๐ Universal Workflows for Software Development Optimization โ
Complete workflows for every development scenario using MCP ADR Analysis Server
This guide provides comprehensive, step-by-step workflows that can be used in any IDE environment to optimize software development using all 31+ tools available in the MCP ADR Analysis Server.
๐ Workflow Index โ
๐ฏ Quick Start Workflows (5-15 minutes) โ
๐๏ธ Core Project Workflows (30-60 minutes) โ
- New Project Setup
- Existing Project Analysis
- PRD to Implementation
- TDD to Deployment Workflow
- Continuous Health Monitoring Loop
๐ Specialized Workflows (60-120 minutes) โ
- Security & Compliance Audit
- Legacy Modernization
- Architecture Review & Documentation
- Research New Features and Update ADRs
- Automated Lint Resolution & CI Integration
- GitHub Actions Generation from Deployment Requirements
๐ Advanced Workflows (2+ hours) โ
โก Quick Start Workflows โ
Quick Project Health Check โ
Duration: 5-10 minutes | Goal: Immediate project insights
Step 1: Get Intelligent Workflow Guidance โ
Tool: get_workflow_guidance
Parameters: {
"goal": "quick project health assessment",
"projectContext": "existing_project",
"timeframe": "quick_analysis",
"primaryConcerns": ["maintainability", "security"]
}
Expected Output: Recommended tool sequence and priority areas
Step 2: Analyze Project Ecosystem โ
Tool: analyze_project_ecosystem
Parameters: {
"analysisDepth": "basic",
"enhancedMode": true,
"includeEnvironment": true
}
Expected Output: Technology stack, patterns, and immediate recommendations
Step 3: Quick Security Check โ
Tool: analyze_content_security
Parameters: {
"contentType": "general"
}
Expected Output: Sensitive data detection and immediate security concerns
Sophia Confidence Score: 90% - This workflow provides reliable first insights with minimal time investment.
Immediate Security Scan โ
Duration: 10-15 minutes | Goal: Comprehensive security assessment
Step 1: Content Security Analysis โ
Tool: analyze_content_security
Parameters: {
"contentType": "code",
"userDefinedPatterns": ["API_KEY", "PASSWORD", "SECRET"]
}
Step 2: Generate Content Masking โ
Tool: generate_content_masking
Parameters: {
"maskingStrategy": "full"
}
Step 3: Configure Custom Security Patterns โ
Tool: configure_custom_patterns
Parameters: {
"projectPath": "."
}
Verification: Use validate_content_masking
to ensure security measures are effective.
Deployment Readiness Check โ
Duration: 15-20 minutes | Goal: Human-guided zero-tolerance deployment validation with TODO integration
Step 1: Human Context Assessment โ
Interactive Checkpoint: Gather human perspective on deployment readiness
Human Feedback Prompts:
- "What's your confidence level for this deployment (1-10)?"
- "Are there any manual testing steps completed?"
- "Any known issues or concerns about this release?"
- "Is the team ready for deployment support?"
Step 2: Check Deployment Readiness with Human Input โ
Tool: deployment_readiness
Parameters: {
"operation": "check_readiness",
"strictMode": true,
"blockOnFailingTests": true,
"targetEnvironment": "production",
"integrateTodoTasks": true,
"updateHealthScoring": true
}
Step 3: Update TODO Tasks Based on Findings โ
Tool: manage_todo_json
Parameters: {
"operation": "get_tasks",
"filters": {
"tags": ["deployment", "blocker", "critical"],
"status": "pending"
},
"sortBy": "priority"
}
Step 4: Create Deployment Blocking Tasks (If Issues Found) โ
Tool: manage_todo_json
Parameters: {
"operation": "create_task",
"title": "Fix deployment blocker: [Issue Description]",
"priority": "critical",
"tags": ["deployment-blocker", "urgent"],
"dueDate": "[Today]"
}
Conditional: Only execute if deployment readiness check fails
Step 5: Update Health Scores Pre-Deployment โ
Tool: smart_score
Parameters: {
"operation": "sync_scores",
"projectPath": ".",
"todoPath": "TODO.md",
"triggerTools": ["manage_todo", "validate_rules"],
"rebalanceWeights": false
}
Step 6: Smart Git Push Validation (Human Approved) โ
Tool: smart_git_push
Parameters: {
"dryRun": true,
"testResults": {
"success": true,
"testsRun": 0,
"testsPassed": 0,
"testsFailed": 0
},
"checkDeploymentReadiness": true,
"targetEnvironment": "production"
}
Requirement: Human approval rating โฅ8/10 required before execution
Step 7: Post-Check Health Dashboard Update โ
Tool: smart_score
Parameters: {
"operation": "get_score_trends",
"projectPath": "."
}
Expected: Updated health trends showing deployment readiness progression
Human-Validated Success Criteria:
- โ Human confidence rating โฅ8/10
- โ Zero test failures
- โ No mock code in production
- โ Security validation passed
- โ No deployment blocking TODO tasks
- โ Manual testing completed
- โ Health scores reflect deployment readiness
Deployment Decision Matrix:
- ๐ข GREEN (Deploy): Human confidence โฅ8 + All automated checks pass + Health score โฅ80%
- ๐ก YELLOW (Review): Human confidence 6-7 + Minor issues identified + Health score 60-79%
- ๐ด RED (Block): Human confidence โค5 OR Critical issues found OR Health score <60%
๐๏ธ Core Project Workflows โ
New Project Setup โ
Duration: 30-45 minutes | Goal: Bootstrap complete architecture from requirements
Phase 1: Requirements Analysis (10 minutes) โ
Step 1: Workflow Guidance โ
Tool: get_workflow_guidance
Parameters: {
"goal": "new project architecture setup from PRD",
"projectContext": "new_project",
"availableAssets": ["PRD.md"],
"timeframe": "thorough_review"
}
Step 2: Generate ADRs from PRD โ
Tool: generate_adrs_from_prd
Parameters: {
"prdPath": "PRD.md",
"outputDirectory": "docs/adrs",
"enhancedMode": true,
"knowledgeEnhancement": true
}
Phase 2: Architecture Foundation (15 minutes) โ
Step 3: Analyze Project Ecosystem โ
Tool: analyze_project_ecosystem
Parameters: {
"analysisDepth": "comprehensive",
"enhancedMode": true,
"knowledgeEnhancement": true,
"learningEnabled": true
}
Step 4: Generate Implementation TODOs โ
Tool: generate_adr_todo
Parameters: {
"adrDirectory": "docs/adrs",
"todoPath": "TODO.md",
"phase": "both",
"includeRules": true
}
Phase 3: Development Guidance (15 minutes) โ
Step 5: Get Development Guidance โ
Tool: get_development_guidance
Parameters: {
"developmentPhase": "planning",
"adrsToImplement": [],
"technologyStack": [],
"teamContext": {
"size": "small_team",
"experienceLevel": "mixed"
}
}
Step 6: Generate Architectural Rules โ
Tool: generate_rules
Parameters: {
"adrDirectory": "docs/adrs",
"source": "adrs",
"outputFormat": "json"
}
Success Criteria: Complete ADR set, actionable TODO list, architectural rules established.
Existing Project Analysis โ
Duration: 45-60 minutes | Goal: Discover and document implicit architectural decisions
Phase 1: Discovery & Assessment (20 minutes) โ
Step 1: Discover Existing ADRs โ
Tool: discover_existing_adrs
Parameters: {
"adrDirectory": "docs/adrs",
"includeContent": true
}
Step 2: Comprehensive Ecosystem Analysis โ
Tool: analyze_project_ecosystem
Parameters: {
"analysisDepth": "comprehensive",
"recursiveDepth": "deep",
"enhancedMode": true,
"includeEnvironment": true
}
Phase 2: Gap Analysis (20 minutes) โ
Step 3: Suggest Missing ADRs โ
Tool: suggest_adrs
Parameters: {
"analysisType": "comprehensive",
"enhancedMode": true,
"learningEnabled": true,
"knowledgeEnhancement": true
}
Step 4: Generate Research Questions โ
Tool: generate_research_questions
Parameters: {
"analysisType": "comprehensive",
"adrDirectory": "docs/adrs"
}
Phase 3: Documentation & Action Planning (20 minutes) โ
Step 5: Generate TODO from ADRs โ
Tool: generate_adr_todo
Parameters: {
"adrDirectory": "docs/adrs",
"preserveExisting": true,
"linkAdrs": true,
"includeRules": true
}
Step 6: Compare Progress vs Reality โ
Tool: compare_adr_progress
Parameters: {
"adrDirectory": "docs/adrs",
"todoPath": "TODO.md",
"deepCodeAnalysis": true,
"functionalValidation": true,
"strictMode": true
}
Sophia Verification Framework: Compare discovered patterns against industry best practices. Confidence: 85% for implicit decision detection.
PRD to Implementation โ
Duration: 60 minutes | Goal: Transform requirements into actionable development plan
Phase 1: Requirements Processing (20 minutes) โ
Step 1: Get Workflow Guidance โ
Tool: get_workflow_guidance
Parameters: {
"goal": "convert PRD to complete implementation roadmap",
"projectContext": "new_project",
"availableAssets": ["PRD.md"],
"timeframe": "comprehensive_audit"
}
Step 2: Generate ADRs from PRD โ
Tool: generate_adrs_from_prd
Parameters: {
"prdPath": "PRD.md",
"prdType": "web-application",
"enhancedMode": true,
"knowledgeEnhancement": true,
"promptOptimization": true
}
Phase 2: Architecture Design (20 minutes) โ
Step 3: Ecosystem Analysis & Validation โ
Tool: analyze_project_ecosystem
Parameters: {
"analysisDepth": "comprehensive",
"technologyFocus": [],
"enhancedMode": true
}
Step 4: Generate Implementation Rules โ
Tool: generate_rules
Parameters: {
"adrDirectory": "docs/adrs",
"source": "both",
"outputFormat": "both"
}
Phase 3: Implementation Planning (20 minutes) โ
Step 5: Create Implementation TODOs โ
Tool: generate_adr_todo
Parameters: {
"adrDirectory": "docs/adrs",
"phase": "both",
"includeRules": true,
"linkAdrs": true
}
Step 6: Development Guidance โ
Tool: get_development_guidance
Parameters: {
"developmentPhase": "implementation",
"adrsToImplement": [],
"focusAreas": ["API design", "database schema", "testing strategy"]
}
Success Metrics: Complete architecture documentation, prioritized implementation roadmap, validated technology choices.
TDD to Deployment Workflow โ
Duration: 45-75 minutes | Goal: Complete test-driven development cycle with production deployment Confidence Level: 95% for established projects, 85% for new implementations
Phase 1: Test-Driven Foundation (25 minutes) โ
Step 1: Get TDD Development Guidance โ
Tool: get_development_guidance
Parameters: {
"developmentPhase": "planning",
"focusAreas": ["testing strategy", "TDD implementation", "deployment pipeline"],
"teamContext": {
"experienceLevel": "mixed",
"size": "small_team"
}
}
Sophia Note: Confidence 90% - Establishes systematic TDD approach with team-appropriate guidance
Step 2: Generate TDD-Focused TODO Tasks โ
Tool: generate_adr_todo
Parameters: {
"adrDirectory": "docs/adrs",
"phase": "test",
"includeRules": true,
"linkAdrs": true,
"preserveExisting": true
}
Expected Output: Test-first implementation tasks with clear acceptance criteria
Step 3: Create Rule Set for TDD Compliance โ
Tool: generate_rules
Parameters: {
"adrDirectory": "docs/adrs",
"source": "both",
"outputFormat": "json",
"existingRules": []
}
Phase 2: Test Implementation & Validation (25 minutes) โ
Step 4: Validate TDD Implementation Rules โ
Tool: validate_rules
Parameters: {
"reportFormat": "detailed",
"validationType": "function",
"rules": []
}
Sophia Verification: Check for test-first patterns, coverage thresholds, mock usage guidelines
Step 5: Monitor Implementation Progress โ
Tool: manage_todo_json
Parameters: {
"operation": "get_tasks",
"filters": {
"status": "in_progress",
"tags": ["testing", "tdd"],
"hasDeadline": false
},
"sortBy": "priority"
}
Step 6: Compare ADR Progress (Reality Check) โ
Tool: compare_adr_progress
Parameters: {
"todoPath": "TODO.md",
"adrDirectory": "docs/adrs",
"deepCodeAnalysis": true,
"functionalValidation": true,
"strictMode": true
}
Critical Check: Distinguish between mock and production code - Confidence threshold: โฅ85%
Phase 3: Deployment Readiness & Release (25 minutes) โ
Step 7: Human-Guided Deployment Readiness Assessment โ
Interactive Checkpoint: Human provides current project state assessment
Tool: get_workflow_guidance
Parameters: {
"goal": "assess deployment readiness with human feedback",
"projectContext": "existing_with_adrs",
"availableAssets": ["test suite", "codebase", "documentation"],
"primaryConcerns": ["deployment safety", "test coverage", "production readiness"],
"timeframe": "quick_analysis"
}
Human Feedback Prompts:
- "What's the current test coverage percentage?"
- "Are there any known failing tests or pending fixes?"
- "What deployment blockers are you aware of?"
- "Rate your confidence in production readiness (1-10)"
Step 8: Update TODO Tasks Based on Human Input โ
Tool: manage_todo_json
Parameters: {
"operation": "bulk_update",
"updates": {
"status": "in_progress",
"tags": ["deployment-readiness", "human-validated"],
"notes": "[Human feedback on current state]"
},
"filters": {
"tags": ["deployment", "testing", "production"],
"status": "pending"
}
}
Step 9: Comprehensive Deployment Readiness Check โ
Tool: deployment_readiness
Parameters: {
"operation": "full_audit",
"targetEnvironment": "production",
"strictMode": true,
"blockOnFailingTests": true,
"requireTestCoverage": 80,
"maxTestFailures": 0,
"allowMockCode": false,
"integrateTodoTasks": true,
"updateHealthScoring": true
}
Zero-Tolerance Policy: No failing tests, no mock code in production deployment
Step 10: Create Deployment Blocking Tasks (If Issues Found) โ
Tool: manage_todo_json
Parameters: {
"operation": "create_task",
"title": "Fix deployment blocker: [Issue Description]",
"description": "Critical issue preventing production deployment",
"priority": "critical",
"tags": ["deployment-blocker", "urgent", "production"],
"dueDate": "[Today + 1 day]",
"assignee": "[Team Lead]"
}
Conditional: Only execute if deployment readiness check fails
Step 11: Human Validation of Deployment Plan โ
Interactive Checkpoint: Human reviews and approves deployment
Human Validation Questions:
- "Review deployment readiness report - approve for production? (y/n)"
- "Any additional manual testing required before deployment?"
- "Confirm rollback plan is ready and tested?"
- "Are all stakeholders notified of deployment timing?"
Step 12: Smart Git Push with Test Validation โ
Tool: smart_git_push
Parameters: {
"message": "TDD Implementation: [Feature Name] - All tests passing, human-validated",
"testResults": {
"success": true,
"testsRun": 0,
"testsPassed": 0,
"testsFailed": 0,
"command": "npm test",
"duration": 0
},
"skipSecurity": false,
"dryRun": false
}
Note: Include actual test results from your IDE's test runner Requirement: Human approval required before execution
Step 13: Generate Deployment Guidance โ
Tool: generate_deployment_guidance
Parameters: {
"environment": "production",
"format": "all",
"includeRollback": true,
"includeValidation": true,
"generateFiles": true
}
Step 14: Update TODO Tasks Post-Deployment โ
Tool: manage_todo_json
Parameters: {
"operation": "bulk_update",
"updates": {
"status": "completed",
"notes": "Deployment successful - [timestamp and details]"
},
"filters": {
"tags": ["deployment-readiness", "production"],
"status": "in_progress"
}
}
Step 15: Update Project Health Scores Post-Deployment โ
Tool: smart_score
Parameters: {
"operation": "recalculate_scores",
"projectPath": ".",
"components": ["deployment_readiness", "task_completion", "code_quality"],
"forceUpdate": true,
"updateSources": true
}
Expected: Immediate health score update reflecting successful deployment
Step 16: Create Post-Deployment Monitoring Tasks with Health Integration โ
Tool: manage_todo_json
Parameters: {
"operation": "create_task",
"title": "Monitor production deployment: [Feature Name]",
"description": "24-hour monitoring of production deployment for stability and performance",
"priority": "high",
"tags": ["post-deployment", "monitoring", "production", "health-tracking"],
"dueDate": "[Today + 1 day]",
"assignee": "[DevOps Team]",
"linkedAdrs": ["deployment-related-adrs"],
"autoComplete": false,
"completionCriteria": "Production health metrics stable for 24 hours"
}
Step 17: Initialize Continuous Health Monitoring Loop โ
Tool: smart_score
Parameters: {
"operation": "sync_scores",
"projectPath": ".",
"todoPath": "TODO.md",
"triggerTools": ["manage_todo", "smart_git_push"],
"rebalanceWeights": true
}
Integration Note: This seamlessly transitions to the Continuous Health Monitoring Loop for ongoing project tracking
TDD Success Metrics:
- โ 100% test coverage for new features
- โ All tests passing before deployment
- โ Zero mock code in production
- โ Human validation and approval obtained
- โ Deployment blocking tasks resolved
- โ TODO tasks updated throughout process
- โ Automated deployment pipeline validated
- โ Rollback procedures documented
- โ Post-deployment monitoring tasks created
- โ Health scores updated post-deployment
- โ Continuous health monitoring activated
Sophia Human-LLM Confidence Framework:
- High Confidence (โฅ90%): Human approval + all automated checks pass โ Proceed with deployment
- Medium Confidence (70-89%): Human review required + additional validation โ Conditional deployment
- Low Confidence (<70%): Human oversight mandatory + TODO blocking tasks โ Stop deployment
Human Feedback Integration Points:
- Pre-Assessment (Step 7): Human provides current state context
- Deployment Plan Review (Step 11): Human validates deployment readiness
- Final Approval (Step 12): Human authorizes production deployment
- Post-Deployment (Step 15): Human confirms monitoring setup
TODO Lifecycle Management:
- Discovery: Identify deployment readiness tasks
- Tracking: Update task status based on human feedback
- Blocking: Create critical blocking tasks for deployment issues
- Completion: Mark deployment tasks as completed
- Monitoring: Create post-deployment follow-up tasks
๐ Specialized Workflows โ
Security & Compliance Audit โ
Duration: 60-90 minutes | Goal: Comprehensive security assessment and remediation
Phase 1: Security Discovery (30 minutes) โ
Step 1: Comprehensive Content Security Analysis โ
Tool: analyze_content_security
Parameters: {
"contentType": "code",
"userDefinedPatterns": [
"API_KEY", "SECRET_KEY", "PASSWORD", "TOKEN",
"DATABASE_URL", "PRIVATE_KEY", "AWS_ACCESS_KEY"
]
}
Step 2: Configure Project-Specific Security Patterns โ
Tool: configure_custom_patterns
Parameters: {
"projectPath": ".",
"existingPatterns": []
}
Step 3: Project Ecosystem Security Analysis โ
Tool: analyze_project_ecosystem
Parameters: {
"analysisScope": ["security"],
"analysisDepth": "comprehensive",
"enhancedMode": true
}
Phase 2: Security Implementation (30 minutes) โ
Step 4: Generate Content Masking Strategy โ
Tool: generate_content_masking
Parameters: {
"maskingStrategy": "environment",
"detectedItems": []
}
Step 5: Configure Output Masking โ
Tool: configure_output_masking
Parameters: {
"action": "set",
"enabled": true,
"strategy": "full"
}
Phase 3: Validation & Rules (30 minutes) โ
Step 6: Generate Security Rules โ
Tool: generate_rules
Parameters: {
"adrDirectory": "docs/adrs",
"source": "both",
"existingRules": []
}
Step 7: Validate Security Implementation โ
Tool: validate_content_masking
Parameters: {
"originalContent": "",
"maskedContent": ""
}
Step 8: Update Security TODOs โ
Tool: manage_todo_json
Parameters: {
"operation": "create_task",
"title": "Security Remediation",
"priority": "critical",
"tags": ["security", "compliance"]
}
Critical Security Verification: Zero exposed credentials, comprehensive masking, enforced security rules.
Legacy Modernization โ
Duration: 90-120 minutes | Goal: Systematic legacy system upgrade strategy
Phase 1: Legacy Analysis (40 minutes) โ
Step 1: Comprehensive Legacy Assessment โ
Tool: analyze_project_ecosystem
Parameters: {
"analysisDepth": "comprehensive",
"recursiveDepth": "comprehensive",
"enhancedMode": true,
"knowledgeEnhancement": true
}
Step 2: Discover Implicit Architectural Decisions โ
Tool: suggest_adrs
Parameters: {
"analysisType": "comprehensive",
"enhancedMode": true,
"learningEnabled": true
}
Step 3: Generate Modernization Research Questions โ
Tool: generate_research_questions
Parameters: {
"analysisType": "comprehensive",
"researchContext": {
"topic": "legacy modernization",
"scope": "architecture",
"objectives": ["performance", "maintainability", "scalability"]
}
}
Phase 2: Modernization Planning (40 minutes) โ
Step 4: Create Modernization ADRs โ
Tool: generate_adr_from_decision
Parameters: {
"decisionData": {
"title": "Legacy System Modernization Strategy",
"context": "Aging legacy system requires modernization",
"decision": "Incremental modernization approach",
"consequences": "Reduced technical debt, improved maintainability"
}
}
Step 5: Generate Migration Rules โ
Tool: generate_rules
Parameters: {
"adrDirectory": "docs/adrs",
"projectPath": ".",
"source": "both"
}
Step 6: Create Modernization Roadmap โ
Tool: generate_adr_todo
Parameters: {
"adrDirectory": "docs/adrs",
"phase": "both",
"includeRules": true,
"linkAdrs": true
}
Phase 3: Validation & Implementation (40 minutes) โ
Step 7: Environment Analysis for Migration โ
Tool: analyze_environment
Parameters: {
"analysisType": "comprehensive",
"adrDirectory": "docs/adrs"
}
Step 8: Deployment Readiness Assessment โ
Tool: deployment_readiness
Parameters: {
"operation": "full_audit",
"strictMode": true,
"targetEnvironment": "staging"
}
Step 9: Progress Validation โ
Tool: compare_adr_progress
Parameters: {
"adrDirectory": "docs/adrs",
"deepCodeAnalysis": true,
"strictMode": true,
"includeRuleValidation": true
}
Modernization Success Criteria: Documented migration strategy, risk assessment, phased implementation plan, validated deployment pipeline.
Architecture Review & Documentation โ
Duration: 90 minutes | Goal: Comprehensive architecture documentation and governance
Phase 1: Architecture Discovery (30 minutes) โ
Step 1: Get Architecture Context โ
Tool: get_architectural_context
Parameters: {
"includeCompliance": true,
"conversationContext": {
"userGoals": ["architecture documentation", "governance"],
"focusAreas": ["maintainability", "scalability"]
}
}
Step 2: Comprehensive Ecosystem Analysis โ
Tool: analyze_project_ecosystem
Parameters: {
"analysisDepth": "comprehensive",
"recursiveDepth": "comprehensive",
"enhancedMode": true,
"includeEnvironment": true
}
Phase 2: Documentation Generation (30 minutes) โ
Step 3: Suggest Architecture ADRs โ
Tool: suggest_adrs
Parameters: {
"analysisType": "comprehensive",
"enhancedMode": true,
"knowledgeEnhancement": true
}
Step 4: Generate Architecture Rules โ
Tool: generate_rules
Parameters: {
"adrDirectory": "docs/adrs",
"source": "both",
"outputFormat": "both"
}
Step 5: Create Rule Set โ
Tool: create_rule_set
Parameters: {
"name": "Architecture Governance Rules",
"outputFormat": "both"
}
Phase 3: Governance & Validation (30 minutes) โ
Step 6: Generate Research Questions โ
Tool: generate_research_questions
Parameters: {
"analysisType": "comprehensive",
"researchContext": {
"topic": "architecture governance",
"scope": "enterprise"
}
}
Step 7: Validate Architecture Rules โ
Tool: validate_rules
Parameters: {
"reportFormat": "detailed",
"validationType": "module"
}
Step 8: Create Architecture TODO โ
Tool: manage_todo_json
Parameters: {
"operation": "import_adr_tasks",
"adrDirectory": "docs/adrs",
"mergeStrategy": "merge"
}
Architecture Governance Success: Complete documentation, enforced rules, validated compliance, ongoing governance process.
Research New Features and Update ADRs โ
Duration: 90-120 minutes | Goal: Interactive research-driven feature development with human-LLM collaboration Confidence Level: 85% for well-defined research scope, 75% for exploratory research
Phase 1: Research Planning & Knowledge Discovery (30 minutes) โ
Step 1: Get Intelligent Research Guidance โ
Tool: get_workflow_guidance
Parameters: {
"goal": "research new features and update architectural decisions",
"projectContext": "existing_with_adrs",
"availableAssets": ["existing ADRs", "codebase", "documentation"],
"primaryConcerns": ["innovation", "architectural consistency", "technical feasibility"],
"timeframe": "thorough_review"
}
Sophia Note: Confidence 90% - Establishes systematic research methodology
Step 2: Generate Context-Aware Research Questions โ
Tool: generate_research_questions
Parameters: {
"analysisType": "comprehensive",
"adrDirectory": "docs/adrs",
"researchContext": {
"topic": "[FEATURE_NAME]",
"scope": "feature_development",
"objectives": ["technical feasibility", "architectural impact", "implementation strategy"],
"constraints": ["existing architecture", "performance requirements", "security standards"],
"timeline": "2-4 weeks"
}
}
Expected Output: Prioritized research questions with methodology and timelines
Step 3: Analyze Current Architecture Context โ
Tool: get_architectural_context
Parameters: {
"conversationContext": {
"userGoals": ["feature research", "ADR updates"],
"focusAreas": ["architecture", "performance", "maintainability"],
"projectPhase": "planning",
"humanRequest": "Research [FEATURE_NAME] and update ADRs based on findings"
}
}
Phase 2: Interactive Research & Documentation (45 minutes) โ
Step 4: Deep Research with Human Feedback Loop โ
Tool: research_mode
Parameters: {
"topic": "[FEATURE_NAME] implementation options and architectural implications",
"currentState": "Initial research phase - analyzing implementation approaches",
"nextSteps": "Compare technology options, validate architectural fit, gather performance data",
"previousState": ""
}
Interactive Process:
- LLM conducts initial research
- Human reviews findings and provides domain expertise
- LLM incorporates feedback and refines research
- Iterate until confidence โฅ85%
Step 5: Create Research Documentation Template โ
Tool: create_research_template
Parameters: {
"title": "[FEATURE_NAME] Research Findings",
"category": "feature_analysis",
"researchPath": "docs/research"
}
Step 6: Web-Based Research Enhancement โ
Tool: firecrawl_deep_research
Parameters: {
"query": "[FEATURE_NAME] best practices, implementation patterns, architectural considerations",
"maxDepth": 3,
"maxUrls": 20,
"timeLimit": 180
}
Verification Step: Cross-reference findings with existing architectural decisions
Phase 3: ADR Integration & Validation (45 minutes) โ
Step 7: Suggest Architecture ADRs from Research โ
Tool: suggest_adrs
Parameters: {
"analysisType": "comprehensive",
"enhancedMode": true,
"knowledgeEnhancement": true,
"learningEnabled": true,
"conversationContext": {
"userGoals": ["document new feature decisions"],
"focusAreas": ["architecture", "performance", "security"],
"humanRequest": "Create ADRs based on [FEATURE_NAME] research findings"
}
}
Step 8: Human-LLM Collaborative ADR Review โ
Interactive Process:
- LLM generates draft ADRs based on research
- Human reviews and provides architectural expertise
- LLM incorporates feedback and refines ADRs
- Validate against existing architecture using:
Tool: compare_adr_progress
Parameters: {
"adrDirectory": "docs/adrs",
"strictMode": true,
"functionalValidation": true,
"includeRuleValidation": true
}
Step 9: Generate ADR from Final Decision โ
Tool: generate_adr_from_decision
Parameters: {
"decisionData": {
"title": "[FEATURE_NAME] Implementation Decision",
"context": "[Research context and problem statement]",
"decision": "[Final architectural decision]",
"alternatives": ["[Alternative approaches considered]"],
"consequences": "[Expected outcomes and trade-offs]",
"evidence": ["[Research findings and supporting data]"]
},
"templateFormat": "nygard",
"existingAdrs": []
}
Step 10: Incorporate Research Findings into ADRs โ
Tool: incorporate_research
Parameters: {
"analysisType": "generate_updates",
"adrDirectory": "docs/adrs",
"researchPath": "docs/research",
"researchFindings": [
{
"finding": "[Key research insight]",
"impact": "[Architectural impact]",
"evidence": ["[Supporting documentation]"]
}
],
"updateType": "content"
}
Step 11: Create Implementation TODO from Research โ
Tool: manage_todo_json
Parameters: {
"operation": "create_task",
"title": "Implement [FEATURE_NAME] based on research findings",
"description": "Implementation task derived from research and ADR decisions",
"priority": "high",
"tags": ["research-driven", "feature-development", "adr-based"],
"linkedAdrs": ["[Generated ADR files]"],
"intentId": "[Research intent ID]"
}
Step 12: Final Validation & Knowledge Graph Integration โ
Tool: manage_todo_json
Parameters: {
"operation": "sync_knowledge_graph",
"direction": "bidirectional",
"intentId": "[Research intent ID]"
}
Research Success Metrics:
- โ Comprehensive research questions answered (โฅ90% coverage)
- โ Human-LLM collaboration confidence score โฅ85%
- โ ADRs updated with research findings and evidence
- โ Implementation tasks created with clear acceptance criteria
- โ Knowledge graph updated with research insights
- โ Research documentation created for future reference
Sophia Interactive Confidence Framework:
- Research Quality Gate: โฅ85% confidence before proceeding to ADR updates
- Human Feedback Integration: Required for domain-specific decisions
- Systematic Verification: Cross-validation against existing architecture
- Explicit Limitations: Acknowledge research scope boundaries
Human-LLM Collaboration Checkpoints:
- Research Direction Validation (Step 4): Human confirms research scope and priorities
- Technical Feasibility Review (Step 8): Human validates architectural implications
- Final Decision Approval (Step 9): Human approves ADR content before generation
Automated Lint Resolution & CI Integration โ
Duration: 45-75 minutes | Goal: Generate automated lint fix scripts and GitHub Actions for any environment Confidence Level: 95% for script generation, 90% for environment-specific customization
Phase 1: Environment & Linting Tool Detection (15 minutes) โ
Step 1: Analyze Project Ecosystem for Linting Tools โ
Tool: analyze_project_ecosystem
Parameters: {
"analysisDepth": "comprehensive",
"analysisScope": ["dependencies", "tools", "code_quality"],
"includeEnvironment": true,
"conversationContext": {
"userGoals": ["automated lint resolution", "ci/cd integration"],
"projectPhase": "development",
"focusAreas": ["code quality", "automation"]
}
}
Expected Output: Detection of ESLint, Prettier, Pylint, RuboCop, Clippy, etc.
Step 2: Generate Code Quality Rules Based on Project โ
Tool: generate_rules
Parameters: {
"adrDirectory": "docs/adrs",
"source": "patterns",
"outputFormat": "json",
"projectPath": "."
}
Step 3: Create Baseline TODO Tasks for Lint Resolution โ
Tool: manage_todo_json
Parameters: {
"operation": "create_task",
"title": "Setup automated lint resolution pipeline",
"description": "Establish automated scripts and CI integration for lint fixes",
"priority": "high",
"tags": ["automation", "code-quality", "ci-cd", "lint-resolution"],
"dueDate": "[Today + 3 days]"
}
Phase 2: Script Generation for Lint Fixes (25 minutes) โ
Step 4: Human Input for Environment Preferences โ
Interactive Checkpoint: Gather human preferences for lint resolution
Human Feedback Prompts:
- "Which linting tools should be prioritized? (ESLint, Prettier, Pylint, etc.)"
- "What environments do you deploy to? (Node.js, Python, Ruby, Go, etc.)"
- "Should lint fixes be auto-committed or create PRs? (auto-commit/pr-creation)"
- "Any specific lint rules that should be excluded from auto-fix?"
Step 5: Generate Environment-Specific Lint Fix Scripts โ
Tool: write_file
Parameters: {
"path": "scripts/auto-lint-fix.sh",
"content": "#!/bin/bash\n# Auto-generated lint resolution script\n# Environment: [Detected from Step 1]\n# Tools: [From human input]\n\nset -e\n\necho \"๐ง Starting automated lint resolution...\"\n\n# Detect project type and run appropriate linters\nif [ -f \"package.json\" ]; then\n echo \"๐ฆ Node.js project detected\"\n if [ -f \".eslintrc.js\" ] || [ -f \".eslintrc.json\" ]; then\n echo \"๐ Running ESLint fixes...\"\n npx eslint . --fix --ext .js,.jsx,.ts,.tsx\n fi\n if [ -f \".prettierrc\" ] || [ -f \"prettier.config.js\" ]; then\n echo \"โจ Running Prettier fixes...\"\n npx prettier --write .\n fi\nfi\n\nif [ -f \"requirements.txt\" ] || [ -f \"setup.py\" ] || [ -f \"pyproject.toml\" ]; then\n echo \"๐ Python project detected\"\n if command -v black &> /dev/null; then\n echo \"โซ Running Black formatter...\"\n black .\n fi\n if command -v isort &> /dev/null; then\n echo \"๐ Running isort...\"\n isort .\n fi\n if command -v flake8 &> /dev/null; then\n echo \"๐ Running flake8 checks...\"\n flake8 . --count --select=E9,F63,F7,F82 --show-source --statistics\n fi\nfi\n\nif [ -f \"Gemfile\" ]; then\n echo \"๐ Ruby project detected\"\n if command -v rubocop &> /dev/null; then\n echo \"๐ฎ Running RuboCop fixes...\"\n rubocop -A\n fi\nfi\n\nif [ -f \"go.mod\" ]; then\n echo \"๐ Go project detected\"\n echo \"๐ง Running go fmt...\"\n go fmt ./...\n if command -v golint &> /dev/null; then\n echo \"๐ Running golint...\"\n golint ./...\n fi\nfi\n\nif [ -f \"Cargo.toml\" ]; then\n echo \"๐ฆ Rust project detected\"\n echo \"๐ง Running cargo fmt...\"\n cargo fmt\n echo \"๐ Running clippy fixes...\"\n cargo clippy --fix --allow-dirty\nfi\n\necho \"โ
Lint resolution completed!\"\n\n# Update health scores\necho \"๐ Updating project health scores...\"\n# This would integrate with MCP tools if available in CI environment\n\necho \"๐ Automated lint resolution finished successfully!\""
}
Step 6: Generate PowerShell Script for Windows Environments โ
Tool: write_file
Parameters: {
"path": "scripts/auto-lint-fix.ps1",
"content": "# Auto-generated PowerShell lint resolution script\n# Environment: Cross-platform Windows support\n\nWrite-Host \"๐ง Starting automated lint resolution...\" -ForegroundColor Green\n\ntry {\n # Node.js projects\n if (Test-Path \"package.json\") {\n Write-Host \"๐ฆ Node.js project detected\" -ForegroundColor Yellow\n \n if ((Test-Path \".eslintrc.js\") -or (Test-Path \".eslintrc.json\")) {\n Write-Host \"๐ Running ESLint fixes...\" -ForegroundColor Cyan\n npx eslint . --fix --ext .js,.jsx,.ts,.tsx\n }\n \n if ((Test-Path \".prettierrc\") -or (Test-Path \"prettier.config.js\")) {\n Write-Host \"โจ Running Prettier fixes...\" -ForegroundColor Cyan\n npx prettier --write .\n }\n }\n \n # Python projects\n if ((Test-Path \"requirements.txt\") -or (Test-Path \"setup.py\") -or (Test-Path \"pyproject.toml\")) {\n Write-Host \"๐ Python project detected\" -ForegroundColor Yellow\n \n if (Get-Command black -ErrorAction SilentlyContinue) {\n Write-Host \"โซ Running Black formatter...\" -ForegroundColor Cyan\n black .\n }\n \n if (Get-Command isort -ErrorAction SilentlyContinue) {\n Write-Host \"๐ Running isort...\" -ForegroundColor Cyan\n isort .\n }\n }\n \n # Additional language support can be added here\n \n Write-Host \"โ
Lint resolution completed!\" -ForegroundColor Green\n \n} catch {\n Write-Host \"โ Error during lint resolution: $($_.Exception.Message)\" -ForegroundColor Red\n exit 1\n}"
}
Step 7: Create Language-Specific Configuration Templates โ
Tool: write_file
Parameters: {
"path": "scripts/lint-configs/.eslintrc.template.json",
"content": "{\n \"extends\": [\n \"eslint:recommended\",\n \"@typescript-eslint/recommended\"\n ],\n \"parser\": \"@typescript-eslint/parser\",\n \"plugins\": [\"@typescript-eslint\"],\n \"rules\": {\n \"no-console\": \"warn\",\n \"no-unused-vars\": \"error\",\n \"prefer-const\": \"error\",\n \"no-var\": \"error\",\n \"object-shorthand\": \"error\",\n \"prefer-template\": \"error\"\n },\n \"env\": {\n \"node\": true,\n \"browser\": true,\n \"es2022\": true\n }\n}"
}
Phase 3: GitHub Actions Workflow Generation (25 minutes) โ
Step 8: Generate Main Lint Resolution GitHub Action โ
Tool: write_file
Parameters: {
"path": ".github/workflows/auto-lint-resolution.yml",
"content": "name: ๐ง Automated Lint Resolution\n\non:\n push:\n branches: [ main, develop ]\n pull_request:\n branches: [ main ]\n schedule:\n # Run daily at 2 AM UTC\n - cron: '0 2 * * *'\n workflow_dispatch:\n inputs:\n force_fix:\n description: 'Force lint fixes even with conflicts'\n required: false\n default: 'false'\n type: boolean\n\njobs:\n lint-resolution:\n runs-on: ubuntu-latest\n \n strategy:\n matrix:\n # Support multiple environments\n include:\n - name: \"Node.js\"\n setup: \"node\"\n version: \"18\"\n - name: \"Python\"\n setup: \"python\"\n version: \"3.11\"\n \n steps:\n - name: ๐ฅ Checkout repository\n uses: actions/checkout@v4\n with:\n token: ${{ secrets.GITHUB_TOKEN }}\n fetch-depth: 0\n \n - name: ๐ง Setup ${{ matrix.name }} ${{ matrix.version }}\n if: matrix.setup == 'node'\n uses: actions/setup-node@v4\n with:\n node-version: ${{ matrix.version }}\n cache: 'npm'\n \n - name: ๐ Setup Python ${{ matrix.version }}\n if: matrix.setup == 'python'\n uses: actions/setup-python@v4\n with:\n python-version: ${{ matrix.version }}\n \n - name: ๐ฆ Install Node.js dependencies\n if: matrix.setup == 'node' && hashFiles('package.json') != ''\n run: |\n if [ -f \"package-lock.json\" ]; then\n npm ci\n elif [ -f \"yarn.lock\" ]; then\n yarn install --frozen-lockfile\n else\n npm install\n fi\n \n - name: ๐ฆ Install Python dependencies\n if: matrix.setup == 'python' && hashFiles('requirements.txt') != ''\n run: |\n python -m pip install --upgrade pip\n if [ -f \"requirements.txt\" ]; then\n pip install -r requirements.txt\n fi\n pip install black isort flake8 pylint\n \n - name: ๐ Run pre-lint health check\n run: |\n echo \"๐ Project health before lint resolution:\"\n # This would integrate with MCP tools if available\n echo \"Starting lint resolution process...\"\n \n - name: ๐ง Execute automated lint fixes\n run: |\n chmod +x scripts/auto-lint-fix.sh\n ./scripts/auto-lint-fix.sh\n \n - name: ๐ Generate lint resolution report\n run: |\n echo \"# ๐ง Lint Resolution Report\" > lint-report.md\n echo \"## Summary\" >> lint-report.md\n echo \"- **Timestamp**: $(date)\" >> lint-report.md\n echo \"- **Environment**: ${{ matrix.name }} ${{ matrix.version }}\" >> lint-report.md\n \n # Check for changes\n if git diff --quiet; then\n echo \"- **Status**: โ
No lint issues found\" >> lint-report.md\n else\n echo \"- **Status**: ๐ง Lint fixes applied\" >> lint-report.md\n echo \"## Changes Made\" >> lint-report.md\n git diff --stat >> lint-report.md\n fi\n \n - name: ๐ค Commit lint fixes\n if: success()\n run: |\n git config --local user.email \"action@github.com\"\n git config --local user.name \"GitHub Action - Lint Resolution\"\n \n if ! git diff --quiet; then\n git add .\n git commit -m \"๐ง Auto-fix lint issues [skip ci]\n \n - Applied automated lint fixes\n - Environment: ${{ matrix.name }} ${{ matrix.version }}\n - Triggered by: ${{ github.event_name }}\n - Timestamp: $(date)\"\n \n git push\n echo \"โ
Lint fixes committed and pushed\"\n else\n echo \"โ
No lint issues found - no changes needed\"\n fi\n \n - name: ๐ Upload lint report\n if: always()\n uses: actions/upload-artifact@v3\n with:\n name: lint-resolution-report-${{ matrix.name }}\n path: lint-report.md\n \n - name: ๐ Update project health metrics\n if: success()\n run: |\n echo \"๐ Updating project health scores after lint resolution\"\n # This would integrate with MCP health monitoring if available\n echo \"Lint resolution completed successfully!\""
}
Step 9: Generate Pull Request Lint Check Action โ
Tool: write_file
Parameters: {
"path": ".github/workflows/pr-lint-check.yml",
"content": "name: ๐ PR Lint Quality Check\n\non:\n pull_request:\n types: [opened, synchronize, reopened]\n\njobs:\n lint-check:\n runs-on: ubuntu-latest\n \n steps:\n - name: ๐ฅ Checkout PR\n uses: actions/checkout@v4\n with:\n fetch-depth: 0\n \n - name: ๐ง Setup Node.js\n if: hashFiles('package.json') != ''\n uses: actions/setup-node@v4\n with:\n node-version: '18'\n cache: 'npm'\n \n - name: ๐ฆ Install dependencies\n if: hashFiles('package.json') != ''\n run: npm ci\n \n - name: ๐ Run lint checks (report only)\n run: |\n echo \"๐ Running lint quality assessment...\"\n \n # Initialize counters\n TOTAL_ISSUES=0\n FIXABLE_ISSUES=0\n \n # Node.js/TypeScript linting\n if [ -f \"package.json\" ] && ([ -f \".eslintrc.js\" ] || [ -f \".eslintrc.json\" ]); then\n echo \"๐ฆ Checking ESLint issues...\"\n ESLINT_ISSUES=$(npx eslint . --format=json --ext .js,.jsx,.ts,.tsx | jq '[.[] | .messages | length] | add // 0')\n ESLINT_FIXABLE=$(npx eslint . --format=json --ext .js,.jsx,.ts,.tsx | jq '[.[] | .messages[] | select(.fix != null)] | length')\n \n TOTAL_ISSUES=$((TOTAL_ISSUES + ESLINT_ISSUES))\n FIXABLE_ISSUES=$((FIXABLE_ISSUES + ESLINT_FIXABLE))\n \n echo \" - Total ESLint issues: $ESLINT_ISSUES\"\n echo \" - Auto-fixable: $ESLINT_FIXABLE\"\n fi\n \n # Generate PR comment\n echo \"# ๐ Lint Quality Report\" > pr-comment.md\n echo \"\" >> pr-comment.md\n echo \"## Summary\" >> pr-comment.md\n echo \"- **Total Issues**: $TOTAL_ISSUES\" >> pr-comment.md\n echo \"- **Auto-Fixable**: $FIXABLE_ISSUES\" >> pr-comment.md\n echo \"- **Manual Review Required**: $((TOTAL_ISSUES - FIXABLE_ISSUES))\" >> pr-comment.md\n echo \"\" >> pr-comment.md\n \n if [ $TOTAL_ISSUES -eq 0 ]; then\n echo \"โ
**No lint issues found!** This PR is ready for review.\" >> pr-comment.md\n elif [ $FIXABLE_ISSUES -eq $TOTAL_ISSUES ]; then\n echo \"๐ง **All issues are auto-fixable!** The automated lint resolution workflow will fix these.\" >> pr-comment.md\n else\n echo \"โ ๏ธ **Manual review required** for some lint issues.\" >> pr-comment.md\n fi\n \n echo \"\" >> pr-comment.md\n echo \"---\" >> pr-comment.md\n echo \"*Generated by automated lint quality check*\" >> pr-comment.md\n \n - name: ๐ Comment on PR\n uses: actions/github-script@v7\n with:\n script: |\n const fs = require('fs');\n const comment = fs.readFileSync('pr-comment.md', 'utf8');\n \n github.rest.issues.createComment({\n issue_number: context.issue.number,\n owner: context.repo.owner,\n repo: context.repo.repo,\n body: comment\n });"
}
Step 10: Update TODO Tasks with Generated Automation โ
Tool: manage_todo_json
Parameters: {
"operation": "bulk_update",
"updates": {
"status": "completed",
"notes": "Automated lint resolution scripts and GitHub Actions generated successfully"
},
"filters": {
"tags": ["automation", "lint-resolution"],
"status": "pending"
}
}
Step 11: Update Health Scores with Automation Integration โ
Tool: smart_score
Parameters: {
"operation": "recalculate_scores",
"projectPath": ".",
"components": ["code_quality", "deployment_readiness"],
"forceUpdate": true,
"updateSources": true
}
Lint Resolution Success Criteria:
- โ Environment-specific scripts generated for all detected languages
- โ GitHub Actions workflows created for automated execution
- โ Cross-platform support (Linux, macOS, Windows)
- โ PR quality checks implemented
- โ Health monitoring integration active
- โ Human preferences incorporated into automation
- โ Error handling and reporting included
GitHub Actions Generation from Deployment Requirements โ
Duration: 60-90 minutes | Goal: Generate complete CI/CD pipelines based on project ADRs and deployment requirements Confidence Level: 92% for standard deployments, 85% for complex enterprise environments
Phase 1: Deployment Requirements Analysis (20 minutes) โ
Step 1: Analyze ADRs for Deployment Architecture โ
Tool: analyze_project_ecosystem
Parameters: {
"analysisDepth": "comprehensive",
"analysisScope": ["architecture", "dependencies", "deployment"],
"includeEnvironment": true,
"conversationContext": {
"userGoals": ["ci/cd automation", "deployment pipeline"],
"projectPhase": "deployment",
"focusAreas": ["deployment", "automation", "infrastructure"]
}
}
Step 2: Generate Deployment Guidance Analysis โ
Tool: generate_deployment_guidance
Parameters: {
"adrDirectory": "docs/adrs",
"environment": "all",
"format": "structured",
"includeConfigs": true,
"includeScripts": true,
"includeValidation": true,
"includeRollback": true
}
Step 3: Human Input for Deployment Preferences โ
Interactive Checkpoint: Gather deployment requirements and preferences
Human Feedback Prompts:
- "What deployment environments do you need? (staging, production, preview, etc.)"
- "Which cloud providers? (AWS, Azure, GCP, Vercel, Netlify, self-hosted)"
- "What testing levels are required? (unit, integration, e2e, security, performance)"
- "Any compliance requirements? (SOC2, GDPR, HIPAA, etc.)"
- "Deployment frequency preferences? (continuous, daily, manual approval)"
- "Rollback strategy preferences? (blue-green, canary, rolling)"
Step 4: Create Deployment Pipeline TODO Tasks โ
Tool: manage_todo_json
Parameters: {
"operation": "create_task",
"title": "Implement CI/CD pipeline based on deployment requirements",
"description": "Generate and configure GitHub Actions workflows for complete deployment automation",
"priority": "high",
"tags": ["ci-cd", "deployment", "automation", "infrastructure"],
"dueDate": "[Today + 5 days]"
}
Phase 2: CI/CD Pipeline Generation (35 minutes) โ
Step 5: Generate Main CI/CD Pipeline Workflow โ
Tool: write_file
Parameters: {
"path": ".github/workflows/ci-cd-pipeline.yml",
"content": "name: ๐ CI/CD Pipeline\n\non:\n push:\n branches: [ main, develop ]\n pull_request:\n branches: [ main ]\n release:\n types: [ published ]\n workflow_dispatch:\n inputs:\n environment:\n description: 'Deployment environment'\n required: true\n default: 'staging'\n type: choice\n options:\n - staging\n - production\n skip_tests:\n description: 'Skip test execution'\n required: false\n default: false\n type: boolean\n\nenv:\n NODE_VERSION: '18'\n PYTHON_VERSION: '3.11'\n # Add other environment variables based on analysis\n\njobs:\n # ==========================================\n # QUALITY ASSURANCE JOBS\n # ==========================================\n \n code-quality:\n name: ๐ Code Quality & Security\n runs-on: ubuntu-latest\n \n steps:\n - name: ๐ฅ Checkout code\n uses: actions/checkout@v4\n with:\n fetch-depth: 0\n \n - name: ๐ง Setup environment\n uses: actions/setup-node@v4\n if: hashFiles('package.json') != ''\n with:\n node-version: ${{ env.NODE_VERSION }}\n cache: 'npm'\n \n - name: ๐ฆ Install dependencies\n if: hashFiles('package.json') != ''\n run: |\n if [ -f \"package-lock.json\" ]; then\n npm ci\n elif [ -f \"yarn.lock\" ]; then\n yarn install --frozen-lockfile\n else\n npm install\n fi\n \n - name: ๐ Run lint checks\n if: hashFiles('package.json') != ''\n run: |\n if [ -f \".eslintrc.js\" ] || [ -f \".eslintrc.json\" ]; then\n npm run lint || npx eslint . --ext .js,.jsx,.ts,.tsx\n fi\n \n - name: ๐ Security audit\n if: hashFiles('package.json') != ''\n run: |\n npm audit --audit-level=high\n # Additional security scanning based on requirements\n \n - name: ๐ Code coverage\n if: hashFiles('package.json') != ''\n run: |\n if grep -q '\"test\"' package.json; then\n npm run test:coverage || npm test -- --coverage\n fi\n \n outputs:\n quality-passed: ${{ success() }}\n \n unit-tests:\n name: ๐งช Unit Tests\n runs-on: ubuntu-latest\n if: github.event.inputs.skip_tests != 'true'\n \n strategy:\n matrix:\n # Multi-environment testing based on project analysis\n node-version: [16, 18, 20]\n \n steps:\n - name: ๐ฅ Checkout code\n uses: actions/checkout@v4\n \n - name: ๐ง Setup Node.js ${{ matrix.node-version }}\n if: hashFiles('package.json') != ''\n uses: actions/setup-node@v4\n with:\n node-version: ${{ matrix.node-version }}\n cache: 'npm'\n \n - name: ๐ฆ Install dependencies\n if: hashFiles('package.json') != ''\n run: npm ci\n \n - name: ๐งช Run unit tests\n if: hashFiles('package.json') != ''\n run: |\n if grep -q '\"test\"' package.json; then\n npm test\n else\n echo \"No test script found in package.json\"\n fi\n \n outputs:\n tests-passed: ${{ success() }}\n \n integration-tests:\n name: ๐ Integration Tests\n runs-on: ubuntu-latest\n needs: [unit-tests]\n if: needs.unit-tests.outputs.tests-passed == 'true'\n \n services:\n postgres:\n image: postgres:15\n env:\n POSTGRES_PASSWORD: postgres\n POSTGRES_DB: test_db\n options: >-\n --health-cmd pg_isready\n --health-interval 10s\n --health-timeout 5s\n --health-retries 5\n ports:\n - 5432:5432\n \n redis:\n image: redis:7\n options: >-\n --health-cmd \"redis-cli ping\"\n --health-interval 10s\n --health-timeout 5s\n --health-retries 5\n ports:\n - 6379:6379\n \n steps:\n - name: ๐ฅ Checkout code\n uses: actions/checkout@v4\n \n - name: ๐ง Setup environment\n uses: actions/setup-node@v4\n if: hashFiles('package.json') != ''\n with:\n node-version: ${{ env.NODE_VERSION }}\n cache: 'npm'\n \n - name: ๐ฆ Install dependencies\n if: hashFiles('package.json') != ''\n run: npm ci\n \n - name: ๐๏ธ Setup test database\n run: |\n # Database migration and seeding based on project requirements\n echo \"Setting up integration test environment\"\n \n - name: ๐ Run integration tests\n run: |\n if grep -q '\"test:integration\"' package.json; then\n npm run test:integration\n else\n echo \"No integration tests configured\"\n fi\n env:\n DATABASE_URL: postgresql://postgres:postgres@localhost:5432/test_db\n REDIS_URL: redis://localhost:6379\n \n outputs:\n integration-passed: ${{ success() }}\n \n # ==========================================\n # BUILD JOBS\n # ==========================================\n \n build:\n name: ๐๏ธ Build Application\n runs-on: ubuntu-latest\n needs: [code-quality, unit-tests]\n if: needs.code-quality.outputs.quality-passed == 'true' && needs.unit-tests.outputs.tests-passed == 'true'\n \n steps:\n - name: ๐ฅ Checkout code\n uses: actions/checkout@v4\n \n - name: ๐ง Setup environment\n uses: actions/setup-node@v4\n if: hashFiles('package.json') != ''\n with:\n node-version: ${{ env.NODE_VERSION }}\n cache: 'npm'\n \n - name: ๐ฆ Install dependencies\n if: hashFiles('package.json') != ''\n run: npm ci\n \n - name: ๐๏ธ Build application\n run: |\n if grep -q '\"build\"' package.json; then\n npm run build\n else\n echo \"No build script found - assuming build-less deployment\"\n fi\n \n - name: ๐ฆ Create deployment artifact\n run: |\n # Create deployment package based on project type\n tar -czf deployment-artifact.tar.gz .\n \n - name: ๐ค Upload build artifacts\n uses: actions/upload-artifact@v3\n with:\n name: deployment-artifact\n path: deployment-artifact.tar.gz\n retention-days: 30\n \n outputs:\n build-passed: ${{ success() }}\n \n # ==========================================\n # DEPLOYMENT JOBS\n # ==========================================\n \n deploy-staging:\n name: ๐ Deploy to Staging\n runs-on: ubuntu-latest\n needs: [build, integration-tests]\n if: |\n needs.build.outputs.build-passed == 'true' &&\n (github.ref == 'refs/heads/develop' || github.event_name == 'workflow_dispatch')\n \n environment:\n name: staging\n url: ${{ steps.deploy.outputs.url }}\n \n steps:\n - name: ๐ฅ Download artifacts\n uses: actions/download-artifact@v3\n with:\n name: deployment-artifact\n \n - name: ๐ Deploy to staging\n id: deploy\n run: |\n echo \"Deploying to staging environment\"\n # Deployment commands based on infrastructure analysis\n # This section would be customized based on deployment target\n \n # Example: Vercel deployment\n # npx vercel --token=${{ secrets.VERCEL_TOKEN }} --prod\n \n # Example: AWS deployment\n # aws s3 sync ./dist s3://${{ secrets.STAGING_BUCKET }}\n \n # Example: Docker deployment\n # docker build -t app:staging .\n # docker push ${{ secrets.REGISTRY }}/app:staging\n \n echo \"url=https://staging.example.com\" >> $GITHUB_OUTPUT\n \n - name: ๐ Health check\n run: |\n echo \"Running staging health checks\"\n # Health check implementation based on application type\n curl -f ${{ steps.deploy.outputs.url }}/health || exit 1\n \n - name: ๐ Update deployment metrics\n if: success()\n run: |\n echo \"๐ Staging deployment successful\"\n # Integration with health monitoring system\n \n deploy-production:\n name: ๐ Deploy to Production\n runs-on: ubuntu-latest\n needs: [build, integration-tests, deploy-staging]\n if: |\n needs.build.outputs.build-passed == 'true' &&\n (github.ref == 'refs/heads/main' || github.event.inputs.environment == 'production')\n \n environment:\n name: production\n url: ${{ steps.deploy.outputs.url }}\n \n steps:\n - name: ๐ฅ Download artifacts\n uses: actions/download-artifact@v3\n with:\n name: deployment-artifact\n \n - name: ๐ Production safety checks\n run: |\n echo \"Running production safety validations\"\n # Additional production safety checks\n # Version validation, rollback preparation, etc.\n \n - name: ๐ Deploy to production\n id: deploy\n run: |\n echo \"Deploying to production environment\"\n # Production deployment commands\n \n echo \"url=https://production.example.com\" >> $GITHUB_OUTPUT\n \n - name: ๐ Production health verification\n run: |\n echo \"Running production health verification\"\n # Comprehensive production health checks\n curl -f ${{ steps.deploy.outputs.url }}/health || exit 1\n \n # Performance validation\n # Security validation\n # Integration testing in production\n \n - name: ๐ Deployment success notification\n if: success()\n run: |\n echo \"๐ Production deployment completed successfully!\"\n # Notification logic (Slack, email, etc.)\n \n - name: ๐ Update production metrics\n if: always()\n run: |\n echo \"๐ Updating production deployment metrics\"\n # Integration with monitoring and health systems\n \n # ==========================================\n # ROLLBACK JOB\n # ==========================================\n \n rollback:\n name: โฉ๏ธ Rollback Production\n runs-on: ubuntu-latest\n if: failure() && github.ref == 'refs/heads/main'\n needs: [deploy-production]\n \n environment:\n name: production-rollback\n \n steps:\n - name: โฉ๏ธ Execute rollback\n run: |\n echo \"๐จ Executing production rollback\"\n # Rollback implementation based on deployment strategy\n \n - name: ๐ Log rollback metrics\n if: always()\n run: |\n echo \"๐ Logging rollback event for analysis\"\n # Rollback metrics and analysis"
}
Step 6: Generate Environment-Specific Configuration โ
Tool: write_file
Parameters: {
"path": ".github/workflows/deploy-preview.yml",
"content": "name: ๐ Deploy Preview Environment\n\non:\n pull_request:\n types: [opened, synchronize, reopened]\n branches: [ main, develop ]\n\njobs:\n deploy-preview:\n name: ๐ Preview Deployment\n runs-on: ubuntu-latest\n if: github.event.pull_request.draft == false\n \n environment:\n name: preview-pr-${{ github.event.number }}\n url: ${{ steps.deploy.outputs.url }}\n \n steps:\n - name: ๐ฅ Checkout PR\n uses: actions/checkout@v4\n \n - name: ๐ง Setup environment\n uses: actions/setup-node@v4\n if: hashFiles('package.json') != ''\n with:\n node-version: '18'\n cache: 'npm'\n \n - name: ๐ฆ Install dependencies\n if: hashFiles('package.json') != ''\n run: npm ci\n \n - name: ๐๏ธ Build for preview\n run: |\n if grep -q '\"build\"' package.json; then\n npm run build\n fi\n \n - name: ๐ Deploy preview\n id: deploy\n run: |\n echo \"Deploying preview for PR #${{ github.event.number }}\"\n # Preview deployment logic based on infrastructure\n \n PREVIEW_URL=\"https://pr-${{ github.event.number }}.preview.example.com\"\n echo \"url=$PREVIEW_URL\" >> $GITHUB_OUTPUT\n \n - name: ๐ Comment preview URL\n uses: actions/github-script@v7\n with:\n script: |\n github.rest.issues.createComment({\n issue_number: context.issue.number,\n owner: context.repo.owner,\n repo: context.repo.repo,\n body: `## ๐ Preview Deployment\\n\\nโ
Your preview is ready!\\n\\n**URL**: ${{ steps.deploy.outputs.url }}\\n\\n*This preview will be available until the PR is closed.*`\n });\n \n - name: ๐งช Run preview tests\n run: |\n echo \"Running tests against preview environment\"\n # Preview environment testing\n curl -f ${{ steps.deploy.outputs.url }} || exit 1"
}
Step 7: Generate Security and Compliance Workflow โ
Tool: write_file
Parameters: {
"path": ".github/workflows/security-compliance.yml",
"content": "name: ๐ Security & Compliance\n\non:\n push:\n branches: [ main, develop ]\n pull_request:\n branches: [ main ]\n schedule:\n # Run security scans daily at 3 AM UTC\n - cron: '0 3 * * *'\n workflow_dispatch:\n\njobs:\n security-scan:\n name: ๐ Security Analysis\n runs-on: ubuntu-latest\n \n steps:\n - name: ๐ฅ Checkout code\n uses: actions/checkout@v4\n with:\n fetch-depth: 0\n \n - name: ๐ Run Trivy vulnerability scanner\n uses: aquasecurity/trivy-action@master\n with:\n scan-type: 'fs'\n scan-ref: '.'\n format: 'sarif'\n output: 'trivy-results.sarif'\n \n - name: ๐ Upload security scan results\n uses: github/codeql-action/upload-sarif@v2\n if: always()\n with:\n sarif_file: 'trivy-results.sarif'\n \n - name: ๐ Dependency security audit\n if: hashFiles('package.json') != ''\n run: |\n npm audit --audit-level=moderate\n # Additional dependency scanning\n \n - name: ๐ก๏ธ Container security scan\n if: hashFiles('Dockerfile') != ''\n run: |\n echo \"Running container security analysis\"\n # Container-specific security scanning\n \n - name: ๐ Generate security report\n if: always()\n run: |\n echo \"# ๐ Security Scan Report\" > security-report.md\n echo \"## Summary\" >> security-report.md\n echo \"- **Scan Date**: $(date)\" >> security-report.md\n echo \"- **Repository**: ${{ github.repository }}\" >> security-report.md\n echo \"- **Branch**: ${{ github.ref_name }}\" >> security-report.md\n \n if [ -f \"trivy-results.sarif\" ]; then\n echo \"- **Vulnerabilities Found**: $(jq '.runs[0].results | length' trivy-results.sarif)\" >> security-report.md\n fi\n \n - name: ๐ค Upload security report\n uses: actions/upload-artifact@v3\n if: always()\n with:\n name: security-report\n path: security-report.md\n \n compliance-check:\n name: ๐ Compliance Validation\n runs-on: ubuntu-latest\n \n steps:\n - name: ๐ฅ Checkout code\n uses: actions/checkout@v4\n \n - name: ๐ License compliance\n run: |\n echo \"Checking license compliance\"\n # License scanning and compliance validation\n \n - name: ๐ Data privacy compliance\n run: |\n echo \"Validating data privacy compliance\"\n # GDPR, CCPA, and other privacy regulation compliance\n \n - name: ๐ Accessibility compliance\n if: hashFiles('package.json') != ''\n run: |\n echo \"Running accessibility compliance checks\"\n # WCAG and accessibility standards validation\n \n - name: ๐ Compliance report\n run: |\n echo \"# ๐ Compliance Report\" > compliance-report.md\n echo \"Generated compliance validation report\"\n \n - name: ๐ค Upload compliance report\n uses: actions/upload-artifact@v3\n if: always()\n with:\n name: compliance-report\n path: compliance-report.md"
}
Phase 3: Monitoring & Health Integration (25 minutes) โ
Step 8: Generate Deployment Monitoring Workflow โ
Tool: write_file
Parameters: {
"path": ".github/workflows/deployment-monitoring.yml",
"content": "name: ๐ Deployment Health Monitoring\n\non:\n workflow_run:\n workflows: [\"๐ CI/CD Pipeline\"]\n types:\n - completed\n schedule:\n # Monitor every hour during business hours\n - cron: '0 9-18 * * 1-5'\n workflow_dispatch:\n inputs:\n environment:\n description: 'Environment to monitor'\n required: true\n default: 'production'\n type: choice\n options:\n - staging\n - production\n - preview\n\njobs:\n health-monitoring:\n name: ๐ Environment Health Check\n runs-on: ubuntu-latest\n \n strategy:\n matrix:\n environment: [staging, production]\n \n steps:\n - name: ๐ฅ Checkout monitoring scripts\n uses: actions/checkout@v4\n \n - name: ๐ง Setup monitoring environment\n run: |\n echo \"Setting up health monitoring for ${{ matrix.environment }}\"\n \n - name: ๐ฅ Application health check\n run: |\n ENVIRONMENT=\"${{ matrix.environment }}\"\n \n if [ \"$ENVIRONMENT\" = \"staging\" ]; then\n BASE_URL=\"https://staging.example.com\"\n elif [ \"$ENVIRONMENT\" = \"production\" ]; then\n BASE_URL=\"https://production.example.com\"\n fi\n \n echo \"๐ Checking health endpoint: $BASE_URL/health\"\n \n # Health endpoint validation\n HEALTH_STATUS=$(curl -s -o /dev/null -w \"%{http_code}\" $BASE_URL/health)\n \n if [ \"$HEALTH_STATUS\" = \"200\" ]; then\n echo \"โ
Health check passed for $ENVIRONMENT\"\n else\n echo \"โ Health check failed for $ENVIRONMENT (HTTP $HEALTH_STATUS)\"\n exit 1\n fi\n \n - name: ๐ Performance monitoring\n run: |\n echo \"๐ Running performance checks for ${{ matrix.environment }}\"\n # Performance monitoring implementation\n # Response time validation\n # Resource usage monitoring\n \n - name: ๐ Security monitoring\n run: |\n echo \"๐ Running security monitoring for ${{ matrix.environment }}\"\n # Security monitoring implementation\n # SSL certificate validation\n # Security header checks\n \n - name: ๐ Generate monitoring report\n if: always()\n run: |\n echo \"# ๐ Deployment Health Report\" > monitoring-report-${{ matrix.environment }}.md\n echo \"## Environment: ${{ matrix.environment }}\" >> monitoring-report-${{ matrix.environment }}.md\n echo \"- **Timestamp**: $(date)\" >> monitoring-report-${{ matrix.environment }}.md\n echo \"- **Status**: ${{ job.status }}\" >> monitoring-report-${{ matrix.environment }}.md\n \n - name: ๐ค Upload monitoring report\n uses: actions/upload-artifact@v3\n if: always()\n with:\n name: monitoring-report-${{ matrix.environment }}\n path: monitoring-report-${{ matrix.environment }}.md\n \n - name: ๐จ Alert on failure\n if: failure()\n run: |\n echo \"๐จ Health monitoring failed for ${{ matrix.environment }}\"\n # Alerting logic (Slack, PagerDuty, etc.)\n \n metrics-collection:\n name: ๐ Collect Deployment Metrics\n runs-on: ubuntu-latest\n needs: [health-monitoring]\n if: always()\n \n steps:\n - name: ๐ Aggregate monitoring data\n run: |\n echo \"๐ Collecting deployment metrics\"\n # Metrics aggregation logic\n \n - name: ๐ Update project health scores\n run: |\n echo \"๐ Updating project health dashboard\"\n # Integration with MCP health monitoring system\n # This would call the smart_score tool if available in CI environment"
}
Step 9: Update TODO Tasks with Generated CI/CD โ
Tool: manage_todo_json
Parameters: {
"operation": "bulk_update",
"updates": {
"status": "completed",
"notes": "Complete CI/CD pipeline generated with security, monitoring, and health integration"
},
"filters": {
"tags": ["ci-cd", "deployment"],
"status": "pending"
}
}
Step 10: Sync Health Scores with CI/CD Integration โ
Tool: smart_score
Parameters: {
"operation": "sync_scores",
"projectPath": ".",
"todoPath": "TODO.md",
"triggerTools": ["manage_todo"],
"rebalanceWeights": true
}
Step 11: Create Monitoring Integration TODO Tasks โ
Tool: manage_todo_json
Parameters: {
"operation": "create_task",
"title": "Configure CI/CD environment secrets and variables",
"description": "Set up required secrets and environment variables for generated GitHub Actions workflows",
"priority": "high",
"tags": ["ci-cd", "configuration", "secrets", "post-generation"],
"dueDate": "[Today + 2 days]",
"linkedAdrs": ["deployment-related-adrs"],
"autoComplete": false,
"completionCriteria": "All GitHub secrets configured and workflows tested"
}
Step 12: Final Health Score Update โ
Tool: smart_score
Parameters: {
"operation": "recalculate_scores",
"projectPath": ".",
"components": ["deployment_readiness", "code_quality", "security_posture"],
"forceUpdate": true,
"updateSources": true
}
GitHub Actions Generation Success Criteria:
- โ Complete CI/CD pipeline with quality gates generated
- โ Environment-specific deployment workflows created
- โ Security and compliance automation integrated
- โ Preview/staging deployment workflows included
- โ Health monitoring and alerting configured
- โ Rollback procedures implemented
- โ Integration with project health monitoring active
- โ Human deployment preferences incorporated
- โ Multi-environment support (staging, production, preview)
- โ Cross-platform compatibility ensured
Sophia Confidence Framework for CI/CD Generation:
- High Confidence (โฅ90%): Standard web applications with common deployment patterns
- Medium Confidence (80-89%): Complex applications with custom infrastructure requirements
- Lower Confidence (70-79%): Enterprise applications with specialized compliance needs
- Human Review Required: Confidence <70% or when dealing with sensitive production environments
Complete Development Lifecycle โ
Duration: 2-3 hours | Goal: End-to-end development process optimization
Phase 1: Project Initialization (45 minutes) โ
- Workflow Guidance - Get intelligent recommendations
- Ecosystem Analysis - Comprehensive technology assessment
- ADR Generation - From requirements or implicit decisions
- Security Foundation - Baseline security configuration
Phase 2: Development Planning (45 minutes) โ
- Rule Generation - Extract architectural constraints
- TODO Generation - Create implementation roadmap
- Development Guidance - Phase-specific implementation strategy
- Research Planning - Identify knowledge gaps
Phase 3: Implementation Validation (45 minutes) โ
- Progress Tracking - Compare TODOs vs reality
- Rule Validation - Ensure architectural compliance
- Security Validation - Continuous security assessment
- Deployment Readiness - Zero-tolerance quality gates
Phase 4: Release & Governance (45 minutes) โ
- Smart Git Push - Intelligent release validation
- Deployment Guidance - Environment-specific procedures
- Documentation Updates - Keep architecture current
- Process Improvement - Reflexion-based learning
Lifecycle Success Metrics: Documented architecture, validated quality, secure deployment, continuous improvement.
Enterprise Architecture Management โ
Duration: 3+ hours | Goal: Enterprise-scale architecture governance
Phase 1: Portfolio Assessment (60 minutes) โ
- Multi-project ecosystem analysis
- Consistency validation across projects
- Enterprise rule generation
- Compliance assessment
Phase 2: Standards Development (60 minutes) โ
- Enterprise ADR templates
- Governance rule sets
- Security standards
- Deployment procedures
Phase 3: Implementation & Enforcement (60 minutes) โ
- Automated validation pipelines
- Continuous compliance monitoring
- Architecture evolution tracking
- Knowledge management
Phase 4: Continuous Improvement (60 minutes) โ
- Performance optimization
- Process refinement
- Tool chain evolution
- Team enablement
Enterprise Success Criteria: Standardized architecture, automated governance, continuous compliance, scalable processes.
๐ก Workflow Optimization Tips โ
๐ง Sophia Methodology Integration โ
Confidence-Based Progression โ
- High Confidence (85%+): Proceed immediately with recommendations
- Medium Confidence (70-84%): Validate with additional tools
- Low Confidence (<70%): Seek alternative approaches or human review
Error Architecture Awareness โ
- Human-Cognitive Errors: Use AI to supplement domain knowledge gaps
- AI-Stochastic Errors: Use human review for critical architectural decisions
- Verification Loops: Implement systematic validation at each phase
Pragmatic Success Criteria โ
- Works Reliably: Solutions must function in production
- Addresses Constraints: Consider budget, time, and skill limitations
- Provides Value: Measurable improvement in development efficiency
- Enables Growth: Scalable architecture and processes
๐ Adaptive Workflow Strategies โ
Time-Based Adaptation โ
- 5-15 minutes: Quick health checks and immediate insights
- 30-60 minutes: Focused problem solving and analysis
- 2+ hours: Comprehensive transformation and governance
Context-Based Adaptation โ
- New Projects: Emphasize planning and foundation building
- Existing Projects: Focus on discovery and gap analysis
- Legacy Systems: Prioritize risk assessment and migration planning
- Enterprise Scale: Emphasize standardization and governance
Goal-Based Adaptation โ
- Security Focus: Prioritize security tools and validation
- Performance Focus: Emphasize environment analysis and optimization
- Compliance Focus: Focus on rule generation and validation
- Documentation Focus: Prioritize ADR generation and maintenance
๐ฏ Success Measurement Framework โ
Immediate Indicators (within session) โ
โ
Tool Execution Success - All tools complete without errors
โ
Data Quality - Comprehensive, relevant analysis results
โ
Actionable Outputs - Clear next steps and recommendations
โ
Security Validation - No exposed sensitive information
Progress Milestones (within days) โ
โ
Implementation Progress - TODO items being completed
โ
Architecture Clarity - Documented decisions and rationale
โ
Rule Compliance - Code following architectural constraints
โ
Quality Metrics - Improving test coverage and deployment success
Final Outcomes (within weeks) โ
โ
Reduced Technical Debt - Measurable improvement in code quality
โ
Faster Development - Reduced time from decision to implementation
โ
Improved Security - Fewer security issues and faster remediation
โ
Better Governance - Consistent architectural decisions across team
Continuous Improvement (ongoing) โ
โ
Process Refinement - Workflow optimization based on outcomes
โ
Tool Chain Evolution - Enhanced tool configurations and sequences
โ
Knowledge Growth - Improved architectural decision making
โ
Team Enablement - Broader adoption of best practices
Ready to optimize your development workflow? Choose your scenario and follow the step-by-step instructions. Each workflow is designed to leverage the full power of the MCP ADR Analysis Server while following Sophia's methodological pragmatism principles for reliable, measurable outcomes.
Continuous Health Monitoring Loop โ
Duration: 20-30 minutes per cycle | Goal: Continuous project health tracking with TODO, file, and deployment monitoring Frequency: Run every 2-4 hours during active development | Confidence Level: 95% for automated monitoring, 90% for human-guided decisions
Phase 1: Health Baseline & TODO Discovery (5 minutes) โ
Step 1: Initialize Project Health Baseline โ
Tool: smart_score
Parameters: {
"operation": "recalculate_scores",
"projectPath": ".",
"components": ["all"],
"forceUpdate": true,
"updateSources": true
}
Sophia Framework: Establishes systematic baseline with 95% confidence for automated components
Step 2: Discover and Sync TODO Tasks โ
Tool: manage_todo_json
Parameters: {
"operation": "get_analytics",
"projectPath": ".",
"timeframe": "week",
"includeVelocity": true,
"includeScoring": true,
"sortBy": "priority"
}
Expected Output: Current task completion metrics, velocity trends, scoring integration
Step 3: Generate Health Dashboard Snapshot โ
Tool: smart_score
Parameters: {
"operation": "diagnose_scores",
"projectPath": ".",
"includeHistory": true,
"checkDataFreshness": true,
"suggestImprovements": true
}
Phase 2: File Change Monitoring & Quality Assessment (8 minutes) โ
Step 4: Analyze Recent File Changes (Human-Guided Context) โ
Interactive Checkpoint: Gather human perspective on recent changes
Human Feedback Prompts:
- "What significant files have you modified since last health check?"
- "Any new dependencies or architectural changes introduced?"
- "Rate your confidence in recent changes (1-10)?"
- "Any known issues or technical debt introduced?"
Step 5: File-Level Health Assessment โ
Tool: validate_rules
Parameters: {
"reportFormat": "detailed",
"validationType": "file",
"rules": [],
"filePath": "[From human input or git status]"
}
Conditional: Execute for each significant file mentioned by human
Step 6: Update TODO Tasks Based on File Changes โ
Tool: manage_todo_json
Parameters: {
"operation": "create_task",
"title": "Address quality issues in [filename]",
"description": "Quality assessment revealed issues requiring attention",
"priority": "medium",
"tags": ["code-quality", "health-monitoring", "automated"],
"linkedAdrs": ["relevant-adr-files"],
"dueDate": "[Today + 2 days]"
}
Conditional: Only execute if quality issues found (confidence threshold โฅ80%)
Step 7: Security Scan on Changed Files โ
Tool: analyze_content_security
Parameters: {
"content": "[File content from changes]",
"contentType": "code",
"userDefinedPatterns": []
}
Phase 3: Deployment Readiness & Health Sync (10 minutes) โ
Step 8: Deployment Readiness Assessment โ
Tool: deployment_readiness
Parameters: {
"operation": "check_readiness",
"targetEnvironment": "production",
"strictMode": true,
"integrateTodoTasks": true,
"updateHealthScoring": true,
"triggerSmartGitPush": false
}
Step 9: Create Health-Based TODO Tasks โ
Tool: manage_todo_json
Parameters: {
"operation": "bulk_update",
"updates": {
"tags": ["health-monitoring", "automated-creation"],
"notes": "Generated by continuous health monitoring - [timestamp]"
},
"filters": {
"category": "health-improvement",
"status": "pending"
}
}
Step 10: Cross-Tool Score Synchronization โ
Tool: smart_score
Parameters: {
"operation": "sync_scores",
"projectPath": ".",
"todoPath": "TODO.md",
"triggerTools": ["manage_todo", "smart_git_push", "validate_rules"],
"rebalanceWeights": false
}
Phase 4: Dashboard Updates & Monitoring Tasks (7 minutes) โ
Step 11: Generate Health Trends Analysis โ
Tool: smart_score
Parameters: {
"operation": "get_score_trends",
"projectPath": "."
}
Step 12: Create Monitoring TODO Tasks for Next Cycle โ
Tool: manage_todo_json
Parameters: {
"operation": "create_task",
"title": "Health Monitoring Cycle - [Next cycle timestamp]",
"description": "Scheduled health monitoring check for project metrics",
"priority": "low",
"tags": ["health-monitoring", "scheduled", "automated"],
"dueDate": "[Today + 4 hours]",
"autoComplete": true,
"completionCriteria": "Health monitoring cycle completed successfully"
}
Step 13: Update Project Health Dashboard โ
Tool: smart_score
Parameters: {
"operation": "optimize_weights",
"projectPath": ".",
"analysisMode": "current_state",
"previewOnly": true
}
Step 14: Human Review & Dashboard Validation โ
Interactive Checkpoint: Human validates health dashboard updates
Human Validation Questions:
- "Review health dashboard - does it accurately reflect project state?"
- "Any health metrics that seem incorrect or misleading?"
- "Should any TODO tasks be reprioritized based on health trends?"
- "Confidence in current health assessment (1-10)?"
Step 15: Sync Final Health State to Knowledge Graph โ
Tool: manage_todo_json
Parameters: {
"operation": "sync_knowledge_graph",
"direction": "bidirectional",
"intentId": "[Active intent ID if available]",
"projectPath": "."
}
Continuous Loop Success Criteria:
- โ Health baseline established and tracked
- โ TODO tasks synchronized with health metrics
- โ File changes assessed for quality impact
- โ Deployment readiness continuously monitored
- โ Dashboard reflects current project state
- โ Human validation โฅ8/10 confidence
- โ Monitoring tasks created for next cycle
Health Monitoring Decision Matrix:
- ๐ข GREEN (Healthy): Overall health โฅ80% + Human confidence โฅ8/10
- ๐ก YELLOW (Watch): Overall health 60-79% + Human confidence 6-7/10
- ๐ด RED (Action Needed): Overall health <60% OR Human confidence โค5/10
Loop Automation Triggers:
- Time-based: Every 2-4 hours during active development
- Event-based: After significant commits, deployments, or TODO updates
- Threshold-based: When health scores drop below 70%
- Human-triggered: Manual execution when concerns arise
Sophia Verification Framework:
- Error Detection: Distinguish between data staleness vs. actual quality degradation
- Confidence Thresholds: โฅ85% for automated actions, โฅ70% for human review triggers
- Fallibilism: Acknowledge monitoring limitations and provide alternative verification approaches