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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>
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@@ -466,4 +466,48 @@ def create_env_file(api_keys: Dict[str, str], env_file_path: Optional[Path] = No
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except Exception as e:
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logger.error(f"Failed to create .env file: {e}")
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display_warning(f"Could not create .env file: {e}")
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return False
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return False
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def check_research_prerequisites() -> tuple[bool, list[str]]:
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"""
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Check if deep research prerequisites are met
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Returns:
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Tuple of (success: bool, warnings: List[str])
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"""
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warnings = []
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logger = get_logger()
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# Check Tavily API key
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if not os.environ.get("TAVILY_API_KEY"):
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warnings.append(
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"TAVILY_API_KEY not set - Deep research web search will not work\n"
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"Get your key from: https://app.tavily.com"
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)
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logger.warning("TAVILY_API_KEY not found in environment")
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else:
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logger.info("Found TAVILY_API_KEY in environment")
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# Check Node.js for MCP
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import shutil
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if not shutil.which("node"):
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warnings.append(
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"Node.js not found - Required for Tavily MCP\n"
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"Install from: https://nodejs.org"
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)
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logger.warning("Node.js not found - required for Tavily MCP")
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else:
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logger.info("Node.js found")
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# Check npm
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if not shutil.which("npm"):
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warnings.append(
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"npm not found - Required for MCP server installation\n"
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"Usually installed with Node.js"
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)
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logger.warning("npm not found - required for MCP installation")
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else:
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logger.info("npm found")
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return len(warnings) == 0, warnings
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