mirror of
https://github.com/SuperClaude-Org/SuperClaude_Framework.git
synced 2025-12-29 16:16:08 +00:00
refactor: PEP8 compliance - directory rename and code formatting (#425)
* fix(orchestration): add WebFetch auto-trigger for infrastructure configuration Problem: Infrastructure configuration changes (e.g., Traefik port settings) were being made based on assumptions without consulting official documentation, violating the 'Evidence > assumptions' principle in PRINCIPLES.md. Solution: - Added Infrastructure Configuration Validation section to MODE_Orchestration.md - Auto-triggers WebFetch for infrastructure tools (Traefik, nginx, Docker, etc.) - Enforces MODE_DeepResearch activation for investigation - BLOCKS assumption-based configuration changes Testing: Verified WebFetch successfully retrieves Traefik official docs (port 80 default) This prevents production outages from infrastructure misconfiguration by ensuring all technical recommendations are backed by official documentation. * feat: Add PM Agent (Project Manager Agent) for seamless orchestration Introduces PM Agent as the default orchestration layer that coordinates all sub-agents and manages workflows automatically. Key Features: - Default orchestration: All user interactions handled by PM Agent - Auto-delegation: Intelligent sub-agent selection based on task analysis - Docker Gateway integration: Zero-token baseline with dynamic MCP loading - Self-improvement loop: Automatic documentation of patterns and mistakes - Optional override: Users can specify sub-agents explicitly if desired Architecture: - Agent spec: SuperClaude/Agents/pm-agent.md - Command: SuperClaude/Commands/pm.md - Updated docs: README.md (15→16 agents), agents.md (new Orchestration category) User Experience: - Default: PM Agent handles everything (seamless, no manual routing) - Optional: Explicit --agent flag for direct sub-agent access - Both modes available simultaneously (no user downside) Implementation Status: - ✅ Specification complete - ✅ Documentation complete - ⏳ Prototype implementation needed - ⏳ Docker Gateway integration needed - ⏳ Testing and validation needed Refs: kazukinakai/docker-mcp-gateway (IRIS MCP Gateway integration) * feat: Add Agent Orchestration rules for PM Agent default activation Implements PM Agent as the default orchestration layer in RULES.md. Key Changes: - New 'Agent Orchestration' section (CRITICAL priority) - PM Agent receives ALL user requests by default - Manual override with @agent-[name] bypasses PM Agent - Agent Selection Priority clearly defined: 1. Manual override → Direct routing 2. Default → PM Agent → Auto-delegation 3. Delegation based on keywords, file types, complexity, context User Experience: - Default: PM Agent handles everything (seamless) - Override: @agent-[name] for direct specialist access - Transparent: PM Agent reports delegation decisions This establishes PM Agent as the orchestration layer while respecting existing auto-activation patterns and manual overrides. Next Steps: - Local testing in agiletec project - Iteration based on actual behavior - Documentation updates as needed * refactor(pm-agent): redesign as self-improvement meta-layer Problem Resolution: PM Agent's initial design competed with existing auto-activation for task routing, creating confusion about orchestration responsibilities and adding unnecessary complexity. Design Change: Redefined PM Agent as a meta-layer agent that operates AFTER specialist agents complete tasks, focusing on: - Post-implementation documentation and pattern recording - Immediate mistake analysis with prevention checklists - Monthly documentation maintenance and noise reduction - Pattern extraction and knowledge synthesis Two-Layer Orchestration System: 1. Task Execution Layer: Existing auto-activation handles task routing (unchanged) 2. Self-Improvement Layer: PM Agent meta-layer handles documentation (new) Files Modified: - SuperClaude/Agents/pm-agent.md: Complete rewrite with meta-layer design - Category: orchestration → meta - Triggers: All user interactions → Post-implementation, mistakes, monthly - Behavioral Mindset: Continuous learning system - Self-Improvement Workflow: BEFORE/DURING/AFTER/MISTAKE RECOVERY/MAINTENANCE - SuperClaude/Core/RULES.md: Agent Orchestration section updated - Split into Task Execution Layer + Self-Improvement Layer - Added orchestration flow diagram - Clarified PM Agent activates AFTER task completion - README.md: Updated PM Agent description - "orchestrates all interactions" → "ensures continuous learning" - Docs/User-Guide/agents.md: PM Agent section rewritten - Section: Orchestration Agent → Meta-Layer Agent - Expertise: Project orchestration → Self-improvement workflow executor - Examples: Task coordination → Post-implementation documentation - PR_DOCUMENTATION.md: Comprehensive PR documentation added - Summary, motivation, changes, testing, breaking changes - Two-layer orchestration system diagram - Verification checklist Integration Validated: Tested with agiletec project's self-improvement-workflow.md: ✅ PM Agent aligns with existing BEFORE/DURING/AFTER/MISTAKE RECOVERY phases ✅ Complements (not competes with) existing workflow ✅ agiletec workflow defines WHAT, PM Agent defines WHO executes it Breaking Changes: None - Existing auto-activation continues unchanged - Specialist agents unaffected - User workflows remain the same - New capability: Automatic documentation and knowledge maintenance Value Proposition: Transforms SuperClaude into a continuously learning system that accumulates knowledge, prevents recurring mistakes, and maintains fresh documentation without manual intervention. 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude <noreply@anthropic.com> * docs: add Claude Code conversation history management research Research covering .jsonl file structure, performance impact, and retention policies. Content: - Claude Code .jsonl file format and message types - Performance issues from GitHub (memory leaks, conversation compaction) - Retention policies (consumer vs enterprise) - Rotation recommendations based on actual data - File history snapshot tracking mechanics Source: Moved from agiletec project (research applicable to all Claude Code projects) 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude <noreply@anthropic.com> * feat: add Development documentation structure Phase 1: Documentation Structure complete - Add Docs/Development/ directory for development documentation - Add ARCHITECTURE.md - System architecture with PM Agent meta-layer - Add ROADMAP.md - 5-phase development plan with checkboxes - Add TASKS.md - Daily task tracking with progress indicators - Add PROJECT_STATUS.md - Current status dashboard and metrics - Add pm-agent-integration.md - Implementation guide for PM Agent mode This establishes comprehensive documentation foundation for: - System architecture understanding - Development planning and tracking - Implementation guidance - Progress visibility Related: #pm-agent-mode #documentation #phase-1 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude <noreply@anthropic.com> * feat: PM Agent session lifecycle and PDCA implementation Phase 2: PM Agent Mode Integration (Design Phase) Commands/pm.md updates: - Add "Always-Active Foundation Layer" concept - Add Session Lifecycle (Session Start/During Work/Session End) - Add PDCA Cycle (Plan/Do/Check/Act) automation - Add Serena MCP Memory Integration (list/read/write_memory) - Document auto-activation triggers Agents/pm-agent.md updates: - Add Session Start Protocol (MANDATORY auto-activation) - Add During Work PDCA Cycle with example workflows - Add Session End Protocol with state preservation - Add PDCA Self-Evaluation Pattern - Add Documentation Strategy (temp → patterns/mistakes) - Add Memory Operations Reference Key Features: - Session start auto-activation for context restoration - 30-minute checkpoint saves during work - Self-evaluation with think_about_* operations - Systematic documentation lifecycle - Knowledge evolution to CLAUDE.md Implementation Status: - ✅ Design complete (Commands/pm.md, Agents/pm-agent.md) - ⏳ Implementation pending (Core components) - ⏳ Serena MCP integration pending Salvaged from mistaken development in ~/.claude directory Related: #pm-agent-mode #session-lifecycle #pdca-cycle #phase-2 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude <noreply@anthropic.com> * fix: disable Serena MCP auto-browser launch Disable web dashboard and GUI log window auto-launch in Serena MCP server to prevent intrusive browser popups on startup. Users can still manually access the dashboard at http://localhost:24282/dashboard/ if needed. Changes: - Add CLI flags to Serena run command: - --enable-web-dashboard false - --enable-gui-log-window false - Ensures Git-tracked configuration (no reliance on ~/.serena/serena_config.yml) - Aligns with AIRIS MCP Gateway integration approach 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude <noreply@anthropic.com> * refactor: rename directories to lowercase for PEP8 compliance - Rename superclaude/Agents -> superclaude/agents - Rename superclaude/Commands -> superclaude/commands - Rename superclaude/Core -> superclaude/core - Rename superclaude/Examples -> superclaude/examples - Rename superclaude/MCP -> superclaude/mcp - Rename superclaude/Modes -> superclaude/modes This change follows Python PEP8 naming conventions for package directories. * style: fix PEP8 violations and update package name to lowercase Changes: - Format all Python files with black (43 files reformatted) - Update package name from 'SuperClaude' to 'superclaude' in pyproject.toml - Fix import statements to use lowercase package name - Add missing imports (timedelta, __version__) - Remove old SuperClaude.egg-info directory PEP8 violations reduced from 2672 to 701 (mostly E501 line length due to black's 88 char vs flake8's 79 char limit). * docs: add PM Agent development documentation Add comprehensive PM Agent development documentation: - PM Agent ideal workflow (7-phase autonomous cycle) - Project structure understanding (Git vs installed environment) - Installation flow understanding (CommandsComponent behavior) - Task management system (current-tasks.md) Purpose: Eliminate repeated explanations and enable autonomous PDCA cycles 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude <noreply@anthropic.com> * feat(pm-agent): add self-correcting execution and warning investigation culture ## Changes ### superclaude/commands/pm.md - Add "Self-Correcting Execution" section with root cause analysis protocol - Add "Warning/Error Investigation Culture" section enforcing zero-tolerance for dismissal - Define error detection protocol: STOP → Investigate → Hypothesis → Different Solution → Execute - Document anti-patterns (retry without understanding) and correct patterns (research-first) ### docs/Development/hypothesis-pm-autonomous-enhancement-2025-10-14.md - Add PDCA workflow hypothesis document for PM Agent autonomous enhancement ## Rationale PM Agent must never retry failed operations without understanding root causes. All warnings and errors require investigation via context7/WebFetch/documentation to ensure production-quality code and prevent technical debt accumulation. 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude <noreply@anthropic.com> * feat(installer): add airis-mcp-gateway MCP server option ## Changes - Add airis-mcp-gateway to MCP server options in installer - Configuration: GitHub-based installation via uvx - Repository: https://github.com/oraios/airis-mcp-gateway - Purpose: Dynamic MCP Gateway for zero-token baseline and on-demand tool loading ## Implementation Added to setup/components/mcp.py self.mcp_servers dictionary with: - install_method: github - install_command: uvx test installation - run_command: uvx runtime execution - required: False (optional server) 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude <noreply@anthropic.com> --------- Co-authored-by: kazuki <kazuki@kazukinoMacBook-Air.local> Co-authored-by: Claude <noreply@anthropic.com>
This commit is contained in:
32
superclaude/mcp/MCP_Chrome-DevTools.md
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superclaude/mcp/MCP_Chrome-DevTools.md
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# Chrome DevTools MCP Server
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**Purpose**: Performance analysis, debugging, and real-time browser inspection
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## Triggers
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- Performance auditing and analysis requests
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- Debugging of layout issues (e.g., CLS)
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- Investigation of slow loading times (e.g., LCP)
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- Analysis of console errors and network requests
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- Real-time inspection of the DOM and CSS
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## Choose When
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- **For deep performance analysis**: When you need to understand performance bottlenecks.
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- **For live debugging**: To inspect the runtime state of a web page and debug live issues.
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- **For network analysis**: To inspect network requests and identify issues like CORS errors.
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- **Not for E2E testing**: Use Playwright for end-to-end testing scenarios.
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- **Not for static analysis**: Use native Claude for code review and logic validation.
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## Works Best With
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- **Sequential**: Sequential plans a performance improvement strategy → Chrome DevTools analyzes and verifies the improvements.
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- **Playwright**: Playwright automates a user flow → Chrome DevTools analyzes the performance of that flow.
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## Examples
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```
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"analyze the performance of this page" → Chrome DevTools (performance analysis)
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"why is this page loading slowly?" → Chrome DevTools (performance analysis)
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"debug the layout shift on this element" → Chrome DevTools (live debugging)
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"check for console errors on the homepage" → Chrome DevTools (live debugging)
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"what network requests are failing?" → Chrome DevTools (network analysis)
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"test the login flow" → Playwright (browser automation)
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"review this function's logic" → Native Claude (static analysis)
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```
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30
superclaude/mcp/MCP_Context7.md
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superclaude/mcp/MCP_Context7.md
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# Context7 MCP Server
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**Purpose**: Official library documentation lookup and framework pattern guidance
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## Triggers
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- Import statements: `import`, `require`, `from`, `use`
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- Framework keywords: React, Vue, Angular, Next.js, Express, etc.
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- Library-specific questions about APIs or best practices
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- Need for official documentation patterns vs generic solutions
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- Version-specific implementation requirements
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## Choose When
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- **Over WebSearch**: When you need curated, version-specific documentation
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- **Over native knowledge**: When implementation must follow official patterns
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- **For frameworks**: React hooks, Vue composition API, Angular services
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- **For libraries**: Correct API usage, authentication flows, configuration
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- **For compliance**: When adherence to official standards is mandatory
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## Works Best With
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- **Sequential**: Context7 provides docs → Sequential analyzes implementation strategy
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- **Magic**: Context7 supplies patterns → Magic generates framework-compliant components
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## Examples
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```
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"implement React useEffect" → Context7 (official React patterns)
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"add authentication with Auth0" → Context7 (official Auth0 docs)
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"migrate to Vue 3" → Context7 (official migration guide)
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"optimize Next.js performance" → Context7 (official optimization patterns)
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"just explain this function" → Native Claude (no external docs needed)
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```
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31
superclaude/mcp/MCP_Magic.md
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superclaude/mcp/MCP_Magic.md
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# Magic MCP Server
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**Purpose**: Modern UI component generation from 21st.dev patterns with design system integration
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## Triggers
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- UI component requests: button, form, modal, card, table, nav
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- Design system implementation needs
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- `/ui` or `/21` commands
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- Frontend-specific keywords: responsive, accessible, interactive
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- Component enhancement or refinement requests
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## Choose When
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- **For UI components**: Use Magic, not native HTML/CSS generation
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- **Over manual coding**: When you need production-ready, accessible components
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- **For design systems**: When consistency with existing patterns matters
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- **For modern frameworks**: React, Vue, Angular with current best practices
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- **Not for backend**: API logic, database queries, server configuration
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## Works Best With
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- **Context7**: Magic uses 21st.dev patterns → Context7 provides framework integration
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- **Sequential**: Sequential analyzes UI requirements → Magic implements structured components
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## Examples
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```
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"create a login form" → Magic (UI component generation)
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"build a responsive navbar" → Magic (UI pattern with accessibility)
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"add a data table with sorting" → Magic (complex UI component)
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"make this component accessible" → Magic (UI enhancement)
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"write a REST API" → Native Claude (backend logic)
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"fix database query" → Native Claude (non-UI task)
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```
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31
superclaude/mcp/MCP_Morphllm.md
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31
superclaude/mcp/MCP_Morphllm.md
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# Morphllm MCP Server
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**Purpose**: Pattern-based code editing engine with token optimization for bulk transformations
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## Triggers
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- Multi-file edit operations requiring consistent patterns
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- Framework updates, style guide enforcement, code cleanup
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- Bulk text replacements across multiple files
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- Natural language edit instructions with specific scope
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- Token optimization needed (efficiency gains 30-50%)
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## Choose When
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- **Over Serena**: For pattern-based edits, not symbol operations
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- **For bulk operations**: Style enforcement, framework updates, text replacements
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- **When token efficiency matters**: Fast Apply scenarios with compression needs
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- **For simple to moderate complexity**: <10 files, straightforward transformations
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- **Not for semantic operations**: Symbol renames, dependency tracking, LSP integration
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## Works Best With
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- **Serena**: Serena analyzes semantic context → Morphllm executes precise edits
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- **Sequential**: Sequential plans edit strategy → Morphllm applies systematic changes
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## Examples
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```
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"update all React class components to hooks" → Morphllm (pattern transformation)
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"enforce ESLint rules across project" → Morphllm (style guide application)
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"replace all console.log with logger calls" → Morphllm (bulk text replacement)
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"rename getUserData function everywhere" → Serena (symbol operation)
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"analyze code architecture" → Sequential (complex analysis)
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"explain this algorithm" → Native Claude (simple explanation)
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```
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32
superclaude/mcp/MCP_Playwright.md
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32
superclaude/mcp/MCP_Playwright.md
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# Playwright MCP Server
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**Purpose**: Browser automation and E2E testing with real browser interaction
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## Triggers
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- Browser testing and E2E test scenarios
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- Visual testing, screenshot, or UI validation requests
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- Form submission and user interaction testing
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- Cross-browser compatibility validation
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- Performance testing requiring real browser rendering
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- Accessibility testing with automated WCAG compliance
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## Choose When
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- **For real browser interaction**: When you need actual rendering, not just code
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- **Over unit tests**: For integration testing, user journeys, visual validation
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- **For E2E scenarios**: Login flows, form submissions, multi-page workflows
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- **For visual testing**: Screenshot comparisons, responsive design validation
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- **Not for code analysis**: Static code review, syntax checking, logic validation
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## Works Best With
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- **Sequential**: Sequential plans test strategy → Playwright executes browser automation
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- **Magic**: Magic creates UI components → Playwright validates accessibility and behavior
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## Examples
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```
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"test the login flow" → Playwright (browser automation)
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"check if form validation works" → Playwright (real user interaction)
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"take screenshots of responsive design" → Playwright (visual testing)
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"validate accessibility compliance" → Playwright (automated WCAG testing)
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"review this function's logic" → Native Claude (static analysis)
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"explain the authentication code" → Native Claude (code review)
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```
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33
superclaude/mcp/MCP_Sequential.md
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33
superclaude/mcp/MCP_Sequential.md
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# Sequential MCP Server
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**Purpose**: Multi-step reasoning engine for complex analysis and systematic problem solving
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## Triggers
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- Complex debugging scenarios with multiple layers
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- Architectural analysis and system design questions
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- `--think`, `--think-hard`, `--ultrathink` flags
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- Problems requiring hypothesis testing and validation
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- Multi-component failure investigation
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- Performance bottleneck identification requiring methodical approach
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## Choose When
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- **Over native reasoning**: When problems have 3+ interconnected components
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- **For systematic analysis**: Root cause analysis, architecture review, security assessment
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- **When structure matters**: Problems benefit from decomposition and evidence gathering
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- **For cross-domain issues**: Problems spanning frontend, backend, database, infrastructure
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- **Not for simple tasks**: Basic explanations, single-file changes, straightforward fixes
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## Works Best With
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- **Context7**: Sequential coordinates analysis → Context7 provides official patterns
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- **Magic**: Sequential analyzes UI logic → Magic implements structured components
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- **Playwright**: Sequential identifies testing strategy → Playwright executes validation
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## Examples
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```
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"why is this API slow?" → Sequential (systematic performance analysis)
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"design a microservices architecture" → Sequential (structured system design)
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"debug this authentication flow" → Sequential (multi-component investigation)
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"analyze security vulnerabilities" → Sequential (comprehensive threat modeling)
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"explain this function" → Native Claude (simple explanation)
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"fix this typo" → Native Claude (straightforward change)
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```
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32
superclaude/mcp/MCP_Serena.md
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32
superclaude/mcp/MCP_Serena.md
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# Serena MCP Server
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**Purpose**: Semantic code understanding with project memory and session persistence
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## Triggers
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- Symbol operations: rename, extract, move functions/classes
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- Project-wide code navigation and exploration
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- Multi-language projects requiring LSP integration
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- Session lifecycle: `/sc:load`, `/sc:save`, project activation
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- Memory-driven development workflows
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- Large codebase analysis (>50 files, complex architecture)
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## Choose When
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- **Over Morphllm**: For symbol operations, not pattern-based edits
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- **For semantic understanding**: Symbol references, dependency tracking, LSP integration
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- **For session persistence**: Project context, memory management, cross-session learning
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- **For large projects**: Multi-language codebases requiring architectural understanding
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- **Not for simple edits**: Basic text replacements, style enforcement, bulk operations
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## Works Best With
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- **Morphllm**: Serena analyzes semantic context → Morphllm executes precise edits
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- **Sequential**: Serena provides project context → Sequential performs architectural analysis
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## Examples
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```
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"rename getUserData function everywhere" → Serena (symbol operation with dependency tracking)
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"find all references to this class" → Serena (semantic search and navigation)
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"load my project context" → Serena (/sc:load with project activation)
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"save my current work session" → Serena (/sc:save with memory persistence)
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"update all console.log to logger" → Morphllm (pattern-based replacement)
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"create a login form" → Magic (UI component generation)
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```
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285
superclaude/mcp/MCP_Tavily.md
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285
superclaude/mcp/MCP_Tavily.md
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# Tavily MCP Server
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**Purpose**: Web search and real-time information retrieval for research and current events
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## Triggers
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- Web search requirements beyond Claude's knowledge cutoff
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- Current events, news, and real-time information needs
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- Market research and competitive analysis tasks
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- Technical documentation not in training data
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- Academic research requiring recent publications
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- Fact-checking and verification needs
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- Deep research investigations requiring multi-source analysis
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- `/sc:research` command activation
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## Choose When
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- **Over WebSearch**: When you need structured search with advanced filtering
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- **Over WebFetch**: When you need multi-source search, not single page extraction
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- **For research**: Comprehensive investigations requiring multiple sources
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- **For current info**: Events, updates, or changes after knowledge cutoff
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- **Not for**: Simple questions answerable from training, code generation, local file operations
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## Works Best With
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- **Sequential**: Tavily provides raw information → Sequential analyzes and synthesizes
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- **Playwright**: Tavily discovers URLs → Playwright extracts complex content
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- **Context7**: Tavily searches for updates → Context7 provides stable documentation
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- **Serena**: Tavily performs searches → Serena stores research sessions
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## Configuration
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Requires TAVILY_API_KEY environment variable from https://app.tavily.com
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## Search Capabilities
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- **Web Search**: General web searches with ranking algorithms
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- **News Search**: Time-filtered news and current events
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- **Academic Search**: Scholarly articles and research papers
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- **Domain Filtering**: Include/exclude specific domains
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- **Content Extraction**: Full-text extraction from search results
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- **Freshness Control**: Prioritize recent content
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- **Multi-Round Searching**: Iterative refinement based on gaps
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## Examples
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```
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"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
|
||||
0
superclaude/mcp/__init__.py
Normal file
0
superclaude/mcp/__init__.py
Normal file
9
superclaude/mcp/configs/context7.json
Normal file
9
superclaude/mcp/configs/context7.json
Normal file
@@ -0,0 +1,9 @@
|
||||
{
|
||||
"context7": {
|
||||
"command": "npx",
|
||||
"args": [
|
||||
"-y",
|
||||
"@upstash/context7-mcp@latest"
|
||||
]
|
||||
}
|
||||
}
|
||||
12
superclaude/mcp/configs/magic.json
Normal file
12
superclaude/mcp/configs/magic.json
Normal file
@@ -0,0 +1,12 @@
|
||||
{
|
||||
"magic": {
|
||||
"type": "stdio",
|
||||
"command": "npx",
|
||||
"args": [
|
||||
"@21st-dev/magic"
|
||||
],
|
||||
"env": {
|
||||
"TWENTYFIRST_API_KEY": ""
|
||||
}
|
||||
}
|
||||
}
|
||||
13
superclaude/mcp/configs/morphllm.json
Normal file
13
superclaude/mcp/configs/morphllm.json
Normal file
@@ -0,0 +1,13 @@
|
||||
{
|
||||
"morphllm-fast-apply": {
|
||||
"command": "npx",
|
||||
"args": [
|
||||
"@morph-llm/morph-fast-apply",
|
||||
"/home/"
|
||||
],
|
||||
"env": {
|
||||
"MORPH_API_KEY": "",
|
||||
"ALL_TOOLS": "true"
|
||||
}
|
||||
}
|
||||
}
|
||||
8
superclaude/mcp/configs/playwright.json
Normal file
8
superclaude/mcp/configs/playwright.json
Normal file
@@ -0,0 +1,8 @@
|
||||
{
|
||||
"playwright": {
|
||||
"command": "npx",
|
||||
"args": [
|
||||
"@playwright/mcp@latest"
|
||||
]
|
||||
}
|
||||
}
|
||||
9
superclaude/mcp/configs/sequential.json
Normal file
9
superclaude/mcp/configs/sequential.json
Normal file
@@ -0,0 +1,9 @@
|
||||
{
|
||||
"sequential-thinking": {
|
||||
"command": "npx",
|
||||
"args": [
|
||||
"-y",
|
||||
"@modelcontextprotocol/server-sequential-thinking"
|
||||
]
|
||||
}
|
||||
}
|
||||
14
superclaude/mcp/configs/serena-docker.json
Normal file
14
superclaude/mcp/configs/serena-docker.json
Normal file
@@ -0,0 +1,14 @@
|
||||
{
|
||||
"serena": {
|
||||
"command": "docker",
|
||||
"args": [
|
||||
"run",
|
||||
"--rm",
|
||||
"-v", "${PWD}:/workspace",
|
||||
"--workdir", "/workspace",
|
||||
"python:3.11-slim",
|
||||
"bash", "-c",
|
||||
"pip install uv && uv tool install serena-ai && uv tool run serena-ai start-mcp-server --context ide-assistant --project /workspace"
|
||||
]
|
||||
}
|
||||
}
|
||||
13
superclaude/mcp/configs/serena.json
Normal file
13
superclaude/mcp/configs/serena.json
Normal file
@@ -0,0 +1,13 @@
|
||||
{
|
||||
"serena": {
|
||||
"command": "uvx",
|
||||
"args": [
|
||||
"--from",
|
||||
"git+https://github.com/oraios/serena",
|
||||
"serena",
|
||||
"start-mcp-server",
|
||||
"--context",
|
||||
"ide-assistant"
|
||||
]
|
||||
}
|
||||
}
|
||||
13
superclaude/mcp/configs/tavily.json
Normal file
13
superclaude/mcp/configs/tavily.json
Normal file
@@ -0,0 +1,13 @@
|
||||
{
|
||||
"tavily": {
|
||||
"command": "npx",
|
||||
"args": [
|
||||
"-y",
|
||||
"mcp-remote",
|
||||
"https://mcp.tavily.com/mcp/?tavilyApiKey=${TAVILY_API_KEY}"
|
||||
],
|
||||
"env": {
|
||||
"TAVILY_API_KEY": "${TAVILY_API_KEY}"
|
||||
}
|
||||
}
|
||||
}
|
||||
Reference in New Issue
Block a user