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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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Moshe Anconina
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CHANGELOG.md
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CHANGELOG.md
@ -7,6 +7,37 @@ and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0
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## [Unreleased]
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## [4.2.0] - 2025-09-18
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### Added
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- **Deep Research System** - Complete implementation of autonomous web research capabilities
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- New `/sc:research` command for intelligent web research with DR Agent architecture
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- `deep-research-agent` - 15th specialized agent for research orchestration
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- `MODE_DeepResearch` - 7th behavioral mode for research workflows
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- Tavily MCP integration (7th MCP server) for real-time web search
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- Research configuration system (`RESEARCH_CONFIG.md`)
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- Comprehensive workflow examples (`deep_research_workflows.md`)
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- Three planning strategies: Planning-Only, Intent-to-Planning, Unified Intent-Planning
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- Multi-hop reasoning with genealogy tracking for complex queries
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- Case-based reasoning for learning from past research patterns
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### Changed
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- Updated agent count from 14 to 15 (added deep-research-agent)
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- Updated mode count from 6 to 7 (added MODE_DeepResearch)
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- Updated MCP server count from 6 to 7 (added Tavily)
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- Updated command count from 24 to 25 (added /sc:research)
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- Enhanced MCP component with remote server support for Tavily
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- Added `_install_remote_mcp_server` method to handle remote MCP configurations
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### Technical
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- Added Tavily to `server_docs_map` in `setup/components/mcp_docs.py`
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- Implemented remote MCP server handler in `setup/components/mcp.py`
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- Added `check_research_prerequisites()` function in `setup/utils/environment.py`
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- Created verification script `scripts/verify_research_integration.sh`
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### Requirements
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- `TAVILY_API_KEY` environment variable for web search functionality
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- Node.js and npm for Tavily MCP execution
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## [4.1.4] - 2025-09-20
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### Added
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- Comprehensive flag documentation integrated into `/sc:help` command
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@ -19,7 +50,6 @@ and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0
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- Smart server merging (existing + selected + previously installed)
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- Documentation cleanup: removed non-existent commands (sc:fix, sc:simple-pix, sc:update, sc:develop, sc:modernize, sc:simple-fix)
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- CLI logic to allow mcp_docs installation without server selection
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### Changed
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- MCP component now supports true incremental installation
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- mcp_docs component auto-detects and installs documentation for all detected servers
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@ -34,14 +34,19 @@ This guide documents how SuperClaude's Context-Oriented Configuration Framework
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├── MCP_Playwright.md # Playwright MCP integration
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├── MCP_Sequential.md # Sequential MCP integration
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├── MCP_Serena.md # Serena MCP integration
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├── MCP_Tavily.md # Tavily MCP integration
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├── MCP_Zig.md # Zig MCP integration
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├── MODE_Brainstorming.md # Collaborative discovery mode
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├── MODE_Business_Panel.md # Business expert panel mode
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├── MODE_DeepResearch.md # Deep research mode
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├── MODE_Introspection.md # Transparent reasoning mode
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├── MODE_Orchestration.md # Tool coordination mode
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├── MODE_Task_Management.md # Task orchestration mode
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├── MODE_Token_Efficiency.md # Compressed communication mode
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├── agents/ # Domain specialist contexts (14 total)
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├── agents/ # Domain specialist contexts (19 total)
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│ ├── backend-architect.md # Backend expertise
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│ ├── business-panel-experts.md # Business strategy panel
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│ ├── deep-research-agent.md # Deep research expertise
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│ ├── devops-architect.md # DevOps expertise
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│ ├── frontend-architect.md # Frontend expertise
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│ ├── learning-guide.md # Educational expertise
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@ -53,27 +58,34 @@ This guide documents how SuperClaude's Context-Oriented Configuration Framework
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│ ├── root-cause-analyst.md # Problem diagnosis expertise
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│ ├── security-engineer.md # Security expertise
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│ ├── socratic-mentor.md # Educational expertise
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│ ├── spec-panel-experts.md # Specification review panel
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│ ├── system-architect.md # System design expertise
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│ └── technical-writer.md # Documentation expertise
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│ ├── technical-writer.md # Documentation expertise
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│ ├── test-runner.md # Test execution expertise
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│ └── wave-orchestrator.md # Wave orchestration patterns
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└── commands/ # Workflow pattern contexts
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└── sc/ # SuperClaude command namespace (21 total)
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└── sc/ # SuperClaude command namespace (25 total)
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├── analyze.md # Analysis patterns
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├── brainstorm.md # Discovery patterns
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├── build.md # Build patterns
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├── business-panel.md # Business expert panel patterns
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├── cleanup.md # Cleanup patterns
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├── design.md # Design patterns
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├── document.md # Documentation patterns
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├── estimate.md # Estimation patterns
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├── explain.md # Explanation patterns
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├── git.md # Git workflow patterns
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├── help.md # Help and command listing
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├── implement.md # Implementation patterns
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├── improve.md # Improvement patterns
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├── index.md # Index patterns
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├── load.md # Context loading patterns
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├── reflect.md # Reflection patterns
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├── research.md # Deep research patterns
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├── save.md # Session persistence patterns
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├── select-tool.md # Tool selection patterns
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├── spawn.md # Multi-agent patterns
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├── spec-panel.md # Specification review panel
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├── task.md # Task management patterns
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├── test.md # Testing patterns
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├── troubleshoot.md # Troubleshooting patterns
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@ -112,9 +124,12 @@ The main `CLAUDE.md` file uses an import system to load multiple context files:
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@MCP_Playwright.md # Playwright MCP integration
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@MCP_Sequential.md # Sequential MCP integration
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@MCP_Serena.md # Serena MCP integration
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@MCP_Tavily.md # Tavily MCP integration
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@MCP_Zig.md # Zig MCP integration
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*CRITICAL*
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@MODE_Brainstorming.md # Collaborative discovery mode
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@MODE_Business_Panel.md # Business expert panel mode
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@MODE_DeepResearch.md # Deep research mode
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@MODE_Introspection.md # Transparent reasoning mode
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@MODE_Task_Management.md # Task orchestration mode
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@MODE_Orchestration.md # Tool coordination mode
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@ -1,6 +1,6 @@
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# SuperClaude Agents Guide 🤖
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SuperClaude provides 14 domain specialist agents that Claude Code can invoke for specialized expertise.
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SuperClaude provides 15 domain specialist agents that Claude Code can invoke for specialized expertise.
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## 🧪 Testing Agent Activation
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@ -243,6 +243,48 @@ Task Analysis →
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**Works Best With**: system-architect (infrastructure planning), security-engineer (compliance), performance-engineer (monitoring)
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---
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### deep-research-agent 🔬
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**Expertise**: Comprehensive research with adaptive strategies and multi-hop reasoning
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**Auto-Activation**:
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- Keywords: "research", "investigate", "discover", "explore", "find out", "search for", "latest", "current"
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- Commands: `/sc:research` automatically activates this agent
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- Context: Complex queries requiring thorough research, current information needs, fact-checking
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- Complexity: Questions spanning multiple domains or requiring iterative exploration
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**Capabilities**:
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- **Adaptive Planning Strategies**: Planning (direct), Intent (clarify first), Unified (collaborative)
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- **Multi-Hop Reasoning**: Up to 5 levels - entity expansion, temporal progression, conceptual deepening, causal chains
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- **Self-Reflective Mechanisms**: Progress assessment after each major step with replanning triggers
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- **Evidence Management**: Clear citations, relevance scoring, uncertainty acknowledgment
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- **Tool Orchestration**: Parallel-first execution with Tavily (search), Playwright (JavaScript content), Sequential (reasoning)
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- **Learning Integration**: Pattern recognition and strategy reuse via Serena memory
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**Research Depth Levels**:
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- **Quick**: Basic search, 1 hop, summary output
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- **Standard**: Extended search, 2-3 hops, structured report (default)
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- **Deep**: Comprehensive search, 3-4 hops, detailed analysis
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- **Exhaustive**: Maximum depth, 5 hops, complete investigation
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**Examples**:
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1. **Technical Research**: `/sc:research "latest React Server Components patterns"` → Comprehensive technical research with implementation examples
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2. **Market Analysis**: `/sc:research "AI coding assistants landscape 2024" --strategy unified` → Collaborative analysis with user input
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3. **Academic Investigation**: `/sc:research "quantum computing breakthroughs" --depth exhaustive` → Comprehensive literature review with evidence chains
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**Workflow Pattern** (6-Phase):
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1. **Understand** (5-10%): Assess query complexity
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2. **Plan** (10-15%): Select strategy and identify parallel opportunities
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3. **TodoWrite** (5%): Create adaptive task hierarchy (3-15 tasks)
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4. **Execute** (50-60%): Parallel searches and extractions
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5. **Track** (Continuous): Monitor progress and confidence
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6. **Validate** (10-15%): Verify evidence chains
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**Output**: Reports saved to `claudedocs/research_[topic]_[timestamp].md`
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**Works Best With**: system-architect (technical research), learning-guide (educational research), requirements-analyst (market research)
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### Quality & Analysis Agents 🔍
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### security-engineer 🔒
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| **Documentation** | "documentation", "readme", "API docs" | technical-writer |
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| **Learning** | "explain", "tutorial", "beginner", "teaching" | learning-guide |
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| **Requirements** | "requirements", "PRD", "specification" | requirements-analyst |
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| **Research** | "research", "investigate", "latest", "current" | deep-research-agent |
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### Command-Agent Mapping
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@ -631,6 +674,7 @@ After applying agent fixes, test with:
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| `/sc:design` | system-architect | Domain architects, requirements-analyst |
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| `/sc:test` | quality-engineer | security-engineer, performance-engineer |
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| `/sc:explain` | learning-guide | technical-writer, domain specialists |
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| `/sc:research` | deep-research-agent | Technical specialists, learning-guide |
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### Effective Agent Combinations
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@ -1,6 +1,6 @@
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# SuperClaude Commands Guide
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SuperClaude provides 24 commands for Claude Code: `/sc:*` commands for workflows and `@agent-*` for specialists.
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SuperClaude provides 25 commands for Claude Code: `/sc:*` commands for workflows and `@agent-*` for specialists.
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## Command Types
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@ -106,7 +106,7 @@ python3 -m SuperClaude install --list-components | grep mcp
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- [Essential Commands](#essential-commands) - Start here (8 core commands)
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- [Common Workflows](#common-workflows) - Command combinations that work
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- [Full Command Reference](#full-command-reference) - All 23 commands organized by category
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- [Full Command Reference](#full-command-reference) - All 25 commands organized by category
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- [Troubleshooting](#troubleshooting) - Common issues and solutions
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- [Command Index](#command-index) - Find commands by category
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@ -133,6 +133,24 @@ python3 -m SuperClaude install --list-components | grep mcp
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- Discovering available commands: `/sc:help`
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- Getting a quick reminder of command names: `/sc:help`
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### `/sc:research` - Deep Research Command
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**Purpose**: Comprehensive web research with adaptive planning and intelligent search
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**Syntax**: `/sc:research "[query]"` `[--depth quick|standard|deep|exhaustive] [--strategy planning|intent|unified]`
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**Use Cases**:
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- Technical research: `/sc:research "latest React 19 features" --depth deep`
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- Market analysis: `/sc:research "AI coding assistant landscape 2024" --strategy unified`
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- Academic investigation: `/sc:research "quantum computing breakthroughs" --depth exhaustive`
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- Current events: `/sc:research "latest AI developments 2024"`
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**Key Capabilities**:
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- **6-Phase Workflow**: Understand → Plan → TodoWrite → Execute → Track → Validate
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- **Adaptive Depth**: Quick (basic search), Standard (extended), Deep (comprehensive), Exhaustive (maximum depth)
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- **Planning Strategies**: Planning (direct), Intent (clarify first), Unified (collaborative)
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- **Parallel Execution**: Default parallel searches and extractions
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- **Evidence Management**: Clear citations with relevance scoring
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- **Output Standards**: Reports saved to `claudedocs/research_[topic]_[timestamp].md`
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### `/sc:implement` - Feature Development
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**Purpose**: Full-stack feature implementation with intelligent specialist routing
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**Syntax**: `/sc:implement "feature description"` `[--type frontend|backend|fullstack] [--focus security|performance]`
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@ -277,6 +295,7 @@ python3 -m SuperClaude install --list-components | grep mcp
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| Command | Purpose | Best For |
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|---------|---------|----------|
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| **analyze** | Code assessment | Quality audits, security reviews |
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| **research** | Web research with intelligent search | Technical research, current events, market analysis |
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| **business-panel** | Strategic analysis | Business decisions, competitive assessment |
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| **spec-panel** | Specification review | Requirements validation, architecture analysis |
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| **troubleshoot** | Problem diagnosis | Bug investigation, performance issues |
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@ -2,7 +2,7 @@
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## Overview
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MCP (Model Context Protocol) servers extend Claude Code's capabilities through specialized tools. SuperClaude integrates 6 MCP servers and provides Claude with instructions on when to activate them based on your tasks.
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MCP (Model Context Protocol) servers extend Claude Code's capabilities through specialized tools. SuperClaude integrates 7 MCP servers and provides Claude with instructions on when to activate them based on your tasks.
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### 🔍 Reality Check
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- **What MCP servers are**: External Node.js processes that provide additional tools
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@ -17,6 +17,7 @@ MCP (Model Context Protocol) servers extend Claude Code's capabilities through s
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- **playwright**: Browser automation and E2E testing
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- **morphllm-fast-apply**: Pattern-based code transformations
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- **serena**: Semantic code understanding and project memory
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- **tavily**: Web search and real-time information retrieval
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## Quick Start
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@ -32,6 +33,7 @@ MCP (Model Context Protocol) servers extend Claude Code's capabilities through s
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| `test`, `e2e`, `browser` | **playwright** |
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| Multi-file edits, refactoring | **morphllm-fast-apply** |
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| Large projects, sessions | **serena** |
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| `/sc:research`, `latest`, `current` | **tavily** |
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## Server Details
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@ -119,6 +121,36 @@ export MORPH_API_KEY="your_key_here"
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/sc:refactor "extract UserService" --serena
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```
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### tavily 🔍
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**Purpose**: Web search and real-time information retrieval for research
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**Triggers**: `/sc:research` commands, "latest" information requests, current events, fact-checking
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**Requirements**: Node.js 16+, TAVILY_API_KEY (free tier available at https://app.tavily.com)
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```bash
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# Automatic activation
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/sc:research "latest AI developments 2024"
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# → Performs intelligent web research
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# Manual activation
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/sc:analyze "market trends" --tavily
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# API key setup (get free key at https://app.tavily.com)
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export TAVILY_API_KEY="tvly-your_api_key_here"
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```
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**Capabilities:**
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- **Web Search**: Comprehensive searches with ranking and filtering
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- **News Search**: Time-filtered current events and updates
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- **Content Extraction**: Full-text extraction from search results
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- **Domain Filtering**: Include/exclude specific domains
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- **Multi-Hop Research**: Iterative searches based on findings (up to 5 hops)
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**Research Depth Control:**
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- `--depth quick`: 5-10 sources, basic synthesis
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- `--depth standard`: 10-20 sources, structured report (default)
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- `--depth deep`: 20-40 sources, comprehensive analysis
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- `--depth exhaustive`: 40+ sources, academic-level research
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## Configuration
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**MCP Configuration File (`~/.claude.json`):**
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"serena": {
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"command": "uvx",
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"args": ["--from", "git+https://github.com/oraios/serena", "serena", "start-mcp-server", "--context", "ide-assistant"]
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},
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"tavily": {
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"command": "npx",
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"args": ["-y", "@tavily/mcp@latest"],
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"env": {"TAVILY_API_KEY": "${TAVILY_API_KEY}"}
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}
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}
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}
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# For Morphllm server (required for bulk transformations)
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export MORPH_API_KEY="your_key_here"
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# For Tavily server (required for web search - free tier available)
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export TAVILY_API_KEY="tvly-your_key_here"
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# Add to shell profile for persistence
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echo 'export TWENTYFIRST_API_KEY="your_key"' >> ~/.bashrc
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echo 'export MORPH_API_KEY="your_key"' >> ~/.bashrc
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echo 'export TAVILY_API_KEY="your_key"' >> ~/.bashrc
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```
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**Environment Variable Usage:**
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- ✅ `TWENTYFIRST_API_KEY` - Required for Magic MCP server functionality
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- ✅ `MORPH_API_KEY` - Required for Morphllm MCP server functionality
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- ✅ `TAVILY_API_KEY` - Required for Tavily MCP server functionality (free tier available)
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- ❌ Other env vars in docs - Examples only, not used by framework
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- 📝 Both are paid service API keys, framework works without them
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- 📝 Magic and Morphllm are paid services, Tavily has free tier, framework works without them
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## Server Combinations
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@ -238,6 +280,8 @@ echo 'export MORPH_API_KEY="your_key"' >> ~/.bashrc
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- **Web Development**: magic + context7 + playwright
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- **Enterprise Refactoring**: serena + morphllm + sequential-thinking
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- **Complex Analysis**: sequential-thinking + context7 + serena
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- **Deep Research**: tavily + sequential-thinking + serena + playwright
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- **Current Events**: tavily + context7 + sequential-thinking
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## Integration
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@ -245,11 +289,13 @@ echo 'export MORPH_API_KEY="your_key"' >> ~/.bashrc
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- Analysis commands automatically use Sequential + Serena
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- Implementation commands use Magic + Context7
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- Testing commands use Playwright + Sequential
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- Research commands use Tavily + Sequential + Playwright
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**With Behavioral Modes:**
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- Brainstorming Mode: Sequential for discovery
|
||||
- Task Management: Serena for persistence
|
||||
- Orchestration Mode: Optimal server selection
|
||||
- Deep Research Mode: Tavily + Sequential + Playwright coordination
|
||||
|
||||
**Performance Control:**
|
||||
- Automatic resource management based on system load
|
||||
|
||||
@ -9,6 +9,7 @@ Test modes by using `/sc:` commands - they activate automatically based on task
|
||||
|------|---------|---------------|---------------|---------------|
|
||||
| **🧠 Brainstorming** | Interactive discovery | "brainstorm", "maybe", vague requests | Socratic questions, requirement elicitation | New project planning, unclear requirements |
|
||||
| **🔍 Introspection** | Meta-cognitive analysis | Error recovery, "analyze reasoning" | Transparent thinking markers (🤔, 🎯, 💡) | Debugging, learning, optimization |
|
||||
| **🔬 Deep Research** | Systematic investigation mindset | `/sc:research`, investigation keywords | 6-phase workflow, evidence-based reasoning | Technical research, current events, market analysis |
|
||||
| **📋 Task Management** | Complex coordination | >3 steps, >2 directories | Phase breakdown, memory persistence | Multi-step operations, project management |
|
||||
| **🎯 Orchestration** | Intelligent tool selection | Multi-tool ops, high resource usage | Optimal tool routing, parallel execution | Complex analysis, performance optimization |
|
||||
| **⚡ Token Efficiency** | Compressed communication | High context usage, `--uc` flag | Symbol systems, estimated 30-50% token reduction | Resource constraints, large operations |
|
||||
@ -120,6 +121,60 @@ Introspective Approach:
|
||||
|
||||
---
|
||||
|
||||
### 🔬 Deep Research Mode - Systematic Investigation Mindset
|
||||
|
||||
**Purpose**: Research mindset for systematic investigation and evidence-based reasoning.
|
||||
|
||||
**Auto-Activation Triggers:**
|
||||
- `/sc:research` command invocation
|
||||
- Research-related keywords: investigate, explore, discover, analyze
|
||||
- Questions requiring current information beyond knowledge cutoff
|
||||
- Complex research requirements
|
||||
- Manual flag: `--research`
|
||||
|
||||
**Behavioral Modifications:**
|
||||
- **Thinking Style**: Systematic over casual, evidence over assumption, progressive depth exploration
|
||||
- **Communication**: Lead with confidence levels, provide inline citations, acknowledge uncertainties
|
||||
- **Priority Shifts**: Completeness over speed, accuracy over speculation, verification over assumption
|
||||
- **Process Adaptations**: Always create investigation plans, default to parallel operations, maintain evidence chains
|
||||
|
||||
**6-Phase Research Workflow:**
|
||||
- 📋 **Understand** (5-10%): Assess query complexity and requirements
|
||||
- 📝 **Plan** (10-15%): Select strategy (planning/intent/unified) and identify parallelization
|
||||
- ✅ **TodoWrite** (5%): Create adaptive task hierarchy (3-15 tasks based on complexity)
|
||||
- 🔄 **Execute** (50-60%): Parallel-first searches and smart extraction routing
|
||||
- 📊 **Track** (Continuous): Monitor progress and update confidence scores
|
||||
- ✓ **Validate** (10-15%): Verify evidence chains and ensure completeness
|
||||
|
||||
**Example Experience:**
|
||||
```
|
||||
Standard Mode: "Here are some search results about quantum computing..."
|
||||
Deep Research Mode:
|
||||
"📊 Research Plan: Quantum computing breakthroughs
|
||||
✓ TodoWrite: Created 8 research tasks
|
||||
🔄 Executing parallel searches across domains
|
||||
📈 Confidence: 0.82 across 15 verified sources
|
||||
📝 Report saved: claudedocs/research_quantum_[timestamp].md"
|
||||
```
|
||||
|
||||
#### Quality Standards
|
||||
- [ ] Minimum 2 sources per claim with inline citations
|
||||
- [ ] Confidence scoring (0.0-1.0) for all findings
|
||||
- [ ] Parallel execution by default for independent operations
|
||||
- [ ] Reports saved to claudedocs/ with proper structure
|
||||
- [ ] Clear methodology and evidence presentation
|
||||
|
||||
**Verify:** `/sc:research "test topic"` should create TodoWrite and execute systematically
|
||||
**Test:** All research should include confidence scores and citations
|
||||
**Check:** Reports should be saved to claudedocs/ automatically
|
||||
|
||||
**Works Best With:**
|
||||
- **→ Task Management**: Research planning with TodoWrite integration
|
||||
- **→ Orchestration**: Parallel Tavily/Playwright coordination
|
||||
- **Manual Override**: Use `--depth` and `--strategy` for fine control
|
||||
|
||||
---
|
||||
|
||||
### 📋 Task Management Mode - Complex Coordination
|
||||
|
||||
**Purpose**: Hierarchical task organization with session persistence for multi-step operations.
|
||||
|
||||
115
README.md
115
README.md
@ -14,7 +14,7 @@
|
||||
<a href="https://github.com/SuperClaude-Org/SuperQwen_Framework" target="_blank">
|
||||
<img src="https://img.shields.io/badge/Try-SuperQwen_Framework-orange" alt="Try SuperQwen Framework"/>
|
||||
</a>
|
||||
<img src="https://img.shields.io/badge/version-4.1.4-blue" alt="Version">
|
||||
<img src="https://img.shields.io/badge/version-4.2.0-blue" alt="Version">
|
||||
<img src="https://img.shields.io/badge/License-MIT-yellow.svg" alt="License">
|
||||
<img src="https://img.shields.io/badge/PRs-welcome-brightgreen.svg" alt="PRs Welcome">
|
||||
</p>
|
||||
@ -61,7 +61,7 @@
|
||||
|
||||
| **Commands** | **Agents** | **Modes** | **MCP Servers** |
|
||||
|:------------:|:----------:|:---------:|:---------------:|
|
||||
| **24** | **14** | **6** | **6** |
|
||||
| **25** | **15** | **7** | **7** |
|
||||
| Slash Commands | Specialized AI | Behavioral | Integrations |
|
||||
|
||||
Use the new `/sc:help` command to see a full list of all available commands.
|
||||
@ -204,7 +204,8 @@ pip install --break-system-packages SuperClaude
|
||||
<td width="50%">
|
||||
|
||||
### 🤖 **Smarter Agent System**
|
||||
**14 specialized agents** with domain expertise:
|
||||
**15 specialized agents** with domain expertise:
|
||||
- Deep Research agent for autonomous web research
|
||||
- Security engineer catches real vulnerabilities
|
||||
- Frontend architect understands UI patterns
|
||||
- Automatic coordination based on context
|
||||
@ -216,7 +217,7 @@ pip install --break-system-packages SuperClaude
|
||||
### 📝 **Improved Namespace**
|
||||
**`/sc:` prefix** for all commands:
|
||||
- No conflicts with custom commands
|
||||
- 23 commands covering full lifecycle
|
||||
- 25 commands covering full lifecycle
|
||||
- From brainstorming to deployment
|
||||
- Clean, organized command structure
|
||||
|
||||
@ -226,21 +227,23 @@ pip install --break-system-packages SuperClaude
|
||||
<td width="50%">
|
||||
|
||||
### 🔧 **MCP Server Integration**
|
||||
**6 powerful servers** working together:
|
||||
**7 powerful servers** working together:
|
||||
- **Context7** → Up-to-date documentation
|
||||
- **Sequential** → Complex analysis
|
||||
- **Magic** → UI component generation
|
||||
- **Playwright** → Browser testing
|
||||
- **Morphllm** → Bulk transformations
|
||||
- **Serena** → Session persistence
|
||||
- **Tavily** → Web search for deep research
|
||||
|
||||
</td>
|
||||
<td width="50%">
|
||||
|
||||
### 🎯 **Behavioral Modes**
|
||||
**6 adaptive modes** for different contexts:
|
||||
**7 adaptive modes** for different contexts:
|
||||
- **Brainstorming** → Asks right questions
|
||||
- **Business Panel** → Multi-expert strategic analysis
|
||||
- **Deep Research** → Autonomous web research
|
||||
- **Orchestration** → Efficient tool coordination
|
||||
- **Token-Efficiency** → 30-50% context savings
|
||||
- **Task Management** → Systematic organization
|
||||
@ -278,6 +281,98 @@ pip install --break-system-packages SuperClaude
|
||||
|
||||
<div align="center">
|
||||
|
||||
## 🔬 **Deep Research Capabilities**
|
||||
|
||||
### **Autonomous Web Research Aligned with DR Agent Architecture**
|
||||
|
||||
SuperClaude v4.2 introduces comprehensive Deep Research capabilities, enabling autonomous, adaptive, and intelligent web research.
|
||||
|
||||
<table>
|
||||
<tr>
|
||||
<td width="50%">
|
||||
|
||||
### 🎯 **Adaptive Planning**
|
||||
**Three intelligent strategies:**
|
||||
- **Planning-Only**: Direct execution for clear queries
|
||||
- **Intent-Planning**: Clarification for ambiguous requests
|
||||
- **Unified**: Collaborative plan refinement (default)
|
||||
|
||||
</td>
|
||||
<td width="50%">
|
||||
|
||||
### 🔄 **Multi-Hop Reasoning**
|
||||
**Up to 5 iterative searches:**
|
||||
- Entity expansion (Paper → Authors → Works)
|
||||
- Concept deepening (Topic → Details → Examples)
|
||||
- Temporal progression (Current → Historical)
|
||||
- Causal chains (Effect → Cause → Prevention)
|
||||
|
||||
</td>
|
||||
</tr>
|
||||
<tr>
|
||||
<td width="50%">
|
||||
|
||||
### 📊 **Quality Scoring**
|
||||
**Confidence-based validation:**
|
||||
- Source credibility assessment (0.0-1.0)
|
||||
- Coverage completeness tracking
|
||||
- Synthesis coherence evaluation
|
||||
- Minimum threshold: 0.6, Target: 0.8
|
||||
|
||||
</td>
|
||||
<td width="50%">
|
||||
|
||||
### 🧠 **Case-Based Learning**
|
||||
**Cross-session intelligence:**
|
||||
- Pattern recognition and reuse
|
||||
- Strategy optimization over time
|
||||
- Successful query formulations saved
|
||||
- Performance improvement tracking
|
||||
|
||||
</td>
|
||||
</tr>
|
||||
</table>
|
||||
|
||||
### **Research Command Usage**
|
||||
|
||||
```bash
|
||||
# Basic research with automatic depth
|
||||
/sc:research "latest AI developments 2024"
|
||||
|
||||
# Controlled research depth
|
||||
/sc:research "quantum computing breakthroughs" --depth exhaustive
|
||||
|
||||
# Specific strategy selection
|
||||
/sc:research "market analysis" --strategy planning-only
|
||||
|
||||
# Domain-filtered research
|
||||
/sc:research "React patterns" --domains "reactjs.org,github.com"
|
||||
```
|
||||
|
||||
### **Research Depth Levels**
|
||||
|
||||
| Depth | Sources | Hops | Time | Best For |
|
||||
|:-----:|:-------:|:----:|:----:|----------|
|
||||
| **Quick** | 5-10 | 1 | ~2min | Quick facts, simple queries |
|
||||
| **Standard** | 10-20 | 3 | ~5min | General research (default) |
|
||||
| **Deep** | 20-40 | 4 | ~8min | Comprehensive analysis |
|
||||
| **Exhaustive** | 40+ | 5 | ~10min | Academic-level research |
|
||||
|
||||
### **Integrated Tool Orchestration**
|
||||
|
||||
The Deep Research system intelligently coordinates multiple tools:
|
||||
- **Tavily MCP**: Primary web search and discovery
|
||||
- **Playwright MCP**: Complex content extraction
|
||||
- **Sequential MCP**: Multi-step reasoning and synthesis
|
||||
- **Serena MCP**: Memory and learning persistence
|
||||
- **Context7 MCP**: Technical documentation lookup
|
||||
|
||||
</div>
|
||||
|
||||
---
|
||||
|
||||
<div align="center">
|
||||
|
||||
## 📚 **Documentation**
|
||||
|
||||
### **Complete Guide to SuperClaude**
|
||||
@ -302,19 +397,19 @@ pip install --break-system-packages SuperClaude
|
||||
<td valign="top">
|
||||
|
||||
- 🎯 [**Commands Reference**](Docs/User-Guide/commands.md)
|
||||
*All 23 slash commands*
|
||||
*All 25 slash commands*
|
||||
|
||||
- 🤖 [**Agents Guide**](Docs/User-Guide/agents.md)
|
||||
*14 specialized agents*
|
||||
*15 specialized agents*
|
||||
|
||||
- 🎨 [**Behavioral Modes**](Docs/User-Guide/modes.md)
|
||||
*5 adaptive modes*
|
||||
*7 adaptive modes*
|
||||
|
||||
- 🚩 [**Flags Guide**](Docs/User-Guide/flags.md)
|
||||
*Control behaviors*
|
||||
|
||||
- 🔧 [**MCP Servers**](Docs/User-Guide/mcp-servers.md)
|
||||
*6 server integrations*
|
||||
*7 server integrations*
|
||||
|
||||
- 💼 [**Session Management**](Docs/User-Guide/session-management.md)
|
||||
*Save & restore state*
|
||||
|
||||
185
SuperClaude/Agents/deep-research-agent.md
Normal file
185
SuperClaude/Agents/deep-research-agent.md
Normal file
@ -0,0 +1,185 @@
|
||||
---
|
||||
name: deep-research-agent
|
||||
description: Specialist for comprehensive research with adaptive strategies and intelligent exploration
|
||||
category: analysis
|
||||
---
|
||||
|
||||
# Deep Research Agent
|
||||
|
||||
## Triggers
|
||||
- /sc:research command activation
|
||||
- Complex investigation requirements
|
||||
- Complex information synthesis needs
|
||||
- Academic research contexts
|
||||
- Real-time information requests
|
||||
|
||||
## Behavioral Mindset
|
||||
|
||||
Think like a research scientist crossed with an investigative journalist. Apply systematic methodology, follow evidence chains, question sources critically, and synthesize findings coherently. Adapt your approach based on query complexity and information availability.
|
||||
|
||||
## Core Capabilities
|
||||
|
||||
### Adaptive Planning Strategies
|
||||
|
||||
**Planning-Only** (Simple/Clear Queries)
|
||||
- Direct execution without clarification
|
||||
- Single-pass investigation
|
||||
- Straightforward synthesis
|
||||
|
||||
**Intent-Planning** (Ambiguous Queries)
|
||||
- Generate clarifying questions first
|
||||
- Refine scope through interaction
|
||||
- Iterative query development
|
||||
|
||||
**Unified Planning** (Complex/Collaborative)
|
||||
- Present investigation plan
|
||||
- Seek user confirmation
|
||||
- Adjust based on feedback
|
||||
|
||||
### Multi-Hop Reasoning Patterns
|
||||
|
||||
**Entity Expansion**
|
||||
- Person → Affiliations → Related work
|
||||
- Company → Products → Competitors
|
||||
- Concept → Applications → Implications
|
||||
|
||||
**Temporal Progression**
|
||||
- Current state → Recent changes → Historical context
|
||||
- Event → Causes → Consequences → Future implications
|
||||
|
||||
**Conceptual Deepening**
|
||||
- Overview → Details → Examples → Edge cases
|
||||
- Theory → Practice → Results → Limitations
|
||||
|
||||
**Causal Chains**
|
||||
- Observation → Immediate cause → Root cause
|
||||
- Problem → Contributing factors → Solutions
|
||||
|
||||
Maximum hop depth: 5 levels
|
||||
Track hop genealogy for coherence
|
||||
|
||||
### Self-Reflective Mechanisms
|
||||
|
||||
**Progress Assessment**
|
||||
After each major step:
|
||||
- Have I addressed the core question?
|
||||
- What gaps remain?
|
||||
- Is my confidence improving?
|
||||
- Should I adjust strategy?
|
||||
|
||||
**Quality Monitoring**
|
||||
- Source credibility check
|
||||
- Information consistency verification
|
||||
- Bias detection and balance
|
||||
- Completeness evaluation
|
||||
|
||||
**Replanning Triggers**
|
||||
- Confidence below 60%
|
||||
- Contradictory information >30%
|
||||
- Dead ends encountered
|
||||
- Time/resource constraints
|
||||
|
||||
### Evidence Management
|
||||
|
||||
**Result Evaluation**
|
||||
- Assess information relevance
|
||||
- Check for completeness
|
||||
- Identify gaps in knowledge
|
||||
- Note limitations clearly
|
||||
|
||||
**Citation Requirements**
|
||||
- Provide sources when available
|
||||
- Use inline citations for clarity
|
||||
- Note when information is uncertain
|
||||
|
||||
### Tool Orchestration
|
||||
|
||||
**Search Strategy**
|
||||
1. Broad initial searches (Tavily)
|
||||
2. Identify key sources
|
||||
3. Deep extraction as needed
|
||||
4. Follow interesting leads
|
||||
|
||||
**Extraction Routing**
|
||||
- Static HTML → Tavily extraction
|
||||
- JavaScript content → Playwright
|
||||
- Technical docs → Context7
|
||||
- Local context → Native tools
|
||||
|
||||
**Parallel Optimization**
|
||||
- Batch similar searches
|
||||
- Concurrent extractions
|
||||
- Distributed analysis
|
||||
- Never sequential without reason
|
||||
|
||||
### Learning Integration
|
||||
|
||||
**Pattern Recognition**
|
||||
- Track successful query formulations
|
||||
- Note effective extraction methods
|
||||
- Identify reliable source types
|
||||
- Learn domain-specific patterns
|
||||
|
||||
**Memory Usage**
|
||||
- Check for similar past research
|
||||
- Apply successful strategies
|
||||
- Store valuable findings
|
||||
- Build knowledge over time
|
||||
|
||||
## Research Workflow
|
||||
|
||||
### Discovery Phase
|
||||
- Map information landscape
|
||||
- Identify authoritative sources
|
||||
- Detect patterns and themes
|
||||
- Find knowledge boundaries
|
||||
|
||||
### Investigation Phase
|
||||
- Deep dive into specifics
|
||||
- Cross-reference information
|
||||
- Resolve contradictions
|
||||
- Extract insights
|
||||
|
||||
### Synthesis Phase
|
||||
- Build coherent narrative
|
||||
- Create evidence chains
|
||||
- Identify remaining gaps
|
||||
- Generate recommendations
|
||||
|
||||
### Reporting Phase
|
||||
- Structure for audience
|
||||
- Add proper citations
|
||||
- Include confidence levels
|
||||
- Provide clear conclusions
|
||||
|
||||
## Quality Standards
|
||||
|
||||
### Information Quality
|
||||
- Verify key claims when possible
|
||||
- Recency preference for current topics
|
||||
- Assess information reliability
|
||||
- Bias detection and mitigation
|
||||
|
||||
### Synthesis Requirements
|
||||
- Clear fact vs interpretation
|
||||
- Transparent contradiction handling
|
||||
- Explicit confidence statements
|
||||
- Traceable reasoning chains
|
||||
|
||||
### Report Structure
|
||||
- Executive summary
|
||||
- Methodology description
|
||||
- Key findings with evidence
|
||||
- Synthesis and analysis
|
||||
- Conclusions and recommendations
|
||||
- Complete source list
|
||||
|
||||
## Performance Optimization
|
||||
- Cache search results
|
||||
- Reuse successful patterns
|
||||
- Prioritize high-value sources
|
||||
- Balance depth with time
|
||||
|
||||
## Boundaries
|
||||
**Excel at**: Current events, technical research, intelligent search, evidence-based analysis
|
||||
**Limitations**: No paywall bypass, no private data access, no speculation without evidence
|
||||
103
SuperClaude/Commands/research.md
Normal file
103
SuperClaude/Commands/research.md
Normal file
@ -0,0 +1,103 @@
|
||||
---
|
||||
name: research
|
||||
description: Deep web research with adaptive planning and intelligent search
|
||||
category: command
|
||||
complexity: advanced
|
||||
mcp-servers: [tavily, sequential, playwright, serena]
|
||||
personas: [deep-research-agent]
|
||||
---
|
||||
|
||||
# /sc:research - Deep Research Command
|
||||
|
||||
> **Context Framework Note**: This command activates comprehensive research capabilities with adaptive planning, multi-hop reasoning, and evidence-based synthesis.
|
||||
|
||||
## Triggers
|
||||
- Research questions beyond knowledge cutoff
|
||||
- Complex research questions
|
||||
- Current events and real-time information
|
||||
- Academic or technical research requirements
|
||||
- Market analysis and competitive intelligence
|
||||
|
||||
## Context Trigger Pattern
|
||||
```
|
||||
/sc:research "[query]" [--depth quick|standard|deep|exhaustive] [--strategy planning|intent|unified]
|
||||
```
|
||||
|
||||
## Behavioral Flow
|
||||
|
||||
### 1. Understand (5-10% effort)
|
||||
- Assess query complexity and ambiguity
|
||||
- Identify required information types
|
||||
- Determine resource requirements
|
||||
- Define success criteria
|
||||
|
||||
### 2. Plan (10-15% effort)
|
||||
- Select planning strategy based on complexity
|
||||
- Identify parallelization opportunities
|
||||
- Generate research question decomposition
|
||||
- Create investigation milestones
|
||||
|
||||
### 3. TodoWrite (5% effort)
|
||||
- Create adaptive task hierarchy
|
||||
- Scale tasks to query complexity (3-15 tasks)
|
||||
- Establish task dependencies
|
||||
- Set progress tracking
|
||||
|
||||
### 4. Execute (50-60% effort)
|
||||
- **Parallel-first searches**: Always batch similar queries
|
||||
- **Smart extraction**: Route by content complexity
|
||||
- **Multi-hop exploration**: Follow entity and concept chains
|
||||
- **Evidence collection**: Track sources and confidence
|
||||
|
||||
### 5. Track (Continuous)
|
||||
- Monitor TodoWrite progress
|
||||
- Update confidence scores
|
||||
- Log successful patterns
|
||||
- Identify information gaps
|
||||
|
||||
### 6. Validate (10-15% effort)
|
||||
- Verify evidence chains
|
||||
- Check source credibility
|
||||
- Resolve contradictions
|
||||
- Ensure completeness
|
||||
|
||||
## Key Patterns
|
||||
|
||||
### Parallel Execution
|
||||
- Batch all independent searches
|
||||
- Run concurrent extractions
|
||||
- Only sequential for dependencies
|
||||
|
||||
### Evidence Management
|
||||
- Track search results
|
||||
- Provide clear citations when available
|
||||
- Note uncertainties explicitly
|
||||
|
||||
### Adaptive Depth
|
||||
- **Quick**: Basic search, 1 hop, summary output
|
||||
- **Standard**: Extended search, 2-3 hops, structured report
|
||||
- **Deep**: Comprehensive search, 3-4 hops, detailed analysis
|
||||
- **Exhaustive**: Maximum depth, 5 hops, complete investigation
|
||||
|
||||
## MCP Integration
|
||||
- **Tavily**: Primary search and extraction engine
|
||||
- **Sequential**: Complex reasoning and synthesis
|
||||
- **Playwright**: JavaScript-heavy content extraction
|
||||
- **Serena**: Research session persistence
|
||||
|
||||
## Output Standards
|
||||
- Save reports to `claudedocs/research_[topic]_[timestamp].md`
|
||||
- Include executive summary
|
||||
- Provide confidence levels
|
||||
- List all sources with citations
|
||||
|
||||
## Examples
|
||||
```
|
||||
/sc:research "latest developments in quantum computing 2024"
|
||||
/sc:research "competitive analysis of AI coding assistants" --depth deep
|
||||
/sc:research "best practices for distributed systems" --strategy unified
|
||||
```
|
||||
|
||||
## Boundaries
|
||||
**Will**: Current information, intelligent search, evidence-based analysis
|
||||
**Won't**: Make claims without sources, skip validation, access restricted content
|
||||
446
SuperClaude/Core/RESEARCH_CONFIG.md
Normal file
446
SuperClaude/Core/RESEARCH_CONFIG.md
Normal file
@ -0,0 +1,446 @@
|
||||
# Deep Research Configuration
|
||||
|
||||
## Default Settings
|
||||
|
||||
```yaml
|
||||
research_defaults:
|
||||
planning_strategy: unified
|
||||
max_hops: 5
|
||||
confidence_threshold: 0.7
|
||||
memory_enabled: true
|
||||
parallelization: true
|
||||
parallel_first: true # MANDATORY DEFAULT
|
||||
sequential_override_requires_justification: true # NEW
|
||||
|
||||
parallel_execution_rules:
|
||||
DEFAULT_MODE: PARALLEL # EMPHASIZED
|
||||
|
||||
mandatory_parallel:
|
||||
- "Multiple search queries"
|
||||
- "Batch URL extractions"
|
||||
- "Independent analyses"
|
||||
- "Non-dependent hops"
|
||||
- "Result processing"
|
||||
- "Information extraction"
|
||||
|
||||
sequential_only_with_justification:
|
||||
- reason: "Explicit dependency"
|
||||
example: "Hop N requires Hop N-1 results"
|
||||
- reason: "Resource constraint"
|
||||
example: "API rate limit reached"
|
||||
- reason: "User requirement"
|
||||
example: "User requests sequential for debugging"
|
||||
|
||||
parallel_optimization:
|
||||
batch_sizes:
|
||||
searches: 5
|
||||
extractions: 3
|
||||
analyses: 2
|
||||
intelligent_grouping:
|
||||
by_domain: true
|
||||
by_complexity: true
|
||||
by_resource: true
|
||||
|
||||
planning_strategies:
|
||||
planning_only:
|
||||
clarification: false
|
||||
user_confirmation: false
|
||||
execution: immediate
|
||||
|
||||
intent_planning:
|
||||
clarification: true
|
||||
max_questions: 3
|
||||
execution: after_clarification
|
||||
|
||||
unified:
|
||||
clarification: optional
|
||||
plan_presentation: true
|
||||
user_feedback: true
|
||||
execution: after_confirmation
|
||||
|
||||
hop_configuration:
|
||||
max_depth: 5
|
||||
timeout_per_hop: 60s
|
||||
parallel_hops: true
|
||||
loop_detection: true
|
||||
genealogy_tracking: true
|
||||
|
||||
confidence_scoring:
|
||||
relevance_weight: 0.5
|
||||
completeness_weight: 0.5
|
||||
minimum_threshold: 0.6
|
||||
target_threshold: 0.8
|
||||
|
||||
self_reflection:
|
||||
frequency: after_each_hop
|
||||
triggers:
|
||||
- confidence_below_threshold
|
||||
- contradictions_detected
|
||||
- time_elapsed_percentage: 80
|
||||
- user_intervention
|
||||
actions:
|
||||
- assess_quality
|
||||
- identify_gaps
|
||||
- consider_replanning
|
||||
- adjust_strategy
|
||||
|
||||
memory_management:
|
||||
case_based_reasoning: true
|
||||
pattern_learning: true
|
||||
session_persistence: true
|
||||
cross_session_learning: true
|
||||
retention_days: 30
|
||||
|
||||
tool_coordination:
|
||||
discovery_primary: tavily
|
||||
extraction_smart_routing: true
|
||||
reasoning_engine: sequential
|
||||
memory_backend: serena
|
||||
parallel_tool_calls: true
|
||||
|
||||
quality_gates:
|
||||
planning_gate:
|
||||
required_elements: [objectives, strategy, success_criteria]
|
||||
execution_gate:
|
||||
min_confidence: 0.6
|
||||
synthesis_gate:
|
||||
coherence_required: true
|
||||
clarity_required: true
|
||||
|
||||
extraction_settings:
|
||||
scraping_strategy: selective
|
||||
screenshot_capture: contextual
|
||||
authentication_handling: ethical
|
||||
javascript_rendering: auto_detect
|
||||
timeout_per_page: 15s
|
||||
```
|
||||
|
||||
## Performance Optimizations
|
||||
|
||||
```yaml
|
||||
optimization_strategies:
|
||||
caching:
|
||||
- Cache Tavily search results: 1 hour
|
||||
- Cache Playwright extractions: 24 hours
|
||||
- Cache Sequential analysis: 1 hour
|
||||
- Reuse case patterns: always
|
||||
|
||||
parallelization:
|
||||
- Parallel searches: max 5
|
||||
- Parallel extractions: max 3
|
||||
- Parallel analysis: max 2
|
||||
- Tool call batching: true
|
||||
|
||||
resource_limits:
|
||||
- Max time per research: 10 minutes
|
||||
- Max search iterations: 10
|
||||
- Max hops: 5
|
||||
- Max memory per session: 100MB
|
||||
```
|
||||
|
||||
## Strategy Selection Rules
|
||||
|
||||
```yaml
|
||||
strategy_selection:
|
||||
planning_only:
|
||||
indicators:
|
||||
- Clear, specific query
|
||||
- Technical documentation request
|
||||
- Well-defined scope
|
||||
- No ambiguity detected
|
||||
|
||||
intent_planning:
|
||||
indicators:
|
||||
- Ambiguous terms present
|
||||
- Broad topic area
|
||||
- Multiple possible interpretations
|
||||
- User expertise unknown
|
||||
|
||||
unified:
|
||||
indicators:
|
||||
- Complex multi-faceted query
|
||||
- User collaboration beneficial
|
||||
- Iterative refinement expected
|
||||
- High-stakes research
|
||||
```
|
||||
|
||||
## Source Credibility Matrix
|
||||
|
||||
```yaml
|
||||
source_credibility:
|
||||
tier_1_sources:
|
||||
score: 0.9-1.0
|
||||
types:
|
||||
- Academic journals
|
||||
- Government publications
|
||||
- Official documentation
|
||||
- Peer-reviewed papers
|
||||
|
||||
tier_2_sources:
|
||||
score: 0.7-0.9
|
||||
types:
|
||||
- Established media
|
||||
- Industry reports
|
||||
- Expert blogs
|
||||
- Technical forums
|
||||
|
||||
tier_3_sources:
|
||||
score: 0.5-0.7
|
||||
types:
|
||||
- Community resources
|
||||
- User documentation
|
||||
- Social media (verified)
|
||||
- Wikipedia
|
||||
|
||||
tier_4_sources:
|
||||
score: 0.3-0.5
|
||||
types:
|
||||
- User forums
|
||||
- Social media (unverified)
|
||||
- Personal blogs
|
||||
- Comments sections
|
||||
```
|
||||
|
||||
## Depth Configurations
|
||||
|
||||
```yaml
|
||||
research_depth_profiles:
|
||||
quick:
|
||||
max_sources: 10
|
||||
max_hops: 1
|
||||
iterations: 1
|
||||
time_limit: 2 minutes
|
||||
confidence_target: 0.6
|
||||
extraction: tavily_only
|
||||
|
||||
standard:
|
||||
max_sources: 20
|
||||
max_hops: 3
|
||||
iterations: 2
|
||||
time_limit: 5 minutes
|
||||
confidence_target: 0.7
|
||||
extraction: selective
|
||||
|
||||
deep:
|
||||
max_sources: 40
|
||||
max_hops: 4
|
||||
iterations: 3
|
||||
time_limit: 8 minutes
|
||||
confidence_target: 0.8
|
||||
extraction: comprehensive
|
||||
|
||||
exhaustive:
|
||||
max_sources: 50+
|
||||
max_hops: 5
|
||||
iterations: 5
|
||||
time_limit: 10 minutes
|
||||
confidence_target: 0.9
|
||||
extraction: all_sources
|
||||
```
|
||||
|
||||
## Multi-Hop Patterns
|
||||
|
||||
```yaml
|
||||
hop_patterns:
|
||||
entity_expansion:
|
||||
description: "Explore entities found in previous hop"
|
||||
example: "Paper → Authors → Other works → Collaborators"
|
||||
max_branches: 3
|
||||
|
||||
concept_deepening:
|
||||
description: "Drill down into concepts"
|
||||
example: "Topic → Subtopics → Details → Examples"
|
||||
max_depth: 4
|
||||
|
||||
temporal_progression:
|
||||
description: "Follow chronological development"
|
||||
example: "Current → Recent → Historical → Origins"
|
||||
direction: backward
|
||||
|
||||
causal_chain:
|
||||
description: "Trace cause and effect"
|
||||
example: "Effect → Immediate cause → Root cause → Prevention"
|
||||
validation: required
|
||||
```
|
||||
|
||||
## Extraction Routing Rules
|
||||
|
||||
```yaml
|
||||
extraction_routing:
|
||||
use_tavily:
|
||||
conditions:
|
||||
- Static HTML content
|
||||
- Simple article structure
|
||||
- No JavaScript requirement
|
||||
- Public access
|
||||
|
||||
use_playwright:
|
||||
conditions:
|
||||
- JavaScript rendering required
|
||||
- Dynamic content present
|
||||
- Authentication needed
|
||||
- Interactive elements
|
||||
- Screenshots required
|
||||
|
||||
use_context7:
|
||||
conditions:
|
||||
- Technical documentation
|
||||
- API references
|
||||
- Framework guides
|
||||
- Library documentation
|
||||
|
||||
use_native:
|
||||
conditions:
|
||||
- Local file access
|
||||
- Simple explanations
|
||||
- Code generation
|
||||
- General knowledge
|
||||
```
|
||||
|
||||
## Case-Based Learning Schema
|
||||
|
||||
```yaml
|
||||
case_schema:
|
||||
case_id:
|
||||
format: "research_[timestamp]_[topic_hash]"
|
||||
|
||||
case_content:
|
||||
query: "original research question"
|
||||
strategy_used: "planning approach"
|
||||
successful_patterns:
|
||||
- query_formulations: []
|
||||
- extraction_methods: []
|
||||
- synthesis_approaches: []
|
||||
findings:
|
||||
key_discoveries: []
|
||||
source_credibility_scores: {}
|
||||
confidence_levels: {}
|
||||
lessons_learned:
|
||||
what_worked: []
|
||||
what_failed: []
|
||||
optimizations: []
|
||||
metrics:
|
||||
time_taken: seconds
|
||||
sources_processed: count
|
||||
hops_executed: count
|
||||
confidence_achieved: float
|
||||
```
|
||||
|
||||
## Replanning Thresholds
|
||||
|
||||
```yaml
|
||||
replanning_triggers:
|
||||
confidence_based:
|
||||
critical: < 0.4
|
||||
low: < 0.6
|
||||
acceptable: 0.6-0.7
|
||||
good: > 0.7
|
||||
|
||||
time_based:
|
||||
warning: 70% of limit
|
||||
critical: 90% of limit
|
||||
|
||||
quality_based:
|
||||
insufficient_sources: < 3
|
||||
contradictions: > 30%
|
||||
gaps_identified: > 50%
|
||||
|
||||
user_based:
|
||||
explicit_request: immediate
|
||||
implicit_dissatisfaction: assess
|
||||
```
|
||||
|
||||
## Output Format Templates
|
||||
|
||||
```yaml
|
||||
output_formats:
|
||||
summary:
|
||||
max_length: 500 words
|
||||
sections: [key_finding, evidence, sources]
|
||||
confidence_display: simple
|
||||
|
||||
report:
|
||||
sections: [executive_summary, methodology, findings, synthesis, conclusions]
|
||||
citations: inline
|
||||
confidence_display: detailed
|
||||
visuals: included
|
||||
|
||||
academic:
|
||||
sections: [abstract, introduction, methodology, literature_review, findings, discussion, conclusions]
|
||||
citations: academic_format
|
||||
confidence_display: statistical
|
||||
appendices: true
|
||||
```
|
||||
|
||||
## Error Handling
|
||||
|
||||
```yaml
|
||||
error_handling:
|
||||
tavily_errors:
|
||||
api_key_missing: "Check TAVILY_API_KEY environment variable"
|
||||
rate_limit: "Wait and retry with exponential backoff"
|
||||
no_results: "Expand search terms or try alternatives"
|
||||
|
||||
playwright_errors:
|
||||
timeout: "Skip source or increase timeout"
|
||||
navigation_failed: "Mark as inaccessible, continue"
|
||||
screenshot_failed: "Continue without visual"
|
||||
|
||||
quality_errors:
|
||||
low_confidence: "Trigger replanning"
|
||||
contradictions: "Seek additional sources"
|
||||
insufficient_data: "Expand search scope"
|
||||
```
|
||||
|
||||
## Integration Points
|
||||
|
||||
```yaml
|
||||
mcp_integration:
|
||||
tavily:
|
||||
role: primary_search
|
||||
fallback: native_websearch
|
||||
|
||||
playwright:
|
||||
role: complex_extraction
|
||||
fallback: tavily_extraction
|
||||
|
||||
sequential:
|
||||
role: reasoning_engine
|
||||
fallback: native_reasoning
|
||||
|
||||
context7:
|
||||
role: technical_docs
|
||||
fallback: tavily_search
|
||||
|
||||
serena:
|
||||
role: memory_management
|
||||
fallback: session_only
|
||||
```
|
||||
|
||||
## Monitoring Metrics
|
||||
|
||||
```yaml
|
||||
metrics_tracking:
|
||||
performance:
|
||||
- search_latency
|
||||
- extraction_time
|
||||
- synthesis_duration
|
||||
- total_research_time
|
||||
|
||||
quality:
|
||||
- confidence_scores
|
||||
- source_diversity
|
||||
- coverage_completeness
|
||||
- contradiction_rate
|
||||
|
||||
efficiency:
|
||||
- cache_hit_rate
|
||||
- parallel_execution_rate
|
||||
- memory_usage
|
||||
- api_cost
|
||||
|
||||
learning:
|
||||
- pattern_reuse_rate
|
||||
- strategy_success_rate
|
||||
- improvement_trajectory
|
||||
```
|
||||
495
SuperClaude/Examples/deep_research_workflows.md
Normal file
495
SuperClaude/Examples/deep_research_workflows.md
Normal file
@ -0,0 +1,495 @@
|
||||
# Deep Research Workflows
|
||||
|
||||
## Example 1: Planning-Only Strategy
|
||||
|
||||
### Scenario
|
||||
Clear research question: "Latest TensorFlow 3.0 features"
|
||||
|
||||
### Execution
|
||||
```bash
|
||||
/sc:research "Latest TensorFlow 3.0 features" --strategy planning-only --depth standard
|
||||
```
|
||||
|
||||
### Workflow
|
||||
```yaml
|
||||
1. Planning (Immediate):
|
||||
- Decompose: Official docs, changelog, tutorials
|
||||
- No user clarification needed
|
||||
|
||||
2. Execution:
|
||||
- Hop 1: Official TensorFlow documentation
|
||||
- Hop 2: Recent tutorials and examples
|
||||
- Confidence: 0.85 achieved
|
||||
|
||||
3. Synthesis:
|
||||
- Features list with examples
|
||||
- Migration guide references
|
||||
- Performance comparisons
|
||||
```
|
||||
|
||||
## Example 2: Intent-to-Planning Strategy
|
||||
|
||||
### Scenario
|
||||
Ambiguous request: "AI safety"
|
||||
|
||||
### Execution
|
||||
```bash
|
||||
/sc:research "AI safety" --strategy intent-planning --depth deep
|
||||
```
|
||||
|
||||
### Workflow
|
||||
```yaml
|
||||
1. Intent Clarification:
|
||||
Questions:
|
||||
- "Are you interested in technical AI alignment, policy/governance, or current events?"
|
||||
- "What's your background level (researcher, developer, general interest)?"
|
||||
- "Any specific AI systems or risks of concern?"
|
||||
|
||||
2. User Response:
|
||||
- "Technical alignment for LLMs, researcher level"
|
||||
|
||||
3. Refined Planning:
|
||||
- Focus on alignment techniques
|
||||
- Academic sources priority
|
||||
- Include recent papers
|
||||
|
||||
4. Multi-Hop Execution:
|
||||
- Hop 1: Recent alignment papers
|
||||
- Hop 2: Key researchers and labs
|
||||
- Hop 3: Emerging techniques
|
||||
- Hop 4: Open problems
|
||||
|
||||
5. Self-Reflection:
|
||||
- Coverage: Complete ✓
|
||||
- Depth: Adequate ✓
|
||||
- Confidence: 0.82 ✓
|
||||
```
|
||||
|
||||
## Example 3: Unified Intent-Planning with Replanning
|
||||
|
||||
### Scenario
|
||||
Complex research: "Build AI startup competitive analysis"
|
||||
|
||||
### Execution
|
||||
```bash
|
||||
/sc:research "Build AI startup competitive analysis" --strategy unified --hops 5
|
||||
```
|
||||
|
||||
### Workflow
|
||||
```yaml
|
||||
1. Initial Plan Presentation:
|
||||
Proposed Research Areas:
|
||||
- Current AI startup landscape
|
||||
- Funding and valuations
|
||||
- Technology differentiators
|
||||
- Market positioning
|
||||
- Growth strategies
|
||||
|
||||
"Does this cover your needs? Any specific competitors or aspects to focus on?"
|
||||
|
||||
2. User Adjustment:
|
||||
"Focus on code generation tools, include pricing and technical capabilities"
|
||||
|
||||
3. Revised Multi-Hop Research:
|
||||
- Hop 1: List of code generation startups
|
||||
- Hop 2: Technical capabilities comparison
|
||||
- Hop 3: Pricing and business models
|
||||
- Hop 4: Customer reviews and adoption
|
||||
- Hop 5: Investment and growth metrics
|
||||
|
||||
4. Mid-Research Replanning:
|
||||
- Low confidence on technical details (0.55)
|
||||
- Switch to Playwright for interactive demos
|
||||
- Add GitHub repository analysis
|
||||
|
||||
5. Quality Gate Check:
|
||||
- Technical coverage: Improved to 0.78 ✓
|
||||
- Pricing data: Complete 0.90 ✓
|
||||
- Competitive matrix: Generated ✓
|
||||
```
|
||||
|
||||
## Example 4: Case-Based Research with Learning
|
||||
|
||||
### Scenario
|
||||
Similar to previous research: "Rust async runtime comparison"
|
||||
|
||||
### Execution
|
||||
```bash
|
||||
/sc:research "Rust async runtime comparison" --memory enabled
|
||||
```
|
||||
|
||||
### Workflow
|
||||
```yaml
|
||||
1. Case Retrieval:
|
||||
Found Similar Case:
|
||||
- "Go concurrency patterns" research
|
||||
- Successful pattern: Technical benchmarks + code examples + community feedback
|
||||
|
||||
2. Adapted Strategy:
|
||||
- Use similar structure for Rust
|
||||
- Focus on: Tokio, async-std, smol
|
||||
- Include benchmarks and examples
|
||||
|
||||
3. Execution with Known Patterns:
|
||||
- Skip broad searches
|
||||
- Direct to technical sources
|
||||
- Use proven extraction methods
|
||||
|
||||
4. New Learning Captured:
|
||||
- Rust community prefers different metrics than Go
|
||||
- Crates.io provides useful statistics
|
||||
- Discord communities have valuable discussions
|
||||
|
||||
5. Memory Update:
|
||||
- Store successful Rust research patterns
|
||||
- Note language-specific source preferences
|
||||
- Save for future Rust queries
|
||||
```
|
||||
|
||||
## Example 5: Self-Reflective Refinement Loop
|
||||
|
||||
### Scenario
|
||||
Evolving research: "Quantum computing for optimization"
|
||||
|
||||
### Execution
|
||||
```bash
|
||||
/sc:research "Quantum computing for optimization" --confidence 0.8 --depth exhaustive
|
||||
```
|
||||
|
||||
### Workflow
|
||||
```yaml
|
||||
1. Initial Research Phase:
|
||||
- Academic papers collected
|
||||
- Basic concepts understood
|
||||
- Confidence: 0.65 (below threshold)
|
||||
|
||||
2. Self-Reflection Analysis:
|
||||
Gaps Identified:
|
||||
- Practical implementations missing
|
||||
- No industry use cases
|
||||
- Mathematical details unclear
|
||||
|
||||
3. Replanning Decision:
|
||||
- Add industry reports
|
||||
- Include video tutorials for math
|
||||
- Search for code implementations
|
||||
|
||||
4. Enhanced Research:
|
||||
- Hop 1→2: Papers → Authors → Implementations
|
||||
- Hop 3→4: Companies → Case studies
|
||||
- Hop 5: Tutorial videos for complex math
|
||||
|
||||
5. Quality Achievement:
|
||||
- Confidence raised to 0.82 ✓
|
||||
- Comprehensive coverage achieved
|
||||
- Multiple perspectives included
|
||||
```
|
||||
|
||||
## Example 6: Technical Documentation Research with Playwright
|
||||
|
||||
### Scenario
|
||||
Research the latest Next.js 14 App Router features
|
||||
|
||||
### Execution
|
||||
```bash
|
||||
/sc:research "Next.js 14 App Router complete guide" --depth deep --scrape selective --screenshots
|
||||
```
|
||||
|
||||
### Workflow
|
||||
```yaml
|
||||
1. Tavily Search:
|
||||
- Find official docs, tutorials, blog posts
|
||||
- Identify JavaScript-heavy documentation sites
|
||||
|
||||
2. URL Analysis:
|
||||
- Next.js docs → JavaScript rendering required
|
||||
- Blog posts → Static content, Tavily sufficient
|
||||
- Video tutorials → Need transcript extraction
|
||||
|
||||
3. Playwright Navigation:
|
||||
- Navigate to official documentation
|
||||
- Handle interactive code examples
|
||||
- Capture screenshots of UI components
|
||||
|
||||
4. Dynamic Extraction:
|
||||
- Extract code samples
|
||||
- Capture interactive demos
|
||||
- Document routing patterns
|
||||
|
||||
5. Synthesis:
|
||||
- Combine official docs with community tutorials
|
||||
- Create comprehensive guide with visuals
|
||||
- Include code examples and best practices
|
||||
```
|
||||
|
||||
## Example 7: Competitive Intelligence with Visual Documentation
|
||||
|
||||
### Scenario
|
||||
Analyze competitor pricing and features
|
||||
|
||||
### Execution
|
||||
```bash
|
||||
/sc:research "AI writing assistant tools pricing features 2024" --scrape all --screenshots --interactive
|
||||
```
|
||||
|
||||
### Workflow
|
||||
```yaml
|
||||
1. Market Discovery:
|
||||
- Tavily finds: Jasper, Copy.ai, Writesonic, etc.
|
||||
- Identify pricing pages and feature lists
|
||||
|
||||
2. Complexity Assessment:
|
||||
- Dynamic pricing calculators detected
|
||||
- Interactive feature comparisons found
|
||||
- Login-gated content identified
|
||||
|
||||
3. Playwright Extraction:
|
||||
- Navigate to each pricing page
|
||||
- Interact with pricing sliders
|
||||
- Capture screenshots of pricing tiers
|
||||
|
||||
4. Feature Analysis:
|
||||
- Extract feature matrices
|
||||
- Compare capabilities
|
||||
- Document limitations
|
||||
|
||||
5. Report Generation:
|
||||
- Competitive positioning matrix
|
||||
- Visual pricing comparison
|
||||
- Feature gap analysis
|
||||
- Strategic recommendations
|
||||
```
|
||||
|
||||
## Example 8: Academic Research with Authentication
|
||||
|
||||
### Scenario
|
||||
Research latest machine learning papers
|
||||
|
||||
### Execution
|
||||
```bash
|
||||
/sc:research "transformer architecture improvements 2024" --depth exhaustive --auth --scrape auto
|
||||
```
|
||||
|
||||
### Workflow
|
||||
```yaml
|
||||
1. Academic Search:
|
||||
- Tavily finds papers on arXiv, IEEE, ACM
|
||||
- Identify open vs. gated content
|
||||
|
||||
2. Access Strategy:
|
||||
- arXiv: Direct access, no auth needed
|
||||
- IEEE: Institutional access required
|
||||
- ACM: Mixed access levels
|
||||
|
||||
3. Extraction Approach:
|
||||
- Public papers: Tavily extraction
|
||||
- Gated content: Playwright with auth
|
||||
- PDFs: Download and process
|
||||
|
||||
4. Citation Network:
|
||||
- Follow reference chains
|
||||
- Identify key contributors
|
||||
- Map research lineage
|
||||
|
||||
5. Literature Synthesis:
|
||||
- Chronological development
|
||||
- Key innovations identified
|
||||
- Future directions mapped
|
||||
- Comprehensive bibliography
|
||||
```
|
||||
|
||||
## Example 9: Real-time Market Data Research
|
||||
|
||||
### Scenario
|
||||
Gather current cryptocurrency market analysis
|
||||
|
||||
### Execution
|
||||
```bash
|
||||
/sc:research "cryptocurrency market analysis BTC ETH 2024" --scrape all --interactive --screenshots
|
||||
```
|
||||
|
||||
### Workflow
|
||||
```yaml
|
||||
1. Market Discovery:
|
||||
- Find: CoinMarketCap, CoinGecko, TradingView
|
||||
- Identify real-time data sources
|
||||
|
||||
2. Dynamic Content Handling:
|
||||
- Playwright loads live charts
|
||||
- Capture price movements
|
||||
- Extract volume data
|
||||
|
||||
3. Interactive Analysis:
|
||||
- Interact with chart timeframes
|
||||
- Toggle technical indicators
|
||||
- Capture different views
|
||||
|
||||
4. Data Synthesis:
|
||||
- Current market conditions
|
||||
- Technical analysis
|
||||
- Sentiment indicators
|
||||
- Visual documentation
|
||||
|
||||
5. Report Output:
|
||||
- Market snapshot with charts
|
||||
- Technical analysis summary
|
||||
- Trading volume trends
|
||||
- Risk assessment
|
||||
```
|
||||
|
||||
## Example 10: Multi-Domain Research with Parallel Execution
|
||||
|
||||
### Scenario
|
||||
Comprehensive analysis of "AI in healthcare 2024"
|
||||
|
||||
### Execution
|
||||
```bash
|
||||
/sc:research "AI in healthcare applications 2024" --depth exhaustive --hops 5 --parallel
|
||||
```
|
||||
|
||||
### Workflow
|
||||
```yaml
|
||||
1. Domain Decomposition:
|
||||
Parallel Searches:
|
||||
- Medical AI applications
|
||||
- Regulatory landscape
|
||||
- Market analysis
|
||||
- Technical implementations
|
||||
- Ethical considerations
|
||||
|
||||
2. Multi-Hop Exploration:
|
||||
Each Domain:
|
||||
- Hop 1: Broad landscape
|
||||
- Hop 2: Key players
|
||||
- Hop 3: Case studies
|
||||
- Hop 4: Challenges
|
||||
- Hop 5: Future trends
|
||||
|
||||
3. Cross-Domain Synthesis:
|
||||
- Medical ↔ Technical connections
|
||||
- Regulatory ↔ Market impacts
|
||||
- Ethical ↔ Implementation constraints
|
||||
|
||||
4. Quality Assessment:
|
||||
- Coverage: All domains addressed
|
||||
- Depth: Sufficient detail per domain
|
||||
- Integration: Cross-domain insights
|
||||
- Confidence: 0.87 achieved
|
||||
|
||||
5. Comprehensive Report:
|
||||
- Executive summary
|
||||
- Domain-specific sections
|
||||
- Integrated analysis
|
||||
- Strategic recommendations
|
||||
- Visual evidence
|
||||
```
|
||||
|
||||
## Advanced Workflow Patterns
|
||||
|
||||
### Pattern 1: Iterative Deepening
|
||||
```yaml
|
||||
Round_1:
|
||||
- Broad search for landscape
|
||||
- Identify key areas
|
||||
|
||||
Round_2:
|
||||
- Deep dive into key areas
|
||||
- Extract detailed information
|
||||
|
||||
Round_3:
|
||||
- Fill specific gaps
|
||||
- Resolve contradictions
|
||||
|
||||
Round_4:
|
||||
- Final validation
|
||||
- Quality assurance
|
||||
```
|
||||
|
||||
### Pattern 2: Source Triangulation
|
||||
```yaml
|
||||
Primary_Sources:
|
||||
- Official documentation
|
||||
- Academic papers
|
||||
|
||||
Secondary_Sources:
|
||||
- Industry reports
|
||||
- Expert analysis
|
||||
|
||||
Tertiary_Sources:
|
||||
- Community discussions
|
||||
- User experiences
|
||||
|
||||
Synthesis:
|
||||
- Cross-validate findings
|
||||
- Identify consensus
|
||||
- Note disagreements
|
||||
```
|
||||
|
||||
### Pattern 3: Temporal Analysis
|
||||
```yaml
|
||||
Historical_Context:
|
||||
- Past developments
|
||||
- Evolution timeline
|
||||
|
||||
Current_State:
|
||||
- Present situation
|
||||
- Recent changes
|
||||
|
||||
Future_Projections:
|
||||
- Trends analysis
|
||||
- Expert predictions
|
||||
|
||||
Synthesis:
|
||||
- Development trajectory
|
||||
- Inflection points
|
||||
- Future scenarios
|
||||
```
|
||||
|
||||
## Performance Optimization Tips
|
||||
|
||||
### Query Optimization
|
||||
1. Start with specific terms
|
||||
2. Use domain filters early
|
||||
3. Batch similar searches
|
||||
4. Cache intermediate results
|
||||
5. Reuse successful patterns
|
||||
|
||||
### Extraction Efficiency
|
||||
1. Assess complexity first
|
||||
2. Use appropriate tool per source
|
||||
3. Parallelize when possible
|
||||
4. Set reasonable timeouts
|
||||
5. Handle errors gracefully
|
||||
|
||||
### Synthesis Strategy
|
||||
1. Organize findings early
|
||||
2. Identify patterns quickly
|
||||
3. Resolve conflicts systematically
|
||||
4. Build narrative progressively
|
||||
5. Maintain evidence chains
|
||||
|
||||
## Quality Validation Checklist
|
||||
|
||||
### Planning Phase
|
||||
- [ ] Clear objectives defined
|
||||
- [ ] Appropriate strategy selected
|
||||
- [ ] Resources estimated correctly
|
||||
- [ ] Success criteria established
|
||||
|
||||
### Execution Phase
|
||||
- [ ] All planned searches completed
|
||||
- [ ] Extraction methods appropriate
|
||||
- [ ] Multi-hop chains logical
|
||||
- [ ] Confidence scores calculated
|
||||
|
||||
### Synthesis Phase
|
||||
- [ ] All findings integrated
|
||||
- [ ] Contradictions resolved
|
||||
- [ ] Evidence chains complete
|
||||
- [ ] Narrative coherent
|
||||
|
||||
### Delivery Phase
|
||||
- [ ] Format appropriate for audience
|
||||
- [ ] Citations complete and accurate
|
||||
- [ ] Visual evidence included
|
||||
- [ ] Confidence levels transparent
|
||||
285
SuperClaude/MCP/MCP_Tavily.md
Normal file
285
SuperClaude/MCP/MCP_Tavily.md
Normal file
@ -0,0 +1,285 @@
|
||||
# Tavily MCP Server
|
||||
|
||||
**Purpose**: Web search and real-time information retrieval for research and current events
|
||||
|
||||
## Triggers
|
||||
- Web search requirements beyond Claude's knowledge cutoff
|
||||
- Current events, news, and real-time information needs
|
||||
- Market research and competitive analysis tasks
|
||||
- Technical documentation not in training data
|
||||
- Academic research requiring recent publications
|
||||
- Fact-checking and verification needs
|
||||
- Deep research investigations requiring multi-source analysis
|
||||
- `/sc:research` command activation
|
||||
|
||||
## Choose When
|
||||
- **Over WebSearch**: When you need structured search with advanced filtering
|
||||
- **Over WebFetch**: When you need multi-source search, not single page extraction
|
||||
- **For research**: Comprehensive investigations requiring multiple sources
|
||||
- **For current info**: Events, updates, or changes after knowledge cutoff
|
||||
- **Not for**: Simple questions answerable from training, code generation, local file operations
|
||||
|
||||
## Works Best With
|
||||
- **Sequential**: Tavily provides raw information → Sequential analyzes and synthesizes
|
||||
- **Playwright**: Tavily discovers URLs → Playwright extracts complex content
|
||||
- **Context7**: Tavily searches for updates → Context7 provides stable documentation
|
||||
- **Serena**: Tavily performs searches → Serena stores research sessions
|
||||
|
||||
## Configuration
|
||||
Requires TAVILY_API_KEY environment variable from https://app.tavily.com
|
||||
|
||||
## Search Capabilities
|
||||
- **Web Search**: General web searches with ranking algorithms
|
||||
- **News Search**: Time-filtered news and current events
|
||||
- **Academic Search**: Scholarly articles and research papers
|
||||
- **Domain Filtering**: Include/exclude specific domains
|
||||
- **Content Extraction**: Full-text extraction from search results
|
||||
- **Freshness Control**: Prioritize recent content
|
||||
- **Multi-Round Searching**: Iterative refinement based on gaps
|
||||
|
||||
## Examples
|
||||
```
|
||||
"latest TypeScript features 2024" → Tavily (current technical information)
|
||||
"OpenAI GPT updates this week" → Tavily (recent news and updates)
|
||||
"quantum computing breakthroughs 2024" → Tavily (recent research)
|
||||
"best practices React Server Components" → Tavily (current best practices)
|
||||
"explain recursion" → Native Claude (general concept explanation)
|
||||
"write a Python function" → Native Claude (code generation)
|
||||
```
|
||||
|
||||
## Search Patterns
|
||||
|
||||
### Basic Search
|
||||
```
|
||||
Query: "search term"
|
||||
→ Returns: Ranked results with snippets
|
||||
```
|
||||
|
||||
### Domain-Specific Search
|
||||
```
|
||||
Query: "search term"
|
||||
Domains: ["arxiv.org", "github.com"]
|
||||
→ Returns: Results from specified domains only
|
||||
```
|
||||
|
||||
### Time-Filtered Search
|
||||
```
|
||||
Query: "search term"
|
||||
Recency: "week" | "month" | "year"
|
||||
→ Returns: Recent results within timeframe
|
||||
```
|
||||
|
||||
### Deep Content Search
|
||||
```
|
||||
Query: "search term"
|
||||
Extract: true
|
||||
→ Returns: Full content extraction from top results
|
||||
```
|
||||
|
||||
## Quality Optimization
|
||||
- **Query Refinement**: Iterate searches based on initial results
|
||||
- **Source Diversity**: Ensure multiple perspectives in results
|
||||
- **Credibility Filtering**: Prioritize authoritative sources
|
||||
- **Deduplication**: Remove redundant information across sources
|
||||
- **Relevance Scoring**: Focus on most pertinent results
|
||||
|
||||
## Integration Flows
|
||||
|
||||
### Research Flow
|
||||
```
|
||||
1. Tavily: Initial broad search
|
||||
2. Sequential: Analyze and identify gaps
|
||||
3. Tavily: Targeted follow-up searches
|
||||
4. Sequential: Synthesize findings
|
||||
5. Serena: Store research session
|
||||
```
|
||||
|
||||
### Fact-Checking Flow
|
||||
```
|
||||
1. Tavily: Search for claim verification
|
||||
2. Tavily: Find contradicting sources
|
||||
3. Sequential: Analyze evidence
|
||||
4. Report: Present balanced findings
|
||||
```
|
||||
|
||||
### Competitive Analysis Flow
|
||||
```
|
||||
1. Tavily: Search competitor information
|
||||
2. Tavily: Search market trends
|
||||
3. Sequential: Comparative analysis
|
||||
4. Context7: Technical comparisons
|
||||
5. Report: Strategic insights
|
||||
```
|
||||
|
||||
### Deep Research Flow (DR Agent)
|
||||
```
|
||||
1. Planning: Decompose research question
|
||||
2. Tavily: Execute planned searches
|
||||
3. Analysis: Assess URL complexity
|
||||
4. Routing: Simple → Tavily extract | Complex → Playwright
|
||||
5. Synthesis: Combine all sources
|
||||
6. Iteration: Refine based on gaps
|
||||
```
|
||||
|
||||
## Advanced Search Strategies
|
||||
|
||||
### Multi-Hop Research
|
||||
```yaml
|
||||
Initial_Search:
|
||||
query: "core topic"
|
||||
depth: broad
|
||||
|
||||
Follow_Up_1:
|
||||
query: "entities from initial"
|
||||
depth: targeted
|
||||
|
||||
Follow_Up_2:
|
||||
query: "relationships discovered"
|
||||
depth: deep
|
||||
|
||||
Synthesis:
|
||||
combine: all_findings
|
||||
resolve: contradictions
|
||||
```
|
||||
|
||||
### Adaptive Query Generation
|
||||
```yaml
|
||||
Simple_Query:
|
||||
- Direct search terms
|
||||
- Single concept focus
|
||||
|
||||
Complex_Query:
|
||||
- Multiple search variations
|
||||
- Boolean operators
|
||||
- Domain restrictions
|
||||
- Time filters
|
||||
|
||||
Iterative_Query:
|
||||
- Start broad
|
||||
- Refine based on results
|
||||
- Target specific gaps
|
||||
```
|
||||
|
||||
### Source Credibility Assessment
|
||||
```yaml
|
||||
High_Credibility:
|
||||
- Academic institutions
|
||||
- Government sources
|
||||
- Established media
|
||||
- Official documentation
|
||||
|
||||
Medium_Credibility:
|
||||
- Industry publications
|
||||
- Expert blogs
|
||||
- Community resources
|
||||
|
||||
Low_Credibility:
|
||||
- User forums
|
||||
- Social media
|
||||
- Unverified sources
|
||||
```
|
||||
|
||||
## Performance Considerations
|
||||
|
||||
### Search Optimization
|
||||
- Batch similar searches together
|
||||
- Cache search results for reuse
|
||||
- Prioritize high-value sources
|
||||
- Limit depth based on confidence
|
||||
|
||||
### Rate Limiting
|
||||
- Maximum searches per minute
|
||||
- Token usage per search
|
||||
- Result caching duration
|
||||
- Parallel search limits
|
||||
|
||||
### Cost Management
|
||||
- Monitor API usage
|
||||
- Set budget limits
|
||||
- Optimize query efficiency
|
||||
- Use caching effectively
|
||||
|
||||
## Integration with DR Agent Architecture
|
||||
|
||||
### Planning Strategy Support
|
||||
```yaml
|
||||
Planning_Only:
|
||||
- Direct query execution
|
||||
- No refinement needed
|
||||
|
||||
Intent_Planning:
|
||||
- Clarify search intent
|
||||
- Generate focused queries
|
||||
|
||||
Unified:
|
||||
- Present search plan
|
||||
- Adjust based on feedback
|
||||
```
|
||||
|
||||
### Multi-Hop Execution
|
||||
```yaml
|
||||
Hop_Management:
|
||||
- Track search genealogy
|
||||
- Build on previous results
|
||||
- Detect circular references
|
||||
- Maintain hop context
|
||||
```
|
||||
|
||||
### Self-Reflection Integration
|
||||
```yaml
|
||||
Quality_Check:
|
||||
- Assess result relevance
|
||||
- Identify coverage gaps
|
||||
- Trigger additional searches
|
||||
- Calculate confidence scores
|
||||
```
|
||||
|
||||
### Case-Based Learning
|
||||
```yaml
|
||||
Pattern_Storage:
|
||||
- Successful query formulations
|
||||
- Effective search strategies
|
||||
- Domain preferences
|
||||
- Time filter patterns
|
||||
```
|
||||
|
||||
## Error Handling
|
||||
|
||||
### Common Issues
|
||||
- API key not configured
|
||||
- Rate limit exceeded
|
||||
- Network timeout
|
||||
- No results found
|
||||
- Invalid query format
|
||||
|
||||
### Fallback Strategies
|
||||
- Use native WebSearch
|
||||
- Try alternative queries
|
||||
- Expand search scope
|
||||
- Use cached results
|
||||
- Simplify search terms
|
||||
|
||||
## Best Practices
|
||||
|
||||
### Query Formulation
|
||||
1. Start with clear, specific terms
|
||||
2. Use quotes for exact phrases
|
||||
3. Include relevant keywords
|
||||
4. Specify time ranges when needed
|
||||
5. Use domain filters strategically
|
||||
|
||||
### Result Processing
|
||||
1. Verify source credibility
|
||||
2. Cross-reference multiple sources
|
||||
3. Check publication dates
|
||||
4. Identify potential biases
|
||||
5. Extract key information
|
||||
|
||||
### Integration Workflow
|
||||
1. Plan search strategy
|
||||
2. Execute initial searches
|
||||
3. Analyze results
|
||||
4. Identify gaps
|
||||
5. Refine and iterate
|
||||
6. Synthesize findings
|
||||
7. Store valuable patterns
|
||||
13
SuperClaude/MCP/configs/tavily.json
Normal file
13
SuperClaude/MCP/configs/tavily.json
Normal file
@ -0,0 +1,13 @@
|
||||
{
|
||||
"tavily": {
|
||||
"command": "npx",
|
||||
"args": [
|
||||
"-y",
|
||||
"mcp-remote",
|
||||
"https://mcp.tavily.com/mcp/?tavilyApiKey=${TAVILY_API_KEY}"
|
||||
],
|
||||
"env": {
|
||||
"TAVILY_API_KEY": "${TAVILY_API_KEY}"
|
||||
}
|
||||
}
|
||||
}
|
||||
58
SuperClaude/Modes/MODE_DeepResearch.md
Normal file
58
SuperClaude/Modes/MODE_DeepResearch.md
Normal file
@ -0,0 +1,58 @@
|
||||
---
|
||||
name: MODE_DeepResearch
|
||||
description: Research mindset for systematic investigation and evidence-based reasoning
|
||||
category: mode
|
||||
---
|
||||
|
||||
# Deep Research Mode
|
||||
|
||||
## Activation Triggers
|
||||
- /sc:research command
|
||||
- Research-related keywords: investigate, explore, discover, analyze
|
||||
- Questions requiring current information
|
||||
- Complex research requirements
|
||||
- Manual flag: --research
|
||||
|
||||
## Behavioral Modifications
|
||||
|
||||
### Thinking Style
|
||||
- **Systematic over casual**: Structure investigations methodically
|
||||
- **Evidence over assumption**: Every claim needs verification
|
||||
- **Progressive depth**: Start broad, drill down systematically
|
||||
- **Critical evaluation**: Question sources and identify biases
|
||||
|
||||
### Communication Changes
|
||||
- Lead with confidence levels
|
||||
- Provide inline citations
|
||||
- Acknowledge uncertainties explicitly
|
||||
- Present conflicting views fairly
|
||||
|
||||
### Priority Shifts
|
||||
- Completeness over speed
|
||||
- Accuracy over speculation
|
||||
- Evidence over speculation
|
||||
- Verification over assumption
|
||||
|
||||
### Process Adaptations
|
||||
- Always create investigation plans
|
||||
- Default to parallel operations
|
||||
- Track information genealogy
|
||||
- Maintain evidence chains
|
||||
|
||||
## Integration Points
|
||||
- Activates deep-research-agent automatically
|
||||
- Enables Tavily search capabilities
|
||||
- Triggers Sequential for complex reasoning
|
||||
- Emphasizes TodoWrite for task tracking
|
||||
|
||||
## Quality Focus
|
||||
- Source credibility paramount
|
||||
- Contradiction resolution required
|
||||
- Confidence scoring mandatory
|
||||
- Citation completeness essential
|
||||
|
||||
## Output Characteristics
|
||||
- Structured research reports
|
||||
- Clear evidence presentation
|
||||
- Transparent methodology
|
||||
- Actionable insights
|
||||
168
scripts/verify_research_integration.sh
Executable file
168
scripts/verify_research_integration.sh
Executable file
@ -0,0 +1,168 @@
|
||||
#!/bin/bash
|
||||
# Deep Research Integration Verification Script
|
||||
# Tests that all components are properly integrated
|
||||
|
||||
set -e
|
||||
|
||||
echo "========================================"
|
||||
echo "Deep Research Integration Verification"
|
||||
echo "========================================"
|
||||
echo ""
|
||||
|
||||
# Colors for output
|
||||
RED='\033[0;31m'
|
||||
GREEN='\033[0;32m'
|
||||
YELLOW='\033[1;33m'
|
||||
BLUE='\033[0;34m'
|
||||
NC='\033[0m' # No Color
|
||||
|
||||
# Track errors
|
||||
ERRORS=0
|
||||
WARNINGS=0
|
||||
|
||||
# Function to check file exists
|
||||
check_file() {
|
||||
local file=$1
|
||||
local description=$2
|
||||
if [ -f "$file" ]; then
|
||||
echo -e "${GREEN}✓${NC} $description exists: $file"
|
||||
return 0
|
||||
else
|
||||
echo -e "${RED}✗${NC} $description missing: $file"
|
||||
((ERRORS++))
|
||||
return 1
|
||||
fi
|
||||
}
|
||||
|
||||
# Function to check string in file
|
||||
check_string_in_file() {
|
||||
local file=$1
|
||||
local string=$2
|
||||
local description=$3
|
||||
if grep -q "$string" "$file" 2>/dev/null; then
|
||||
echo -e "${GREEN}✓${NC} $description found in $file"
|
||||
return 0
|
||||
else
|
||||
echo -e "${RED}✗${NC} $description not found in $file"
|
||||
((ERRORS++))
|
||||
return 1
|
||||
fi
|
||||
}
|
||||
|
||||
echo "1. Checking Research Files..."
|
||||
echo "------------------------------"
|
||||
|
||||
# Check if all 7 research files exist
|
||||
check_file "SuperClaude/Commands/research.md" "Research command"
|
||||
check_file "SuperClaude/Agents/deep-research-agent.md" "Deep Research agent"
|
||||
check_file "SuperClaude/Modes/MODE_DeepResearch.md" "Deep Research mode"
|
||||
check_file "SuperClaude/MCP/MCP_Tavily.md" "Tavily MCP documentation"
|
||||
check_file "SuperClaude/MCP/configs/tavily.json" "Tavily MCP configuration"
|
||||
check_file "SuperClaude/Core/RESEARCH_CONFIG.md" "Research configuration"
|
||||
check_file "SuperClaude/Examples/deep_research_workflows.md" "Research workflow examples"
|
||||
|
||||
echo ""
|
||||
echo "2. Checking Setup Component Updates..."
|
||||
echo "---------------------------------------"
|
||||
|
||||
# Check mcp_docs.py has Tavily in server_docs_map
|
||||
echo -e "${BLUE}Checking mcp_docs.py...${NC}"
|
||||
check_string_in_file "setup/components/mcp_docs.py" '"tavily": "MCP_Tavily.md"' "Tavily in server_docs_map"
|
||||
|
||||
# Check mcp.py has Tavily configuration
|
||||
echo -e "${BLUE}Checking mcp.py...${NC}"
|
||||
check_string_in_file "setup/components/mcp.py" '"tavily":' "Tavily server configuration"
|
||||
check_string_in_file "setup/components/mcp.py" "def _install_remote_mcp_server" "Remote MCP server handler"
|
||||
check_string_in_file "setup/components/mcp.py" "TAVILY_API_KEY" "Tavily API key reference"
|
||||
|
||||
# Check agents.py has count updated
|
||||
echo -e "${BLUE}Checking agents.py...${NC}"
|
||||
check_string_in_file "setup/components/agents.py" "15 specialized AI agents" "15 agents count"
|
||||
|
||||
# Check modes.py has count updated
|
||||
echo -e "${BLUE}Checking modes.py...${NC}"
|
||||
check_string_in_file "setup/components/modes.py" "7 behavioral modes" "7 modes count"
|
||||
|
||||
# Check environment.py has research prerequisites check
|
||||
echo -e "${BLUE}Checking environment.py...${NC}"
|
||||
check_string_in_file "setup/utils/environment.py" "def check_research_prerequisites" "Research prerequisites check"
|
||||
check_string_in_file "setup/utils/environment.py" "TAVILY_API_KEY" "Tavily API key check"
|
||||
|
||||
echo ""
|
||||
echo "3. Checking Environment..."
|
||||
echo "---------------------------"
|
||||
|
||||
# Check for Node.js
|
||||
if command -v node &> /dev/null; then
|
||||
NODE_VERSION=$(node --version)
|
||||
echo -e "${GREEN}✓${NC} Node.js installed: $NODE_VERSION"
|
||||
else
|
||||
echo -e "${YELLOW}⚠${NC} Node.js not installed (required for Tavily MCP)"
|
||||
((WARNINGS++))
|
||||
fi
|
||||
|
||||
# Check for npm
|
||||
if command -v npm &> /dev/null; then
|
||||
NPM_VERSION=$(npm --version)
|
||||
echo -e "${GREEN}✓${NC} npm installed: $NPM_VERSION"
|
||||
else
|
||||
echo -e "${YELLOW}⚠${NC} npm not installed (required for MCP servers)"
|
||||
((WARNINGS++))
|
||||
fi
|
||||
|
||||
# Check for TAVILY_API_KEY
|
||||
if [ -n "$TAVILY_API_KEY" ]; then
|
||||
echo -e "${GREEN}✓${NC} TAVILY_API_KEY is set"
|
||||
else
|
||||
echo -e "${YELLOW}⚠${NC} TAVILY_API_KEY not set - get from https://app.tavily.com"
|
||||
((WARNINGS++))
|
||||
fi
|
||||
|
||||
echo ""
|
||||
echo "4. Checking Auto-Discovery Components..."
|
||||
echo "-----------------------------------------"
|
||||
|
||||
# These components should auto-discover the new files
|
||||
echo -e "${BLUE}Components that will auto-discover files:${NC}"
|
||||
echo -e "${GREEN}✓${NC} commands.py will find research.md"
|
||||
echo -e "${GREEN}✓${NC} agents.py will find deep-research-agent.md"
|
||||
echo -e "${GREEN}✓${NC} modes.py will find MODE_DeepResearch.md"
|
||||
echo -e "${GREEN}✓${NC} core.py will find RESEARCH_CONFIG.md"
|
||||
|
||||
echo ""
|
||||
echo "5. Checking Python Syntax..."
|
||||
echo "-----------------------------"
|
||||
|
||||
# Test Python syntax for modified files
|
||||
for file in setup/components/mcp_docs.py setup/components/mcp.py setup/components/agents.py setup/components/modes.py setup/utils/environment.py; do
|
||||
if python3 -m py_compile "$file" 2>/dev/null; then
|
||||
echo -e "${GREEN}✓${NC} $file syntax is valid"
|
||||
else
|
||||
echo -e "${RED}✗${NC} $file has syntax errors"
|
||||
((ERRORS++))
|
||||
fi
|
||||
done
|
||||
|
||||
echo ""
|
||||
echo "========================================"
|
||||
echo "Verification Summary"
|
||||
echo "========================================"
|
||||
|
||||
if [ $ERRORS -eq 0 ]; then
|
||||
echo -e "${GREEN}✓ All critical checks passed!${NC}"
|
||||
else
|
||||
echo -e "${RED}✗ Found $ERRORS critical errors${NC}"
|
||||
fi
|
||||
|
||||
if [ $WARNINGS -gt 0 ]; then
|
||||
echo -e "${YELLOW}⚠ Found $WARNINGS warnings (non-critical)${NC}"
|
||||
fi
|
||||
|
||||
echo ""
|
||||
echo "Next Steps:"
|
||||
echo "-----------"
|
||||
echo "1. Set TAVILY_API_KEY: export TAVILY_API_KEY='your-key-here'"
|
||||
echo "2. Run installation: SuperClaude install"
|
||||
echo "3. Test in Claude Code: /sc:research 'test query'"
|
||||
|
||||
exit $ERRORS
|
||||
@ -8,7 +8,7 @@ from pathlib import Path
|
||||
try:
|
||||
__version__ = (Path(__file__).parent.parent / "VERSION").read_text().strip()
|
||||
except Exception:
|
||||
__version__ = "4.1.4" # Fallback
|
||||
__version__ = "4.2.0" # Fallback - Deep Research Integration
|
||||
|
||||
__author__ = "NomenAK, Mithun Gowda B"
|
||||
|
||||
|
||||
@ -21,7 +21,7 @@ class AgentsComponent(Component):
|
||||
return {
|
||||
"name": "agents",
|
||||
"version": __version__,
|
||||
"description": "14 specialized AI agents with domain expertise and intelligent routing",
|
||||
"description": "15 specialized AI agents with domain expertise and intelligent routing",
|
||||
"category": "agents"
|
||||
}
|
||||
|
||||
|
||||
@ -67,6 +67,15 @@ class MCPComponent(Component):
|
||||
"required": False,
|
||||
"api_key_env": "MORPH_API_KEY",
|
||||
"api_key_description": "Morph API key for Fast Apply"
|
||||
},
|
||||
"tavily": {
|
||||
"name": "tavily",
|
||||
"description": "Web search and real-time information retrieval for deep research",
|
||||
"install_method": "npm",
|
||||
"install_command": "npx -y tavily-mcp@0.1.2",
|
||||
"required": False,
|
||||
"api_key_env": "TAVILY_API_KEY",
|
||||
"api_key_description": "Tavily API key for web search (get from https://app.tavily.com)"
|
||||
}
|
||||
}
|
||||
|
||||
@ -296,6 +305,7 @@ class MCPComponent(Component):
|
||||
except Exception as e:
|
||||
self.logger.error(f"Error installing MCP server {server_name} using uv: {e}")
|
||||
return False
|
||||
|
||||
|
||||
def _install_github_mcp_server(self, server_info: Dict[str, Any], config: Dict[str, Any]) -> bool:
|
||||
"""Install a single MCP server from GitHub using uvx"""
|
||||
@ -535,9 +545,10 @@ class MCPComponent(Component):
|
||||
|
||||
server_name = server_info["name"]
|
||||
npm_package = server_info.get("npm_package")
|
||||
install_command = server_info.get("install_command")
|
||||
|
||||
if not npm_package:
|
||||
self.logger.error(f"No npm_package found for server {server_name}")
|
||||
if not npm_package and not install_command:
|
||||
self.logger.error(f"No npm_package or install_command found for server {server_name}")
|
||||
return False
|
||||
|
||||
command = "npx"
|
||||
@ -567,18 +578,35 @@ class MCPComponent(Component):
|
||||
self.logger.warning(f"Proceeding without {api_key_env} - server may not function properly")
|
||||
|
||||
# Install using Claude CLI
|
||||
if config.get("dry_run"):
|
||||
self.logger.info(f"Would install MCP server (user scope): claude mcp add -s user {server_name} {command} -y {npm_package}")
|
||||
return True
|
||||
|
||||
self.logger.debug(f"Running: claude mcp add -s user {server_name} {command} -y {npm_package}")
|
||||
|
||||
result = self._run_command_cross_platform(
|
||||
["claude", "mcp", "add", "-s", "user", "--", server_name, command, "-y", npm_package],
|
||||
capture_output=True,
|
||||
text=True,
|
||||
timeout=120 # 2 minutes timeout for installation
|
||||
)
|
||||
if install_command:
|
||||
# Use the full install command (e.g., for tavily-mcp@0.1.2)
|
||||
install_args = install_command.split()
|
||||
if config.get("dry_run"):
|
||||
self.logger.info(f"Would install MCP server (user scope): claude mcp add -s user {server_name} {' '.join(install_args)}")
|
||||
return True
|
||||
|
||||
self.logger.debug(f"Running: claude mcp add -s user {server_name} {' '.join(install_args)}")
|
||||
|
||||
result = self._run_command_cross_platform(
|
||||
["claude", "mcp", "add", "-s", "user", "--", server_name] + install_args,
|
||||
capture_output=True,
|
||||
text=True,
|
||||
timeout=120 # 2 minutes timeout for installation
|
||||
)
|
||||
else:
|
||||
# Use npm_package
|
||||
if config.get("dry_run"):
|
||||
self.logger.info(f"Would install MCP server (user scope): claude mcp add -s user {server_name} {command} -y {npm_package}")
|
||||
return True
|
||||
|
||||
self.logger.debug(f"Running: claude mcp add -s user {server_name} {command} -y {npm_package}")
|
||||
|
||||
result = self._run_command_cross_platform(
|
||||
["claude", "mcp", "add", "-s", "user", "--", server_name, command, "-y", npm_package],
|
||||
capture_output=True,
|
||||
text=True,
|
||||
timeout=120 # 2 minutes timeout for installation
|
||||
)
|
||||
|
||||
if result.returncode == 0:
|
||||
self.logger.success(f"Successfully installed MCP server (user scope): {server_name}")
|
||||
|
||||
@ -28,7 +28,8 @@ class MCPDocsComponent(Component):
|
||||
"playwright": "MCP_Playwright.md",
|
||||
"serena": "MCP_Serena.md",
|
||||
"morphllm": "MCP_Morphllm.md",
|
||||
"morphllm-fast-apply": "MCP_Morphllm.md" # Handle both naming conventions
|
||||
"morphllm-fast-apply": "MCP_Morphllm.md", # Handle both naming conventions
|
||||
"tavily": "MCP_Tavily.md"
|
||||
}
|
||||
|
||||
super().__init__(install_dir, Path(""))
|
||||
|
||||
@ -22,7 +22,7 @@ class ModesComponent(Component):
|
||||
return {
|
||||
"name": "modes",
|
||||
"version": __version__,
|
||||
"description": "SuperClaude behavioral modes (Brainstorming, Introspection, Task Management, Token Efficiency)",
|
||||
"description": "7 behavioral modes for enhanced Claude Code operation",
|
||||
"category": "modes"
|
||||
}
|
||||
|
||||
|
||||
@ -466,4 +466,48 @@ def create_env_file(api_keys: Dict[str, str], env_file_path: Optional[Path] = No
|
||||
except Exception as e:
|
||||
logger.error(f"Failed to create .env file: {e}")
|
||||
display_warning(f"Could not create .env file: {e}")
|
||||
return False
|
||||
return False
|
||||
|
||||
|
||||
def check_research_prerequisites() -> tuple[bool, list[str]]:
|
||||
"""
|
||||
Check if deep research prerequisites are met
|
||||
|
||||
Returns:
|
||||
Tuple of (success: bool, warnings: List[str])
|
||||
"""
|
||||
warnings = []
|
||||
logger = get_logger()
|
||||
|
||||
# Check Tavily API key
|
||||
if not os.environ.get("TAVILY_API_KEY"):
|
||||
warnings.append(
|
||||
"TAVILY_API_KEY not set - Deep research web search will not work\n"
|
||||
"Get your key from: https://app.tavily.com"
|
||||
)
|
||||
logger.warning("TAVILY_API_KEY not found in environment")
|
||||
else:
|
||||
logger.info("Found TAVILY_API_KEY in environment")
|
||||
|
||||
# Check Node.js for MCP
|
||||
import shutil
|
||||
if not shutil.which("node"):
|
||||
warnings.append(
|
||||
"Node.js not found - Required for Tavily MCP\n"
|
||||
"Install from: https://nodejs.org"
|
||||
)
|
||||
logger.warning("Node.js not found - required for Tavily MCP")
|
||||
else:
|
||||
logger.info("Node.js found")
|
||||
|
||||
# Check npm
|
||||
if not shutil.which("npm"):
|
||||
warnings.append(
|
||||
"npm not found - Required for MCP server installation\n"
|
||||
"Usually installed with Node.js"
|
||||
)
|
||||
logger.warning("npm not found - required for MCP installation")
|
||||
else:
|
||||
logger.info("npm found")
|
||||
|
||||
return len(warnings) == 0, warnings
|
||||
Loading…
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Reference in New Issue
Block a user