strategies and multi-hop reasoning
+
+**Auto-Activation**:
+- Keywords: "research", "investigate", "discover", "explore", "find out", "search for", "latest", "current"
+- Commands: `/sc:research` automatically activates this agent
+- Context: Complex queries requiring thorough research, current information needs, fact-checking
+- Complexity: Questions spanning multiple domains or requiring iterative exploration
+
+**Capabilities**:
+- **Adaptive Planning Strategies**: Planning (direct), Intent (clarify first), Unified (collaborative)
+- **Multi-Hop Reasoning**: Up to 5 levels - entity expansion, temporal progression, conceptual deepening, causal chains
+- **Self-Reflective Mechanisms**: Progress assessment after each major step with replanning triggers
+- **Evidence Management**: Clear citations, relevance scoring, uncertainty acknowledgment
+- **Tool Orchestration**: Parallel-first execution with Tavily (search), Playwright (JavaScript content), Sequential (reasoning)
+- **Learning Integration**: Pattern recognition and strategy reuse via Serena memory
+
+**Research Depth Levels**:
+- **Quick**: Basic search, 1 hop, summary output
+- **Standard**: Extended search, 2-3 hops, structured report (default)
+- **Deep**: Comprehensive search, 3-4 hops, detailed analysis
+- **Exhaustive**: Maximum depth, 5 hops, complete investigation
+
+**Examples**:
+1. **Technical Research**: `/sc:research "latest React Server Components patterns"` → Comprehensive technical research with implementation examples
+2. **Market Analysis**: `/sc:research "AI coding assistants landscape 2024" --strategy unified` → Collaborative analysis with user input
+3. **Academic Investigation**: `/sc:research "quantum computing breakthroughs" --depth exhaustive` → Comprehensive literature review with evidence chains
+
+**Workflow Pattern** (6-Phase):
+1. **Understand** (5-10%): Assess query complexity
+2. **Plan** (10-15%): Select strategy and identify parallel opportunities  
+3. **TodoWrite** (5%): Create adaptive task hierarchy (3-15 tasks)
+4. **Execute** (50-60%): Parallel searches and extractions
+5. **Track** (Continuous): Monitor progress and confidence
+6. **Validate** (10-15%): Verify evidence chains
+
+**Output**: Reports saved to `claudedocs/research_[topic]_[timestamp].md`
+
+**Works Best With**: system-architect (technical research), learning-guide (educational research), requirements-analyst (market research)
+
 ### Quality & Analysis Agents 🔍
 
 ### security-engineer 🔒
@@ -618,6 +660,7 @@ After applying agent fixes, test with:
 | **Documentation** | "documentation", "readme", "API docs" | technical-writer |
 | **Learning** | "explain", "tutorial", "beginner", "teaching" | learning-guide |
 | **Requirements** | "requirements", "PRD", "specification" | requirements-analyst |
+| **Research** | "research", "investigate", "latest", "current" | deep-research-agent |
 
 ### Command-Agent Mapping
 
@@ -631,6 +674,7 @@ After applying agent fixes, test with:
 | `/sc:design` | system-architect | Domain architects, requirements-analyst |
 | `/sc:test` | quality-engineer | security-engineer, performance-engineer |
 | `/sc:explain` | learning-guide | technical-writer, domain specialists |
+| `/sc:research` | deep-research-agent | Technical specialists, learning-guide |
 
 ### Effective Agent Combinations