# TDD Mode Resources Documentation

## Overview

This document provides comprehensive guidance for accessing and utilizing SAFLA's MCP resources within the Test-Driven Development (TDD) mode. The TDD mode leverages SAFLA's 15 direct resources to monitor test execution, analyze coverage, track performance, and optimize testing workflows through real-time data access.

## Core Testing Resources

### 1. Test Execution and Results Resources

#### Test Results Resource: [`safla://test-results`](safla/mcp_stdio_server.py:1)

**Primary Usage**: Real-time access to test execution results, coverage data, and quality metrics

```bash
# Access current test execution results
access_mcp_resource safla "safla://test-results"

# Expected Response:
{
  "latest_execution": {
    "timestamp": "2024-01-15T14:30:00Z",
    "execution_id": "test_run_001",
    "total_tests": 234,
    "passed": 228,
    "failed": 6,
    "skipped": 0,
    "execution_time": "3m 45s",
    "parallel_workers": 4
  },
  "test_categories": {
    "unit_tests": {
      "total": 156,
      "passed": 154,
      "failed": 2,
      "execution_time": "1m 23s"
    },
    "integration_tests": {
      "total": 54,
      "passed": 52,
      "failed": 2,
      "execution_time": "1m 45s"
    },
    "performance_tests": {
      "total": 24,
      "passed": 22,
      "failed": 2,
      "execution_time": "37s"
    }
  },
  "failure_analysis": [
    {
      "test_name": "data_processor.unit.test.ts:validateInput",
      "error_type": "assertion_failure",
      "error_message": "Expected 'valid' but received 'invalid'",
      "stack_trace": "at line 45",
      "category": "unit_test"
    },
    {
      "test_name": "api_integration.test.ts:postUserData", 
      "error_type": "timeout",
      "error_message": "Test timeout after 5000ms",
      "category": "integration_test"
    }
  ]
}
```

**Advanced Usage Patterns**:
```bash
# Monitor test results during continuous execution
while true; do
  access_mcp_resource safla "safla://test-results"
  sleep 30
done

# Extract specific test categories
access_mcp_resource safla "safla://test-results" | jq '.test_categories.unit_tests'

# Monitor failure trends
access_mcp_resource safla "safla://test-results" | jq '.failure_analysis'
```

#### Test Coverage Resource: [`safla://test-coverage`](safla/mcp_stdio_server.py:1)

**Primary Usage**: Detailed test coverage analysis and gap identification

```bash
# Access comprehensive coverage data
access_mcp_resource safla "safla://test-coverage"

# Expected Response:
{
  "coverage_summary": {
    "overall_coverage": 94.7,
    "line_coverage": 94.7,
    "branch_coverage": 91.2,
    "function_coverage": 97.8,
    "statement_coverage": 95.1
  },
  "file_coverage": [
    {
      "file": "src/data_processor.ts",
      "line_coverage": 96.2,
      "branch_coverage": 93.4,
      "function_coverage": 100.0,
      "uncovered_lines": [45, 67, 89],
      "uncovered_branches": [
        {"line": 78, "condition": "error_handling"},
        {"line": 156, "condition": "edge_case"}
      ]
    },
    {
      "file": "src/validator.ts", 
      "line_coverage": 98.1,
      "branch_coverage": 95.7,
      "function_coverage": 100.0,
      "uncovered_lines": [23, 178]
    }
  ],
  "coverage_trends": {
    "7_day_trend": "+2.3%",
    "30_day_trend": "+5.7%",
    "target_progress": "94.7% of 95% target"
  },
  "quality_metrics": {
    "test_quality_score": 87.4,
    "maintainability_index": 82.1,
    "complexity_coverage": 89.7,
    "edge_case_coverage": 76.3
  }
}
```

**Coverage Analysis Patterns**:
```bash
# Monitor coverage gaps
access_mcp_resource safla "safla://test-coverage" | jq '.file_coverage[] | select(.line_coverage < 95)'

# Track coverage trends
access_mcp_resource safla "safla://test-coverage" | jq '.coverage_trends'

# Identify quality improvement opportunities
access_mcp_resource safla "safla://test-coverage" | jq '.quality_metrics'
```

### 2. Performance and Optimization Resources

#### Performance Metrics Resource: [`safla://performance-metrics`](safla/mcp_stdio_server.py:1)

**Primary Usage**: Real-time performance monitoring during test execution

```bash
# Access current performance metrics
access_mcp_resource safla "safla://performance-metrics"

# Expected Response:
{
  "test_execution_performance": {
    "avg_test_execution_time": "1.2s",
    "parallel_efficiency": 87.3,
    "resource_utilization": {
      "cpu_usage": 68.4,
      "memory_usage": 2.1,
      "disk_io": "moderate",
      "network_io": "low"
    },
    "bottlenecks": [
      {
        "component": "database_mocking",
        "impact": "medium",
        "recommendation": "implement_connection_pooling"
      }
    ]
  },
  "application_performance": {
    "response_times": {
      "avg": "45ms",
      "p95": "78ms", 
      "p99": "123ms"
    },
    "throughput": {
      "requests_per_second": 1247,
      "concurrent_users": 500
    },
    "memory_metrics": {
      "heap_usage": "1.8GB",
      "peak_usage": "2.1GB",
      "gc_frequency": "every_2.3s"
    }
  },
  "performance_trends": {
    "response_time_trend": "improving",
    "throughput_trend": "stable",
    "memory_trend": "optimizing"
  }
}
```

**Performance Monitoring Patterns**:
```bash
# Monitor test execution performance
access_mcp_resource safla "safla://performance-metrics" | jq '.test_execution_performance'

# Track application performance during testing
access_mcp_resource safla "safla://performance-metrics" | jq '.application_performance'

# Identify performance bottlenecks
access_mcp_resource safla "safla://performance-metrics" | jq '.test_execution_performance.bottlenecks'
```

#### Performance Baselines Resource: [`safla://performance-baselines`](safla/mcp_stdio_server.py:1)

**Primary Usage**: Baseline comparison for performance regression testing

```bash
# Access established performance baselines
access_mcp_resource safla "safla://performance-baselines"

# Expected Response:
{
  "baseline_metrics": {
    "established_date": "2024-01-01T00:00:00Z",
    "baseline_version": "v2.1.0",
    "test_execution_baselines": {
      "unit_test_avg_time": "0.8s",
      "integration_test_avg_time": "2.1s",
      "performance_test_avg_time": "5.3s",
      "total_suite_time": "8.2s"
    },
    "application_baselines": {
      "response_time": "42ms",
      "throughput": "1150_ops_per_second",
      "memory_usage": "1.9GB",
      "cpu_utilization": "65%"
    }
  },
  "regression_thresholds": {
    "response_time_threshold": "10%",
    "throughput_threshold": "5%",
    "memory_threshold": "15%",
    "test_execution_threshold": "20%"
  },
  "baseline_history": [
    {
      "version": "v2.0.0",
      "date": "2023-12-01T00:00:00Z",
      "response_time": "48ms",
      "throughput": "1050_ops_per_second"
    },
    {
      "version": "v1.9.0",
      "date": "2023-11-01T00:00:00Z", 
      "response_time": "52ms",
      "throughput": "980_ops_per_second"
    }
  ]
}
```

**Baseline Comparison Patterns**:
```bash
# Compare current performance with baselines
current_metrics=$(access_mcp_resource safla "safla://performance-metrics")
baselines=$(access_mcp_resource safla "safla://performance-baselines")

# Calculate performance regression
echo "$current_metrics" | jq --argjson baselines "$baselines" '
  .application_performance.response_times.avg as $current_rt |
  $baselines.baseline_metrics.application_baselines.response_time as $baseline_rt |
  (($current_rt | tonumber) - ($baseline_rt | sub("ms"; "") | tonumber)) / ($baseline_rt | sub("ms"; "") | tonumber) * 100
'
```

### 3. System and Configuration Resources

#### SAFLA Configuration Resource: [`safla://config`](safla/mcp_stdio_server.py:1)

**Primary Usage**: Access testing configuration and environment settings

```bash
# Access SAFLA configuration for testing
access_mcp_resource safla "safla://config"

# Expected Response:
{
  "testing_configuration": {
    "default_framework": "jest",
    "coverage_threshold": 95,
    "parallel_workers": 4,
    "timeout_settings": {
      "unit_test_timeout": "5000ms",
      "integration_test_timeout": "30000ms",
      "performance_test_timeout": "60000ms"
    },
    "reporting": {
      "coverage_reports": true,
      "performance_reports": true,
      "html_reports": true,
      "json_exports": true
    }
  },
  "environment_settings": {
    "test_environment": "development",
    "database_config": "test_db",
    "api_endpoints": "mock_services",
    "logging_level": "debug"
  },
  "optimization_settings": {
    "memory_optimization": "enabled",
    "parallel_execution": "enabled",
    "cache_test_results": true,
    "incremental_testing": true
  }
}
```

**Configuration Usage Patterns**:
```bash
# Extract testing-specific configuration
access_mcp_resource safla "safla://config" | jq '.testing_configuration'

# Monitor optimization settings
access_mcp_resource safla "safla://config" | jq '.optimization_settings'

# Validate environment configuration
access_mcp_resource safla "safla://config" | jq '.environment_settings'
```

#### System Status Resource: [`safla://status`](safla/mcp_stdio_server.py:1)

**Primary Usage**: Monitor system health during testing operations

```bash
# Access system status for testing operations
access_mcp_resource safla "safla://status"

# Expected Response:
{
  "system_health": {
    "overall_status": "healthy",
    "uptime": "7d 12h 34m",
    "last_restart": "2024-01-08T10:00:00Z"
  },
  "testing_services": {
    "test_runner": "active",
    "coverage_analyzer": "active", 
    "performance_monitor": "active",
    "mock_services": "active",
    "database_test_instance": "active"
  },
  "resource_utilization": {
    "cpu_usage": 68.4,
    "memory_usage": 72.1,
    "disk_usage": 45.3,
    "network_usage": "moderate"
  },
  "active_test_sessions": {
    "total_sessions": 3,
    "unit_test_sessions": 1,
    "integration_test_sessions": 1,
    "performance_test_sessions": 1
  }
}
```

**System Monitoring Patterns**:
```bash
# Monitor testing service health
access_mcp_resource safla "safla://status" | jq '.testing_services'

# Check resource utilization during testing
access_mcp_resource safla "safla://status" | jq '.resource_utilization'

# Monitor active test sessions
access_mcp_resource safla "safla://status" | jq '.active_test_sessions'
```

### 4. Learning and Adaptation Resources

#### Learning Metrics Resource: [`safla://learning-metrics`](safla/mcp_stdio_server.py:1)

**Primary Usage**: Monitor adaptive learning for test optimization

```bash
# Access learning metrics for testing improvements
access_mcp_resource safla "safla://learning-metrics"

# Expected Response:
{
  "test_learning_metrics": {
    "test_effectiveness_learning": 89.4,
    "coverage_optimization_learning": 76.2,
    "performance_prediction_accuracy": 92.1,
    "failure_pattern_recognition": 84.7
  },
  "adaptation_success": {
    "successful_test_optimizations": 34,
    "failed_optimizations": 3,
    "optimization_success_rate": 91.9,
    "avg_improvement_percentage": 12.3
  },
  "learning_trends": {
    "7_day_learning_rate": 15.2,
    "30_day_adaptation_count": 127,
    "knowledge_retention_score": 94.1
  },
  "test_pattern_insights": [
    {
      "pattern": "async_test_optimization",
      "confidence": 94.2,
      "application_count": 23,
      "success_rate": 91.3
    },
    {
      "pattern": "mock_efficiency_improvement",
      "confidence": 87.6,
      "application_count": 18,
      "success_rate": 88.9
    }
  ]
}
```

**Learning Analysis Patterns**:
```bash
# Monitor test learning effectiveness
access_mcp_resource safla "safla://learning-metrics" | jq '.test_learning_metrics'

# Track adaptation success rates
access_mcp_resource safla "safla://learning-metrics" | jq '.adaptation_success'

# Analyze test pattern insights
access_mcp_resource safla "safla://learning-metrics" | jq '.test_pattern_insights'
```

#### Adaptation Patterns Resource: [`safla://adaptation-patterns`](safla/mcp_stdio_server.py:1)

**Primary Usage**: Analyze testing adaptation trends and behavioral evolution

```bash
# Access adaptation patterns for testing evolution
access_mcp_resource safla "safla://adaptation-patterns"

# Expected Response:
{
  "testing_adaptation_patterns": {
    "test_generation_evolution": {
      "pattern_type": "incremental_improvement",
      "confidence": 92.3,
      "trend": "improving",
      "adaptations": [
        "enhanced_edge_case_detection",
        "improved_assertion_quality",
        "optimized_test_structure"
      ]
    },
    "coverage_optimization_patterns": {
      "pattern_type": "targeted_improvement",
      "confidence": 87.1,
      "trend": "stable",
      "adaptations": [
        "gap_prioritization",
        "intelligent_test_selection",
        "coverage_prediction"
      ]
    },
    "performance_testing_evolution": {
      "pattern_type": "predictive_optimization",
      "confidence": 89.7,
      "trend": "advancing",
      "adaptations": [
        "bottleneck_prediction",
        "load_pattern_optimization",
        "resource_usage_prediction"
      ]
    }
  },
  "behavioral_evolution": {
    "test_strategy_refinement": 78.4,
    "quality_focus_adaptation": 85.2,
    "efficiency_optimization": 91.6
  },
  "pattern_effectiveness": [
    {
      "pattern": "adaptive_test_prioritization",
      "effectiveness": 94.1,
      "usage_frequency": "high",
      "impact": "significant"
    },
    {
      "pattern": "intelligent_mock_generation",
      "effectiveness": 87.3,
      "usage_frequency": "medium",
      "impact": "moderate"
    }
  ]
}
```

**Adaptation Analysis Patterns**:
```bash
# Monitor testing evolution patterns
access_mcp_resource safla "safla://adaptation-patterns" | jq '.testing_adaptation_patterns'

# Track behavioral evolution in testing
access_mcp_resource safla "safla://adaptation-patterns" | jq '.behavioral_evolution'

# Analyze pattern effectiveness
access_mcp_resource safla "safla://adaptation-patterns" | jq '.pattern_effectiveness'
```

### 5. Goal and Strategy Resources

#### System Goals Resource: [`safla://goals`](safla/mcp_stdio_server.py:1)

**Primary Usage**: Monitor testing goals and progress tracking

```bash
# Access testing-related goals
access_mcp_resource safla "safla://goals"

# Expected Response:
{
  "active_testing_goals": [
    {
      "goal_id": "test_coverage_excellence",
      "goal_name": "Comprehensive Test Coverage",
      "description": "Achieve 95% test coverage with high quality",
      "priority": "high",
      "status": "active",
      "progress": 0.89,
      "target_metrics": {
        "line_coverage": 0.95,
        "branch_coverage": 0.92,
        "quality_score": 0.90
      },
      "current_metrics": {
        "line_coverage": 0.947,
        "branch_coverage": 0.912,
        "quality_score": 0.874
      },
      "deadline": "2024-02-01T00:00:00Z",
      "estimated_completion": "2024-01-28T00:00:00Z"
    },
    {
      "goal_id": "performance_test_optimization",
      "goal_name": "Performance Testing Excellence",
      "description": "Optimize performance testing efficiency and accuracy",
      "priority": "medium",
      "status": "active",
      "progress": 0.72,
      "target_metrics": {
        "test_execution_speed": 0.3,
        "accuracy_improvement": 0.15,
        "resource_efficiency": 0.25
      }
    }
  ],
  "completed_goals": [
    {
      "goal_id": "test_automation_setup",
      "completion_date": "2024-01-10T00:00:00Z",
      "final_score": 96.2,
      "achievements": ["full_ci_integration", "automated_reporting", "quality_gates"]
    }
  ]
}
```

**Goal Monitoring Patterns**:
```bash
# Monitor active testing goals
access_mcp_resource safla "safla://goals" | jq '.active_testing_goals'

# Track goal progress
access_mcp_resource safla "safla://goals" | jq '.active_testing_goals[] | {goal_name, progress, estimated_completion}'

# Analyze completed achievements
access_mcp_resource safla "safla://goals" | jq '.completed_goals'
```

#### Available Strategies Resource: [`safla://strategies`](safla/mcp_stdio_server.py:1)

**Primary Usage**: Access testing strategies and performance metrics

```bash
# Access available testing strategies
access_mcp_resource safla "safla://strategies"

# Expected Response:
{
  "testing_strategies": [
    {
      "strategy_id": "comprehensive_tdd_001",
      "strategy_name": "Comprehensive Test-Driven Development",
      "context": "full_feature_development",
      "effectiveness_score": 94.2,
      "usage_count": 47,
      "success_rate": 91.5,
      "components": [
        "red_green_refactor_cycle",
        "comprehensive_coverage",
        "performance_validation",
        "quality_assurance"
      ]
    },
    {
      "strategy_id": "performance_focused_testing",
      "strategy_name": "Performance-Focused Testing Strategy",
      "context": "performance_critical_features",
      "effectiveness_score": 89.7,
      "usage_count": 23,
      "success_rate": 87.0,
      "components": [
        "baseline_establishment",
        "load_testing",
        "stress_testing",
        "regression_monitoring"
      ]
    },
    {
      "strategy_id": "adaptive_test_optimization",
      "strategy_name": "Adaptive Test Optimization",
      "context": "continuous_improvement",
      "effectiveness_score": 92.1,
      "usage_count": 34,
      "success_rate": 89.4,
      "components": [
        "intelligent_test_selection",
        "coverage_gap_analysis",
        "performance_optimization",
        "learning_integration"
      ]
    }
  ],
  "strategy_performance": {
    "most_effective": "comprehensive_tdd_001",
    "most_used": "comprehensive_tdd_001",
    "highest_success_rate": "comprehensive_tdd_001",
    "emerging_strategies": ["adaptive_test_optimization"]
  }
}
```

**Strategy Analysis Patterns**:
```bash
# Identify most effective testing strategies
access_mcp_resource safla "safla://strategies" | jq '.testing_strategies | sort_by(.effectiveness_score) | reverse'

# Monitor strategy performance
access_mcp_resource safla "safla://strategies" | jq '.strategy_performance'

# Analyze strategy usage patterns
access_mcp_resource safla "safla://strategies" | jq '.testing_strategies[] | {strategy_name, usage_count, success_rate}'
```

### 6. Agent and Session Resources

#### Agent Sessions Resource: [`safla://agent-sessions`](safla/mcp_stdio_server.py:1)

**Primary Usage**: Monitor active testing agent sessions

```bash
# Access active agent sessions for testing
access_mcp_resource safla "safla://agent-sessions"

# Expected Response:
{
  "active_testing_sessions": [
    {
      "session_id": "tdd_agent_001",
      "agent_type": "cognitive",
      "focus": "test_driven_development",
      "status": "active",
      "uptime": "2h 15m",
      "tasks_completed": 12,
      "current_task": "integration_test_generation",
      "performance_metrics": {
        "task_completion_rate": 94.2,
        "quality_score": 87.6,
        "efficiency_rating": 91.3
      }
    },
    {
      "session_id": "performance_test_agent_002",
      "agent_type": "cognitive", 
      "focus": "performance_testing",
      "status": "active",
      "uptime": "45m",
      "tasks_completed": 3,
      "current_task": "load_test_execution",
      "performance_metrics": {
        "task_completion_rate": 100.0,
        "accuracy": 96.1,
        "efficiency_rating": 89.7
      }
    }
  ],
  "session_statistics": {
    "total_active_sessions": 2,
    "avg_session_uptime": "1h 30m",
    "total_tasks_completed": 15,
    "avg_performance_score": 91.2
  }
}
```

**Agent Monitoring Patterns**:
```bash
# Monitor testing agent performance
access_mcp_resource safla "safla://agent-sessions" | jq '.active_testing_sessions[] | {session_id, focus, performance_metrics}'

# Track agent task completion
access_mcp_resource safla "safla://agent-sessions" | jq '.session_statistics'

# Monitor specific agent types
access_mcp_resource safla "safla://agent-sessions" | jq '.active_testing_sessions[] | select(.focus == "test_driven_development")'
```

### 7. Advanced Resource Integration Patterns

#### Multi-Resource Analysis
```bash
# Comprehensive testing dashboard data
test_results=$(access_mcp_resource safla "safla://test-results")
coverage_data=$(access_mcp_resource safla "safla://test-coverage")
performance_metrics=$(access_mcp_resource safla "safla://performance-metrics")

# Combine data for comprehensive analysis
echo "$test_results $coverage_data $performance_metrics" | jq -s '
{
  "testing_summary": {
    "execution_status": .[0].latest_execution,
    "coverage_status": .[1].coverage_summary,
    "performance_status": .[2].test_execution_performance
  }
}'
```

#### Real-Time Monitoring Workflows
```bash
# Continuous testing monitoring script
#!/bin/bash
while true; do
  echo "=== Testing Status Update $(date) ==="
  
  # Test execution status
  echo "Test Results:"
  access_mcp_resource safla "safla://test-results" | jq '.latest_execution | {passed, failed, execution_time}'
  
  # Coverage status
  echo "Coverage Status:"
  access_mcp_resource safla "safla://test-coverage" | jq '.coverage_summary'
  
  # Performance status
  echo "Performance Status:"
  access_mcp_resource safla "safla://performance-metrics" | jq '.test_execution_performance.resource_utilization'
  
  sleep 60
done
```

#### Resource-Based Alerting
```bash
# Alert on coverage drops
coverage=$(access_mcp_resource safla "safla://test-coverage" | jq '.coverage_summary.overall_coverage')
if (( $(echo "$coverage < 95" | bc -l) )); then
  echo "ALERT: Coverage dropped below 95%: $coverage%"
fi

# Alert on test failures
failures=$(access_mcp_resource safla "safla://test-results" | jq '.latest_execution.failed')
if [ "$failures" -gt 0 ]; then
  echo "ALERT: $failures test(s) failed"
fi
```

This comprehensive resources documentation provides detailed guidance for leveraging SAFLA's MCP resources within the TDD mode, ensuring effective monitoring, analysis, and optimization of testing workflows through real-time data access and intelligent resource utilization.