construction-expert

construction-expert is a skill for Claude Code from personamanagmentlayer/pcl. It costs 54 tokens per session (2,313 once invoked), scanned A, original, Apache-2.0.

An expert guidance skill for construction management, project planning, building information modeling, safety, and construction technology. Building information modeling, or BIM, is the use of shared digital building models and project information.

In plain words
What is it for?
Helping with schedules, estimates, resources, quality, contracts, change orders, BIM, site surveys, construction sensors, safety requirements, building codes, and environmental standards.
Why use it?
It gives a coding agent construction-specific context for planning work, controlling costs, managing risks, and following industry rules.

Skill for Claude Code

Written for Claude Code: allowed-tools in frontmatter.

Good fit Helping with schedules, estimates, resources, quality, contracts, change orders, BIM, site surveys, construction sensors, safety requirements, building codes, and environmental standards.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/personamanagmentlayer/pcl/construction-expert
Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

Any agent
npx skills add personamanagmentlayer/pcl --skill construction-expert
Clone the repo
git clone --depth 1 https://github.com/personamanagmentlayer/pcl

Made for: Claude Code.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for construction-expert

README.md
[![agentmods](https://agentmods.dev/badge/skills/personamanagmentlayer/pcl/construction-expert/github.svg)](https://agentmods.dev/skills/personamanagmentlayer/pcl/construction-expert)
Your own site
<a href="https://agentmods.dev/skills/personamanagmentlayer/pcl/construction-expert"><img src="https://agentmods.dev/badge/skills/personamanagmentlayer/pcl/construction-expert/github.svg" alt="Measured on agentmods" height="20"></a>

Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

agentmods 80×15 button for construction-expert

Your own site · 80×15
<a href="https://agentmods.dev/skills/personamanagmentlayer/pcl/construction-expert"><img src="https://agentmods.dev/badge/skills/personamanagmentlayer/pcl/construction-expert.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 54 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 2,313 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe. Third-party audits
  • Socket pass 18 Mar 2026
  • Snyk pass 15 Feb 2026
  • NVIDIA SkillSpector pass 7 Sept 2026
How audits are shown
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5.1 $0.00054 $0.02313
Opus 5 $0.00027 $0.01156
Sonnet 5 $0.00011 $0.00463
Haiku 4.5 $0.00005 $0.00231

Measured 4d ago against content hash 5f270a547634, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-09, from the pricing page.

Security

Grade A, and why

construction-expert scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 4d ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

stdlib/domains/construction-expert/SKILL.md · 349 lines

How it starts

The opening of the file, as written. The whole thing — 349 lines — stays where its author put it; the contents beside it link to each section on GitHub.

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()}"

Read the full file on GitHub · 349 lines

Files

What ships with it

1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 4d ago Changed · -269 lines · +34 tokens per session 5f270a547634
  2. 9d ago First seen · 618 lines · 20 tokens per session scan A 450f03bec93a

Subscribe to this mod's changes

construction-expert is a skill published in the GitHub repository personamanagmentlayer/pcl (40 stars, last pushed yesterday), licensed Apache-2.0. It adds 54 tokens to every session and 2,313 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.