personamanagmentlayer/pcl2 files

Construction Expert

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Specification
Skill ID
personamanagmentlayer/pcl/construction-expert
Publisher
personamanagmentlayer
Repository
pcl
Installs
0
Files
2
Synced
Sep 23, 2026
How to use it

Open any RiverX project, open the Skills panel in the chat, and search for this identifier. The files are fetched from the source repository at install time.

personamanagmentlayer/pcl/construction-expertInstalls these files
  • SKILL.md
  • references/PROJECT_MANAGEMENT_SYSTEM.md

What this skill tells the agent

Construction Expert

Expert guidance for construction management, project planning, Building Information Modeling (BIM), safety compliance, and modern construction technology solutions.

Core Concepts

Construction Management

  • Project planning and scheduling
  • Cost estimation and control
  • Resource management
  • Quality assurance
  • Contract management
  • Risk management
  • Change order management

Technologies

  • Building Information Modeling (BIM)
  • Construction management software
  • Drone surveying and inspection
  • 3D printing and modular construction
  • IoT sensors for monitoring
  • Augmented reality for visualization
  • Construction robotics

Standards and Regulations

  • OSHA safety regulations
  • Building codes (IBC, IRC)
  • AIA contracts and standards
  • LEED certification
  • ISO 19650 (BIM standards)
  • CSI MasterFormat
  • Environmental regulations

Safety Management System

@dataclass
class SafetyIncident:
    """Safety incident report"""
    incident_id: str
    project_id: str
    incident_type: str  # 'injury', 'near_miss', 'property_damage'
    severity: str  # 'minor', 'moderate', 'severe', 'fatal'
    description: str
    location: str
    occurred_at: datetime
    reported_by: str
    injured_person: Optional[str]
    root_cause: Optional[str]
    corrective_actions: List[str]

class SafetyManagementSystem:
    """Construction safety management"""

    def __init__(self):
        self.incidents = []
        self.safety_inspections = []
        self.training_records = []

    def conduct_safety_inspection(self, project_id: str, inspector: str) -> dict:
        """Conduct safety inspection"""
        inspection_items = [
            'Personal protective equipment (PPE)',
            'Fall protection systems',
            'Scaffolding integrity',
            'Electrical safety',
            'Equipment guarding',
            'Housekeeping',
            'Fire prevention',
            'First aid availability',
            'Emergency exits',
            'Signage and barriers'
        ]

        violations = []
        passed_items = []

        # Simulate inspection (in production, would be actual checklist)
        for item in inspection_items:
            # Random pass/fail for demonstration
            import random
            if random.random() < 0.85:  # 85% pass rate
                passed_items.append(item)
            else:
                violations.append({
                    'item': item,
                    'severity': random.choice(['minor', 'major']),
                    'action_required': 'Correct immediately' if random.random() < 0.3 else 'Correct within 24 hours'
                })

        inspection = {
            'inspection_id': self._generate_inspection_id(),
            'project_id': project_id,
            'inspector': inspector,
            'inspection_date': datetime.now(),
            'items_inspected': len(inspection_items),
            'items_passed': len(passed_items),
            'violations': violations,
            'overall_score': (len(passed_items) / len(inspection_items)) * 100,
            'status': 'pass' if len(violations) == 0 else 'fail'
        }

        self.safety_inspections.append(inspection)

        return inspection

    def report_incident(self, incident_data: dict) -> SafetyIncident:
        """Report safety incident"""
        incident = SafetyIncident(
            incident_id=self._generate_incident_id(),
            project_id=incident_data['project_id'],
            incident_type=incident_data['incident_type'],
            severity=incident_data['severity'],
            description=incident_data['description'],
            location=incident_data['location'],
            occurred_at=incident_data['occurred_at'],
            reported_by=incident_data['reported_by'],
            injured_person=incident_data.get('injured_person'),
            root_cause=None,
            corrective_actions=[]
        )

        self.incidents.append(incident)

        # Notify relevant parties
        self._notify_incident(incident)

        return incident

    def calculate_safety_metrics(self, project_id: str, hours_worked: float) -> dict:
        """Calculate safety performance metrics"""
        project_incidents = [
            i for i in self.incidents
            if i.project_id == project_id
        ]

        # Count recordable incidents
        recordable_incidents = [
            i for i in project_incidents
            if i.incident_type == 'injury' and i.severity in ['moderate', 'severe', 'fatal']
        ]

        # OSHA Incident Rate = (Number of incidents × 200,000) / Total hours worked
        if hours_worked > 0:
            incident_rate = (len(recordable_incidents) * 200000) / hours_worked
        else:
            incident_rate = 0

        # Days Away, Restricted, or Transferred (DART) Rate
        dart_incidents = [
            i for i in recordable_incidents
            if i.severity in ['severe', 'fatal']
        ]
        dart_rate = (len(dart_incidents) * 200000) / hours_worked if hours_worked > 0 else 0

        return {
            'project_id': project_id,
            'total_hours_worked': hours_worked,
            'total_incidents': len(project_incidents),
            'recordable_incidents': len(recordable_incidents),
            'incident_rate': incident_rate,
            'dart_rate': dart_rate,
            'safety_rating': 'Excellent' if incident_rate < 1.0 else
                           'Good' if incident_rate < 3.0 else
                           'Needs Improvement'
        }

    def _notify_incident(self, incident: SafetyIncident):
        """Notify stakeholders of incident"""
        # Implementation would send notifications
        pass

    def _generate_inspection_id(self) -> str:
        import uuid
        return f"INS-{uuid.uuid4().hex[:8].upper()}"

    def _generate_incident_id(self) -> str:
        import uuid
        return f"INC-{uuid.uuid4().hex[:8].upper()}"

BIM Integration

class BIMManagement:
    """Building Information Modeling management"""

    def __init__(self):
        self.models = {}
        self.clash_detections = []

    def perform_clash_detection(self, model_ids: List[str]) -> dict:
        """Detect clashes between BIM models"""
        # Simulate clash detection between disciplines
        # In production, would use BIM software APIs (Revit, Navisworks)

        clashes = [
            {
                'clash_id': 'CLASH-001',
                'type': 'hard',  # 'hard' or 'soft'
                'disciplines': ['structural', 'mep'],
                'description': 'Steel beam conflicts with HVAC duct',
                'location': 'Level 3, Grid B-4',
                'severity': 'high',
                'status': 'open'
            },
            {
                'clash_id': 'CLASH-002',
                'type': 'soft',
                'disciplines': ['architectural', 'mep'],
                'description': 'Insufficient clearance for plumbing access',
                'location': 'Level 2, Grid C-2',
                'severity': 'medium',
                'status': 'open'
            }
        ]

        return {
            'models_analyzed': model_ids,
            'total_clashes': len(clashes),
            'hard_clashes': len([c for c in clashes if c['type'] == 'hard']),
            'soft_clashes': len([c for c in clashes if c['type'] == 'soft']),
            'clashes': clashes
        }

    def extract_quantities(self, model_id: str) -> dict:
        """Extract material quantities from BIM model"""
        # Simulate quantity takeoff
        # In production, would extract from actual BIM model

        quantities = {
            'concrete': {
                'unit': 'cubic_yards',
                'quantity': 1250,
                'cost_per_unit': 150,
                'total_cost': 187500
            },
            'rebar': {
                'unit': 'tons',
                'quantity': 85,

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