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.
npx skills add datadrivenconstruction/DDC_Skills_for_AI_Agents_in_Construction --skill bim-consistency-checkergit clone --depth 1 https://github.com/datadrivenconstruction/DDC_Skills_for_AI_Agents_in_ConstructionWrote 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.
[](https://agentmods.dev/skills/datadrivenconstruction/ddc_skills_for_ai_agents_in_construction/bim-consistency-checker)<a href="https://agentmods.dev/skills/datadrivenconstruction/ddc_skills_for_ai_agents_in_construction/bim-consistency-checker"><img src="https://agentmods.dev/badge/skills/datadrivenconstruction/ddc_skills_for_ai_agents_in_construction/bim-consistency-checker/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.
<a href="https://agentmods.dev/skills/datadrivenconstruction/ddc_skills_for_ai_agents_in_construction/bim-consistency-checker"><img src="https://agentmods.dev/badge/skills/datadrivenconstruction/ddc_skills_for_ai_agents_in_construction/bim-consistency-checker.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00028 | $0.03817 |
| Opus 5 | $0.00014 | $0.01909 |
| Sonnet 5 | $0.00006 | $0.00763 |
| Haiku 4.5 | $0.00003 | $0.00382 |
Grade A, and why
bim-consistency-checker 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 9d 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.
Copies of this mod
1 near-identical copy found in the catalogue:
- bim-consistency-checker — 100% identical, 0 lines differ
How it starts
The opening of the file, as written. The whole thing — 491 lines — stays where its author put it; the contents beside it link to each section on GitHub.
BIM Consistency Checker for Construction
Overview
Validate BIM model consistency including naming conventions, parameter completeness, spatial relationships, classification compliance, and cross-reference integrity.
Business Case
BIM consistency checking ensures:
- Data Quality: Complete and accurate model data
- Interoperability: Models work across platforms
- Coordination: Consistent information for all trades
- Deliverable Compliance: Meet BIM execution plan requirements
Technical Implementation
from dataclasses import dataclass, field
from typing import List, Dict, Any, Optional, Set
from enum import Enum
import re
class CheckSeverity(Enum):
ERROR = "error"
WARNING = "warning"
INFO = "info"
class CheckCategory(Enum):
NAMING = "naming"
PARAMETERS = "parameters"
SPATIAL = "spatial"
CLASSIFICATION = "classification"
GEOMETRY = "geometry"
RELATIONSHIPS = "relationships"
@dataclass
class ConsistencyIssue:
element_id: str
element_name: str
category: CheckCategory
severity: CheckSeverity
rule: str
message: str
suggestion: str = ""
@dataclass
class ConsistencyReport:
model_name: str
total_elements: int
elements_checked: int
issues: List[ConsistencyIssue]
issues_by_category: Dict[str, int]
issues_by_severity: Dict[str, int]
pass_rate: float
@dataclass
class NamingConvention:
element_type: str
pattern: str
description: str
examples: List[str]
class BIMConsistencyChecker:
"""Check BIM model consistency and data quality."""
# Default naming conventions
DEFAULT_NAMING_RULES = [
NamingConvention(
element_type='Level',
pattern=r'^(L|Level)\s*\d{1,2}$|^(B|Basement)\s*\d?$|^(R|Roof)$',
description='Levels should follow L01, Level 1, B1, Roof pattern',
examples=['L01', 'Level 1', 'B1', 'Roof']
),
NamingConvention(
element_type='Grid',
pattern=r'^[A-Z]$|^\d{1,2}$|^[A-Z]\.\d$',
description='Grids should be single letters (A-Z) or numbers',
examples=['A', '1', 'A.1']
),
NamingConvention(
element_type='Room',
pattern=r'^\d{3,4}[A-Z]?\s*-?\s*.+',
description='Rooms should have number and name (101 - Office)',
examples=['101 - Office', '201A Conference']
),
NamingConvention(
element_type='Wall',
pattern=r'^(INT|EXT|CW|CMU|GYP)[-_].+',
description='Walls should have type prefix',
examples=['INT-GYP-1HR', 'EXT-CMU-8IN']
),
NamingConvention(
element_type='Door',
pattern=r'^[A-Z]?\d{2,3}[A-Z]?$',
description='Doors should follow type numbering',
examples=['101', 'A101', '101A']
),
]
# Required parameters by element type
REQUIRED_PARAMETERS = {
'Wall': ['Fire Rating', 'Function', 'Structural'],
'Door': ['Fire Rating', 'Width', 'Height', 'Frame Material'],
'Room': ['Name', 'Number', 'Area', 'Department'],
'Window': ['Width', 'Height', 'Glass Type'],
'Floor': ['Structural', 'Fire Rating'],
'Ceiling': ['Height', 'Type'],
'Column': ['Structural Material', 'Shape'],
'Beam': ['Structural Material', 'Size'],
}
def __init__(self):
self.naming_rules: List[NamingConvention] = list(self.DEFAULT_NAMING_RULES)
self.required_params: Dict[str, List[str]] = dict(self.REQUIRED_PARAMETERS)
self.issues: List[ConsistencyIssue] = []
def add_naming_rule(self, rule: NamingConvention):
"""Add custom naming convention rule."""
self.naming_rules.append(rule)
def set_required_parameters(self, element_type: str, parameters: List[str]):
"""Set required parameters for an element type."""
self.required_params[element_type] = parameters
def check_model(self, elements: List[Dict]) -> ConsistencyReport:
"""Run all consistency checks on model elements."""
self.issues = []
for element in elements:
self._check_naming(element)
self._check_parameters(element)
self._check_spatial(element)
self._check_classification(element)
self._check_geometry(element)
# Cross-element checks
self._check_relationships(elements)
self._check_duplicates(elements)
# Calculate statistics
issues_by_category = {}
issues_by_severity = {}
for issue in self.issues:
cat = issue.category.value
sev = issue.severity.value
issues_by_category[cat] = issues_by_category.get(cat, 0) + 1
issues_by_severity[sev] = issues_by_severity.get(sev, 0) + 1
elements_with_issues = len(set(i.element_id for i in self.issues))
pass_rate = (len(elements) - elements_with_issues) / len(elements) * 100 if elements else 100
return ConsistencyReport(
model_name='Model',
total_elements=len(elements),
elements_checked=len(elements),
issues=self.issues,
issues_by_category=issues_by_category,
issues_by_severity=issues_by_severity,
pass_rate=pass_rate
)
def _check_naming(self, element: Dict):
"""Check element naming conventions."""
element_type = element.get('type', '')
name = element.get('name', '')
element_id = element.get('id', '')
if not name:
self.issues.append(ConsistencyIssue(
element_id=element_id,
element_name='(no name)',
category=CheckCategory.NAMING,
severity=CheckSeverity.ERROR,
rule='Name Required',
message='Element has no name',
suggestion='Assign a descriptive name following conventions'
))
return
# Check against naming rules
for rule in self.naming_rules:
if rule.element_type.lower() in element_type.lower():
if not re.match(rule.pattern, name, re.IGNORECASE):
self.issues.append(ConsistencyIssue(
element_id=element_id,
element_name=name,
category=CheckCategory.NAMING,
severity=CheckSeverity.WARNING,
rule=f'{rule.element_type} Naming',
message=f'Name "{name}" does not follow convention',
suggestion=f'{rule.description}. Examples: {", ".join(rule.examples)}'
))
# Check for special characters
if re.search(r'[<>:"/\\|?*]', name):
self.issues.append(ConsistencyIssue(
element_id=element_id,
element_name=name,
category=CheckCategory.NAMING,
severity=CheckSeverity.ERROR,
rule='Invalid Characters',
message='Name contains invalid characters',
suggestion='Remove special characters: < > : " / \\ | ? *'
))
def _check_parameters(self, element: Dict):
"""Check parameter completeness."""
element_type = element.get('type', '')
element_id = element.get('id', '')
name = element.get('name', '')
params = element.get('parameters', {})
# Check required parameters
required = self.required_params.get(element_type, [])
for param in required:
if param not in params or params[param] in [None, '', 'None']:
self.issues.append(ConsistencyIssue(
element_id=element_id,
element_name=name,
category=CheckCategory.PARAMETERS,
severity=CheckSeverity.WARNING,
rule='Required Parameter',
message=f'Missing required parameter: {param}',
suggestion=f'Set value for {param}'
))
# Check for default/placeholder values
placeholder_values = ['TBD', 'XXX', 'TODO', 'CHANGE', '<default>']
for param, value in params.items():
if str(value).upper() in placeholder_values:
self.issues.append(ConsistencyIssue(
element_id=element_id,
element_name=name,
category=CheckCategory.PARAMETERS,
severity=CheckSeverity.WARNING,
rule='Placeholder Value',
message=f'Parameter "{param}" has placeholder value: {value}',
suggestion='Replace with actual value'
))
def _check_spatial(self, element: Dict):
"""Check spatial consistency."""
element_id = element.get('id', '')
name = element.get('name', '')
element_type = element.get('type', '')
# Check level assignment
level = element.get('level')
requires_level = element_type in ['Wall', 'Door', 'Window', 'Room', 'Floor', 'Ceiling']
if requires_level and not level:
self.issues.append(ConsistencyIssue(
element_id=element_id,
element_name=name,
category=CheckCategory.SPATIAL,
severity=CheckSeverity.ERROR,
rule='Level Assignment',
message='Element not assigned to a level',
suggestion='Assign element to appropriate level'
))
# Check room bounding
if element_type == 'Wall':
room_bounding = element.get('room_bounding', True)
if not room_bounding:
self.issues.append(ConsistencyIssue(
element_id=element_id,
element_name=name,
category=CheckCategory.SPATIAL,
severity=CheckSeverity.INFO,
rule='Room Bounding',
message='Wall is not room bounding',
suggestion='Verify this is intentional'
))
def _check_classification(self, element: Dict):
"""Check classification codes."""
element_id = element.get('id', '')
name = element.get('name', '')
params = element.get('parameters', {})
# Check for classification
classification = params.get('Classification') or params.get('OmniClass') or params.get('UniFormat')
if not classification:
self.issues.append(ConsistencyIssue(
element_id=element_id,
element_name=name,
category=CheckCategory.CLASSIFICATION,
severity=CheckSeverity.INFO,
rule='Classification Required',
message='Element has no classification code',
suggestion='Assign OmniClass, UniFormat, or other classification'
))
else:
# Validate format
if not re.match(r'^\d{2}[-\s]?\d{2}[-\s]?\d{2}', str(classification)):
self.issues.append(ConsistencyIssue(
element_id=element_id,
element_name=name,
category=CheckCategory.CLASSIFICATION,
severity=CheckSeverity.WARNING,
rule='Classification Format',
message=f'Invalid classification format: {classification}',
suggestion='Use standard format (XX XX XX)'
))
def _check_geometry(self, element: Dict):
"""Check geometry validity."""
element_id = element.get('id', '')
name = element.get('name', '')
geometry = element.get('geometry', {})
# Check for zero area/volume
area = geometry.get('area', 0)
volume = geometry.get('volume', 0)
if area == 0 and volume == 0 and element.get('type') not in ['Grid', 'Level', 'ReferencePlane']:
self.issues.append(ConsistencyIssue(
element_id=element_id,
element_name=name,
category=CheckCategory.GEOMETRY,
severity=CheckSeverity.ERROR,
rule='Zero Geometry',
message='Element has zero area and volume',
suggestion='Check element geometry is valid'
))
# Check for extremely small elements
if 0 < area < 0.01: # Less than 0.01 m² or ft²
self.issues.append(ConsistencyIssue(
element_id=element_id,
element_name=name,
category=CheckCategory.GEOMETRY,
severity=CheckSeverity.WARNING,
rule='Tiny Element',
message=f'Element has very small area: {area}',
suggestion='Verify element is intentional and not a modeling error'
))
def _check_relationships(self, elements: List[Dict]):
"""Check cross-element relationships."""
# Build lookup
elements_by_id = {e['id']: e for e in elements}
elements_by_type = {}
for e in elements:
t = e.get('type', '')
if t not in elements_by_type:
elements_by_type[t] = []
elements_by_type[t].append(e)
# Check door-wall relationships
for door in elements_by_type.get('Door', []):
host_wall = door.get('host_id')
if host_wall and host_wall not in elements_by_id:
self.issues.append(ConsistencyIssue(
element_id=door['id'],
element_name=door.get('name', ''),
category=CheckCategory.RELATIONSHIPS,
severity=CheckSeverity.ERROR,
rule='Invalid Host',
message=f'Door references non-existent wall: {host_wall}',
suggestion='Rehost door to valid wall'
))
# Check room enclosure
for room in elements_by_type.get('Room', []):
if not room.get('is_bounded', True):
self.issues.append(ConsistencyIssue(
element_id=room['id'],
element_name=room.get('name', ''),
category=CheckCategory.RELATIONSHIPS,
severity=CheckSeverity.ERROR,
rule='Unbounded Room',
message='Room is not properly bounded',
suggestion='Check room boundary walls'
))
def _check_duplicates(self, elements: List[Dict]):
"""Check for duplicate elements."""
seen: Dict[str, List[Dict]] = {}
for element in elements:
# Create signature for duplicate detection
sig_parts = [
element.get('type', ''),
str(element.get('geometry', {}).get('location', '')),
element.get('name', '')
]
signature = '|'.join(sig_parts)
if signature in seen:
for dup in seen[signature]:
self.issues.append(ConsistencyIssue(
element_id=element['id'],
element_name=element.get('name', ''),
category=CheckCategory.RELATIONSHIPS,
severity=CheckSeverity.WARNING,
rule='Duplicate Element',
message=f'Possible duplicate of element {dup["id"]}',
suggestion='Review and remove duplicate if confirmed'
))
if signature not in seen:
seen[signature] = []
seen[signature].append(element)
def generate_report(self, report: ConsistencyReport) -> str:
"""Generate consistency check report."""
lines = ["# BIM Consistency Check Report", ""]
lines.append(f"**Model:** {report.model_name}")
lines.append(f"**Elements Checked:** {report.elements_checked}")
lines.append(f"**Pass Rate:** {report.pass_rate:.1f}%")
lines.append("")
# Summary
lines.append("## Summary")
lines.append(f"- **Total Issues:** {len(report.issues)}")
lines.append(f"- Errors: {report.issues_by_severity.get('error', 0)}")
lines.append(f"- Warnings: {report.issues_by_severity.get('warning', 0)}")
lines.append(f"- Info: {report.issues_by_severity.get('info', 0)}")
lines.append("")
# By category
lines.append("## Issues by Category")
for cat, count in sorted(report.issues_by_category.items()):
lines.append(f"- {cat}: {count}")
lines.append("")
# Critical issues
errors = [i for i in report.issues if i.severity == CheckSeverity.ERROR]
if errors:
lines.append("## Critical Issues (Errors)")
for issue in errors[:20]:
lines.append(f"\n### {issue.element_name} ({issue.element_id})")
lines.append(f"- **Rule:** {issue.rule}")
lines.append(f"- **Issue:** {issue.message}")
lines.append(f"- **Fix:** {issue.suggestion}")
return "\n".join(lines)
What ships with it
2 files 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.
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.
- 9d ago First seen · 491 lines · 28 tokens per session scan A 28aad113a06d
bim-consistency-checker is a skill published in the GitHub repository datadrivenconstruction/DDC_Skills_for_AI_Agents_in_Construction (310 stars, last pushed 21d ago), licensed MIT. It adds 28 tokens to every session and 3,817 once invoked, about $0.0001 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 2026-09-03.
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