{ "vibe_check_mentor": { "title": "Senior Engineer Collaborative Reasoning", "description": "Interactive senior engineer mentor combining vibe-check pattern detection with collaborative reasoning. Multiple engineering personas analyze your technical decisions and provide structured feedback.", "features": [ "🧠 Multi-persona collaborative reasoning (Senior, Product, AI/ML Engineer perspectives)", "🎯 Automatic anti-pattern detection drives persona responses", "💬 Session continuity for multi-turn conversations", "📊 Structured insights with consensus and disagreements", "🎓 Educational coaching recommendations", "⚡ Interrupt mode for quick focused interventions" ], "modes": { "interrupt": "Quick focused intervention (<3 seconds) - single question/approval", "standard": "Normal collaborative reasoning with selected personas", "comprehensive": "Full analysis (legacy, same as reasoning_depth=comprehensive)" }, "reasoning_depths": { "quick": "Senior engineer perspective only", "standard": "Senior + Product engineer perspectives", "comprehensive": "All personas with full collaborative reasoning" }, "use_cases": [ "Should I build a custom auth system?", "Planning microservices architecture", "What's the best approach for API integration?", "Continue previous discussion about caching" ], "parameters": { "query": "Technical question or decision to discuss", "context": "Additional context (code, architecture, requirements)", "session_id": "Session ID to continue previous conversation", "reasoning_depth": "Analysis depth - quick/standard/comprehensive (default: standard)", "continue_session": "Whether to continue existing session (default: false)", "mode": "Interaction mode - interrupt/standard (default: standard)", "phase": "Development phase - planning/implementation/review (default: planning)", "confidence_threshold": "Minimum confidence to trigger interrupt (default: 0.7)", "file_paths": "Optional list of file paths to analyze (max 10 files, 1MB each)", "working_directory": "Optional working directory for resolving relative paths" }, "returns": "Collaborative reasoning analysis with multi-perspective insights or quick interrupt" }, "analyze_text_llm": { "title": "Deep Text Analysis using Claude CLI", "description": "Executes Claude CLI in a separate process to provide comprehensive LLM-powered analysis with full reasoning capabilities. For fast pattern detection without LLM calls, use analyze_text_nollm instead.", "features": [ "Full Claude reasoning capabilities", "Comprehensive anti-pattern detection", "Security analysis", "Code quality assessment" ], "parameters": { "content": "Text content to analyze", "task_type": "Type of analysis (general, pr_review, code_analysis, issue_analysis)", "additional_context": "Optional additional context for the analysis", "timeout_seconds": "Maximum time to wait for response", "model": "Claude model to use (sonnet, opus, haiku, or full model name)" }, "returns": "Comprehensive Claude CLI analysis results" }, "analyze_pr_llm": { "title": "Comprehensive PR Review using Claude CLI", "description": "Deep PR analysis with LLM-powered reasoning including anti-pattern detection, security analysis, and code quality assessment. For fast direct PR analysis, use analyze_pr_nollm instead.", "parameters": { "pr_diff": "The full diff content of the pull request", "pr_description": "Description/title of the pull request", "file_changes": "List of changed files for context", "timeout_seconds": "Maximum time to wait for analysis", "model": "Claude model to use" }, "returns": "Comprehensive Claude CLI PR review results" }, "analyze_code_llm": { "title": "Deep Code Analysis using Claude CLI", "description": "Comprehensive code analysis with LLM-powered reasoning for anti-pattern detection, security vulnerabilities, and maintainability.", "parameters": { "code_content": "The code to analyze", "file_path": "Optional file path for context", "language": "Programming language for specialized analysis", "timeout_seconds": "Maximum time to wait for analysis", "model": "Claude model to use" }, "returns": "Detailed Claude CLI code analysis results" }, "analyze_issue_llm": { "title": "Deep GitHub Issue Analysis using Claude CLI", "description": "Comprehensive issue analysis with LLM-powered reasoning for anti-pattern prevention, requirements quality, and implementation guidance. For fast direct issue analysis, use analyze_issue_nollm instead.", "parameters": { "issue_content": "The issue body/content", "issue_title": "Title of the issue", "issue_labels": "List of issue labels for context", "timeout_seconds": "Maximum time to wait for analysis", "model": "Claude model to use" }, "returns": "Comprehensive Claude CLI issue analysis with anti-pattern prevention guidance" }, "analyze_github_issue_llm": { "title": "Comprehensive GitHub Issue Vibe Check", "description": "Fetches the GitHub issue, analyzes it for anti-patterns and engineering guidance using Claude CLI, and optionally posts a friendly coaching comment. For fast direct issue analysis, use analyze_issue_nollm instead.", "important": "When this tool returns a comment_url or user_message field, ALWAYS include the full GitHub URL in your response", "parameters": { "issue_number": "GitHub issue number to analyze", "repository": "Repository in format owner/repo (default: kesslerio/vibe-check-mcp)", "post_comment": "Whether to post analysis as GitHub comment (default: True)", "analysis_mode": "quick or comprehensive analysis (default: comprehensive)", "detail_level": "Educational detail level - brief/standard/comprehensive (default: standard)", "timeout_seconds": "Maximum time to wait for analysis (default: 90)", "model": "Claude model to use" }, "returns": "Comprehensive Claude CLI vibe check analysis with GitHub integration" }, "analyze_github_pr_llm": { "title": "Comprehensive GitHub PR Vibe Check", "description": "Fetches the GitHub PR, analyzes it for anti-patterns and engineering guidance using Claude CLI, and optionally posts a friendly coaching review.", "parameters": { "pr_number": "GitHub PR number to analyze", "repository": "Repository in format owner/repo", "post_comment": "Whether to post analysis as GitHub review", "analysis_mode": "quick or comprehensive analysis", "detail_level": "Educational detail level", "timeout_seconds": "Maximum time to wait for analysis", "model": "Claude model to use" }, "returns": "Comprehensive Claude CLI vibe check analysis with GitHub integration" }, "analyze_text_nollm": { "title": "Fast Text Analysis with Pattern Detection", "description": "Direct pattern detection and anti-pattern analysis without LLM reasoning, enhanced with project-specific context and library awareness. Perfect for quick vibe checks and development workflow.", "features": [ "🚀 Fast pattern detection on any content", "🎯 Direct analysis without LLM dependencies", "🤝 Basic coaching recommendations", "📊 Pattern detection with confidence scoring", "🔍 Project-aware analysis with library context", "📚 Pattern exceptions and contextual recommendations" ], "use_cases": [ "Quick vibe check this text", "Fast pattern analysis", "Basic text check" ], "parameters": { "text": "Text content to analyze for anti-patterns", "detail_level": "Educational detail level (brief/standard/comprehensive)", "use_project_context": "Whether to automatically load project context (default: true)", "project_root": "Root directory for project context loading (default: current directory)" }, "returns": "Fast pattern detection analysis results with contextual recommendations" }, "demo_large_prompt_handling": { "title": "Demo: Zen-style Large Prompt Handling", "description": "Demonstrates the simple approach for handling prompts that exceed MCP's 25K token limit. No complex infrastructure needed!", "how_it_works": [ "Check if content >50K characters", "Ask Claude to save to file and resubmit", "Claude handles the file operations automatically", "Process the content normally" ], "parameters": { "content": "The content to analyze (if >50K chars, will request file mode)", "files": "Optional list of file paths (when Claude resubmits with files)", "detail_level": "Analysis detail level" }, "returns": "Either analysis results or instructions to use file mode" }, "check_integration_alternatives": { "title": "Official Alternative Check for Integration Decisions", "description": "Validates integration approaches against official alternatives to prevent unnecessary custom development. Based on real-world case studies.", "features": [ "🔍 Official alternative detection", "⚠️ Red flag identification for anti-patterns", "📋 Decision framework generation", "🎯 Custom development justification requirements" ], "use_cases": [ "Check cognee integration", "Validate docker approach", "Integration decision" ], "parameters": { "technology": "Technology being integrated (e.g., cognee, supabase, claude)", "custom_features": "Comma-separated list of features being custom developed", "description": "Optional description of the integration context" }, "returns": "Integration recommendation with research requirements and next steps" }, "analyze_integration_decision_text": { "title": "Analyze Text for Integration Decision Anti-patterns", "description": "Scans text content for integration patterns and provides recommendations to prevent custom development when official alternatives exist. Detects technologies and custom development indicators automatically.", "features": [ "🔍 Technology detection in text", "⚠️ Custom development pattern identification", "📋 Automatic recommendation generation", "🎯 Integration decision guidance" ], "use_cases": [ "Analyze this integration plan", "Check for integration anti-patterns" ], "parameters": { "text": "Text content to analyze for integration patterns", "detail_level": "Educational detail level (brief/standard/comprehensive)" }, "returns": "Analysis of detected technologies and integration recommendations" } }