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DDC_Skills_for_AI_Agents_in_Construction

von datadrivenconstruction · datadrivenconstruction/DDC_Skills_for_AI_Agents_in_Construction

221 construction-industry skills for Claude Code — BIM analysis, cost estimation, scheduling, and document control in one bundle.

DDC Skills for AI Agents in Construction is a domain-heavy bundle from Data Driven Construction covering BIM (IFC, Revit data), cost estimation, schedule analysis, and document workflows. Claude picks up construction vocabulary, units, and typical deliverables so it can actually be useful on job-site data instead of generic sheet munging.

▶ Demo ansehen 📦 Installieren 💡 Anwendungsfälle

Warum nutzen

Hauptfunktionen

Live-Demo

In der Praxis

ddc-skills-for-ai-agents-in-construction-skill.replay ▶ bereit
0/0

Installation

Repository des Autors · Offizielle Dokumentation zu Claude Skills

Anwendungsfälle

Praxisnahe Nutzung: DDC_Skills_for_AI_Agents_in_Construction

How to audit a BIM IFC model for basic data quality

👤 BIM coordinators and VDC teams ⏱ ~60 min advanced

Wann einsetzen: You receive an IFC file from a consultant and need a quality check.

Ablauf
  1. Parse the IFC
    Audit model.ifc — count entities by class, find missing Psets, flag orphan geometry.✓ Kopiert
    → Entity counts + quality flags
  2. Check naming and classification
    Verify wall and room naming against our company standard.✓ Kopiert
    → Per-element conformance report
  3. Produce a coordinator-ready report
    Generate an issue list the consultant can act on.✓ Kopiert
    → Ordered issue list

Ergebnis: A model audit report you can send back in under an hour.

Fallstricke
  • Huge IFC files exceed memory — Stream-parse rather than load full tree; or pre-filter by spatial structure
Kombinieren mit: filesystem

Produce a quick order-of-magnitude cost estimate

👤 Estimators, PMs, bid teams ⏱ ~30 min intermediate

Wann einsetzen: Early-phase numbers for a concept before you commit to a detailed estimate.

Ablauf
  1. Describe the project
    Concrete frame office, ~12,000 sqm, Tier-1 city, shell-only. Give me a per-sqm cost range.✓ Kopiert
    → Range with the assumptions stated
  2. Break into WBS
    Break the estimate into WBS sections with % allocations.✓ Kopiert
    → Top-level WBS with line items
  3. Flag risks
    List the top 5 cost risks for this concept.✓ Kopiert
    → Risks with impact

Ergebnis: A defensible concept estimate ready for internal review.

Fallstricke
  • Using global averages without local adjustment — Always override with local benchmarks when you have them

Review a construction schedule for common issues

👤 Schedulers and PMs ⏱ ~30 min intermediate

Wann einsetzen: You got a schedule from a subcontractor and need to check for the obvious red flags.

Ablauf
  1. Feed the schedule
    Review schedule.xlsx — flag missing logic, negative float, open ends, and unrealistic durations.✓ Kopiert
    → Categorized findings
  2. Prioritize
    Rank by impact on completion date.✓ Kopiert
    → Sorted list

Ergebnis: Quick surface-level schedule review that catches 80% of common problems.

Fallstricke
  • Missing CPM-level analysis — For real float analysis, export from P6 rather than relying on Excel

Kombinationen

Mit anderen MCPs für 10-fache Wirkung

ddc-skills-for-ai-agents-in-construction-skill + filesystem

Process a whole project folder of IFCs, schedules, and docs

Walk project/ and produce a weekly coordination packet.✓ Kopiert

Werkzeuge

Was dieses MCP bereitstellt

WerkzeugEingabenWann aufrufenKosten
bim-audit IFC path On any incoming IFC ifcopenshell compute
cost-estimation project concept Early phase 0
schedule-review schedule export Sub-submittal review 0
document-control RFIs/submittals/COs Project admin 0

Kosten & Limits

Was der Betrieb kostet

API-Kontingent
none
Tokens pro Aufruf
5–30k per task
Kosten in €
free at skill level
Tipp
Use only the sub-skills relevant to your role — this bundle is wide

Sicherheit

Rechte, Secrets, Reichweite

Credential-Speicherung: none
Datenabfluss: none

Fehlerbehebung

Häufige Fehler und Lösungen

ifcopenshell install fails

Use Python 3.10 or 3.11 and pip install ifcopenshell from a wheel matching your platform.

Prüfen: python -c 'import ifcopenshell; print(ifcopenshell.version)'
Estimates are wildly off

Override unit costs with your regional database; the skill uses generic benchmarks only

Alternativen

DDC_Skills_for_AI_Agents_in_Construction vs. andere

AlternativeWann stattdessenKompromiss
generic csv-data-summarizer-claude-skillYour construction data is CSV and you don't need BIM semanticsNo domain knowledge

Mehr

Ressourcen

📖 Offizielle README auf GitHub lesen

🐙 Offene Issues ansehen

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