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DDC_Skills_for_AI_Agents_in_Construction

par 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.

▶ Voir la démo 📦 Installer 💡 Cas d'usage

Pourquoi l'utiliser

Fonctionnalités clés

Démo en direct

Aperçu en pratique

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

Installation

Dépôt de l’auteur · Documentation officielle des Skills Claude

Cas d'usage

Usages concrets : 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

Quand l'utiliser : You receive an IFC file from a consultant and need a quality check.

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

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

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

Produce a quick order-of-magnitude cost estimate

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

Quand l'utiliser : Early-phase numbers for a concept before you commit to a detailed estimate.

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

Résultat : A defensible concept estimate ready for internal review.

Pièges
  • 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

Quand l'utiliser : You got a schedule from a subcontractor and need to check for the obvious red flags.

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

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

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

Combinaisons

Associez-le à d'autres MCPs pour un effet X10

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.✓ Copié

Outils

Ce que ce MCP expose

OutilEntréesQuand appelerCoût
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

Coût et limites

Coût d'exécution

Quota d'API
none
Tokens par appel
5–30k per task
Monétaire
free at skill level
Astuce
Use only the sub-skills relevant to your role — this bundle is wide

Sécurité

Permissions, secrets, portée

Stockage des identifiants : none
Sortie de données : none

Dépannage

Erreurs courantes et correctifs

ifcopenshell install fails

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

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

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

Alternatives

DDC_Skills_for_AI_Agents_in_Construction vs autres

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

Plus

Ressources

📖 Lire le README officiel sur GitHub

🐙 Voir les issues ouvertes

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