Check data compliance with construction standards. Validate data against ISO 19650, IFC, COBie, UniFormat standards.
npx skills add https://github.com/datadrivenconstruction/DDC_Skills_for_AI_Agents_in_Construction --skill standards-compliance-checker
Construction data compliance challenges:
Automated compliance checking against major construction data standards including ISO 19650, IFC, COBie, and UniFormat.
from typing import Dict, Any, List, Optional
from dataclasses import dataclass, field
from enum import Enum
import re
class Standard(Enum):
ISO_19650 = "iso_19650"
IFC = "ifc"
COBIE = "cobie"
UNIFORMAT = "uniformat"
OMNICLASS = "omniclass"
MASTERFORMAT = "masterformat"
class ComplianceLevel(Enum):
COMPLIANT = "compliant"
MINOR_ISSUES = "minor_issues"
MAJOR_ISSUES = "major_issues"
NON_COMPLIANT = "non_compliant"
@dataclass
class ComplianceIssue:
rule_id: str
rule_name: str
severity: str # error, warning, info
message: str
field: str = ""
value: Any = None
@dataclass
class ComplianceReport:
standard: Standard
total_rules: int
passed: int
failed: int
warnings: int
compliance_level: ComplianceLevel
issues: List[ComplianceIssue] = field(default_factory=list)
class StandardsComplianceChecker:
"""Check compliance with construction data standards."""
def __init__(self):
self.rules: Dict[Standard, List[Dict]] = self._load_rules()
def _load_rules(self) -> Dict[Standard, List[Dict]]:
"""Load compliance rules for each standard."""
return {
Standard.ISO_19650: [
{"id": "ISO-001", "name": "File naming convention", "field": "filename",
"pattern": r"^[A-Z]{2,6}-[A-Z]{2,4}-[A-Z]{2,3}-[A-Z0-9]{2,4}-[A-Z]{2,3}-[A-Z]{2,4}-[A-Z0-9]{3,8}$"},
{"id": "ISO-002", "name": "Status code valid", "field": "status",
"values": ["WIP", "S0", "S1", "S2", "S3", "S4", "A", "B", "CR"]},
{"id": "ISO-003", "name": "Revision format", "field": "revision",
"pattern": r"^P[0-9]{2}|C[0-9]{2}$"},
],
Standard.IFC: [
{"id": "IFC-001", "name": "GUID format", "field": "global_id",
"pattern": r"^[0-9A-Za-z_$]{22}$"},
{"id": "IFC-002", "name": "Name required", "field": "name", "required": True},
{"id": "IFC-003", "name": "ObjectType defined", "field": "object_type", "required": True},
],
Standard.COBIE: [
{"id": "COB-001", "name": "Facility name", "field": "facility_name", "required": True},
{"id": "COB-002", "name": "Space name format", "field": "space_name",
"pattern": r"^[A-Z0-9]{2,10}[-_]?[A-Z0-9]{0,10}$"},
{"id": "COB-003", "name": "Component type", "field": "component_type", "required": True},
{"id": "COB-004", "name": "Manufacturer info", "field": "manufacturer", "required": True},
],
Standard.UNIFORMAT: [
{"id": "UNI-001", "name": "Level 1 code", "field": "level1",
"values": ["A", "B", "C", "D", "E", "F", "G", "Z"]},
{"id": "UNI-002", "name": "Code format", "field": "code",
"pattern": r"^[A-G][0-9]{4}$"},
],
Standard.MASTERFORMAT: [
{"id": "MF-001", "name": "Division format", "field": "division",
"pattern": r"^[0-9]{2}$"},
{"id": "MF-002", "name": "Section format", "field": "section",
"pattern": r"^[0-9]{2}\s?[0-9]{2}\s?[0-9]{2}(\.[0-9]{2})?$"},
]
}
def check_compliance(self, data: Dict[str, Any],
standard: Standard) -> ComplianceReport:
"""Check data against specified standard."""
rules = self.rules.get(standard, [])
issues = []
passed = 0
failed = 0
warnings = 0
for rule in rules:
result = self._check_rule(data, rule)
if result:
issues.append(result)
if result.severity == "error":
failed += 1
else:
warnings += 1
else:
passed += 1
# Determine compliance level
if failed == 0 and warnings == 0:
level = ComplianceLevel.COMPLIANT
elif failed == 0:
level = ComplianceLevel.MINOR_ISSUES
elif failed <= len(rules) * 0.3:
level = ComplianceLevel.MAJOR_ISSUES
else:
level = ComplianceLevel.NON_COMPLIANT
return ComplianceReport(
standard=standard,
total_rules=len(rules),
passed=passed,
failed=failed,
warnings=warnings,
compliance_level=level,
issues=issues
)
def _check_rule(self, data: Dict[str, Any], rule: Dict) -> Optional[ComplianceIssue]:
"""Check single compliance rule."""
field = rule.get('field', '')
value = data.get(field)
# Required check
if rule.get('required') and (value is None or value == ''):
return ComplianceIssue(
rule_id=rule['id'],
rule_name=rule['name'],
severity="error",
message=f"Required field '{field}' is missing",
field=field
)
# Skip other checks if value is empty
if value is None or value == '':
return None
# Pattern check
if 'pattern' in rule:
if not re.match(rule['pattern'], str(value)):
return ComplianceIssue(
rule_id=rule['id'],
rule_name=rule['name'],
severity="error",
message=f"Field '{field}' does not match required format",
field=field,
value=value
)
# Allowed values check
if 'values' in rule:
if value not in rule['values']:
return ComplianceIssue(
rule_id=rule['id'],
rule_name=rule['name'],
severity="error",
message=f"Field '{field}' must be one of: {rule['values']}",
field=field,
value=value
)
return None
def check_multiple_standards(self, data: Dict[str, Any],
standards: List[Standard]) -> Dict[str, ComplianceReport]:
"""Check data against multiple standards."""
reports = {}
for standard in standards:
reports[standard.value] = self.check_compliance(data, standard)
return reports
def check_batch(self, records: List[Dict[str, Any]],
standard: Standard) -> Dict[str, Any]:
"""Check multiple records against standard."""
all_issues = []
compliant_count = 0
for i, record in enumerate(records):
report = self.check_compliance(record, standard)
if report.compliance_level == ComplianceLevel.COMPLIANT:
compliant_count += 1
for issue in report.issues:
all_issues.append({
'record_index': i,
'rule_id': issue.rule_id,
'field': issue.field,
'message': issue.message
})
return {
'standard': standard.value,
'total_records': len(records),
'compliant_records': compliant_count,
'compliance_rate': round(compliant_count / len(records) * 100, 1) if records else 0,
'total_issues': len(all_issues),
'issues': all_issues
}
def add_custom_rule(self, standard: Standard, rule: Dict):
"""Add custom compliance rule."""
if standard not in self.rules:
self.rules[standard] = []
self.rules[standard].append(rule)
def generate_report_summary(self, report: ComplianceReport) -> str:
"""Generate human-readable report summary."""
lines = [
f"Compliance Report: {report.standard.value.upper()}",
"=" * 40,
f"Total Rules: {report.total_rules}",
f"Passed: {report.passed}",
f"Failed: {report.failed}",
f"Warnings: {report.warnings}",
f"Status: {report.compliance_level.value.upper()}",
"",
"Issues:"
]
for issue in report.issues:
lines.append(f" [{issue.severity.upper()}] {issue.rule_id}: {issue.message}")
return "\n".join(lines)
# Initialize checker
checker = StandardsComplianceChecker()
# Check ISO 19650 compliance
data = {
"filename": "PRJ-ARC-MOD-0001-DWG-PLAN-001",
"status": "S3",
"revision": "P01"
}
report = checker.check_compliance(data, Standard.ISO_19650)
print(f"Compliance: {report.compliance_level.value}")
print(f"Passed: {report.passed}/{report.total_rules}")
cobie_data = {
"facility_name": "Building A",
"space_name": "OFFICE-101",
"component_type": "HVAC_Unit",
"manufacturer": "Carrier"
}
report = checker.check_compliance(cobie_data, Standard.COBIE)
records = [{"filename": "...", "status": "..."}, ...]
batch_report = checker.check_batch(records, Standard.ISO_19650)
print(f"Compliance rate: {batch_report['compliance_rate']}%")
reports = checker.check_multiple_standards(
data,
[Standard.ISO_19650, Standard.IFC]
)
Integration with protocols.io API for managing scientific protocols. This skill should be used when working with protocols.io to search, create, update, or publish protocols; manage protocol steps and materials; handle discussions and comments; organize workspaces; upload and manage files; or integrate protocols.io functionality into workflows. Applicable for protocol discovery, collaborative protocol development, experiment tracking, lab protocol management, and scientific documentation.
Analyzes job descriptions and generates tailored resumes that highlight relevant experience, skills, and achievements to maximize interview chances
Generate Excalidraw diagrams from natural language descriptions. Use when asked to "create a diagram", "make a flowchart", "visualize a process", "draw a system architecture", "create a mind map", or "generate an Excalidraw file". Supports flowcharts, relationship diagrams, mind maps, and system architecture diagrams. Outputs .excalidraw JSON files that can be opened directly in Excalidraw.
Build and distribute Expo development clients locally or via TestFlight
Use when you have a written implementation plan to execute in a separate session with review checkpoints
Data structure for annotated matrices in single-cell analysis. Use when working with .h5ad files or integrating with the scverse ecosystem. This is the data format skill—for analysis workflows use scanpy; for probabilistic models use scvi-tools; for population-scale queries use cellxgene-census.
Benchling R&D platform integration. Access registry (DNA, proteins), inventory, ELN entries, workflows via API, build Benchling Apps, query Data Warehouse, for lab data management automation.
Comprehensive molecular biology toolkit. Use for sequence manipulation, file parsing (FASTA/GenBank/PDB), phylogenetics, and programmatic NCBI/PubMed access (Bio.Entrez). Best for batch processing, custom bioinformatics pipelines, BLAST automation. For quick lookups use gget; for multi-service integration use bioservices.
Take datadrivenconstruction/standards-compliance-checker from the repository into ~/.claude/skills for personal
use, or into .claude/skills inside a project.
The agent identifies a skill by the name field in its header. Two skills with the
same name cannot sit side by side — one of them will be ignored.