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DDC_Skills_for_AI_Agents_in_Construction

por 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.

Por que usar

Principais recursos

Demo ao vivo

Como fica na prática

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

Instalar

Escolha seu cliente

~/Library/Application Support/Claude/claude_desktop_config.json  · Windows: %APPDATA%\Claude\claude_desktop_config.json
{
  "mcpServers": {
    "ddc-skills-for-ai-agents-in-construction-skill": {
      "command": "git",
      "args": [
        "clone",
        "https://github.com/datadrivenconstruction/DDC_Skills_for_AI_Agents_in_Construction",
        "~/.claude/skills/DDC_Skills_for_AI_Agents_in_Construction"
      ],
      "_inferred": true
    }
  }
}

Abra Claude Desktop → Settings → Developer → Edit Config. Reinicie após salvar.

~/.cursor/mcp.json · .cursor/mcp.json
{
  "mcpServers": {
    "ddc-skills-for-ai-agents-in-construction-skill": {
      "command": "git",
      "args": [
        "clone",
        "https://github.com/datadrivenconstruction/DDC_Skills_for_AI_Agents_in_Construction",
        "~/.claude/skills/DDC_Skills_for_AI_Agents_in_Construction"
      ],
      "_inferred": true
    }
  }
}

Cursor usa o mesmo esquema mcpServers que o Claude Desktop. Config de projeto vence a global.

VS Code → Cline → MCP Servers → Edit
{
  "mcpServers": {
    "ddc-skills-for-ai-agents-in-construction-skill": {
      "command": "git",
      "args": [
        "clone",
        "https://github.com/datadrivenconstruction/DDC_Skills_for_AI_Agents_in_Construction",
        "~/.claude/skills/DDC_Skills_for_AI_Agents_in_Construction"
      ],
      "_inferred": true
    }
  }
}

Clique no ícone MCP Servers na barra lateral do Cline, depois "Edit Configuration".

~/.codeium/windsurf/mcp_config.json
{
  "mcpServers": {
    "ddc-skills-for-ai-agents-in-construction-skill": {
      "command": "git",
      "args": [
        "clone",
        "https://github.com/datadrivenconstruction/DDC_Skills_for_AI_Agents_in_Construction",
        "~/.claude/skills/DDC_Skills_for_AI_Agents_in_Construction"
      ],
      "_inferred": true
    }
  }
}

Mesmo formato do Claude Desktop. Reinicie o Windsurf para aplicar.

~/.continue/config.json
{
  "mcpServers": [
    {
      "name": "ddc-skills-for-ai-agents-in-construction-skill",
      "command": "git",
      "args": [
        "clone",
        "https://github.com/datadrivenconstruction/DDC_Skills_for_AI_Agents_in_Construction",
        "~/.claude/skills/DDC_Skills_for_AI_Agents_in_Construction"
      ]
    }
  ]
}

O Continue usa um array de objetos de servidor em vez de um map.

~/.config/zed/settings.json
{
  "context_servers": {
    "ddc-skills-for-ai-agents-in-construction-skill": {
      "command": {
        "path": "git",
        "args": [
          "clone",
          "https://github.com/datadrivenconstruction/DDC_Skills_for_AI_Agents_in_Construction",
          "~/.claude/skills/DDC_Skills_for_AI_Agents_in_Construction"
        ]
      }
    }
  }
}

Adicione em context_servers. Zed recarrega automaticamente ao salvar.

claude mcp add ddc-skills-for-ai-agents-in-construction-skill -- git clone https://github.com/datadrivenconstruction/DDC_Skills_for_AI_Agents_in_Construction ~/.claude/skills/DDC_Skills_for_AI_Agents_in_Construction

Uma linha só. Verifique com claude mcp list. Remova com claude mcp remove.

Casos de uso

Usos do mundo real: 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

Quando usar: You receive an IFC file from a consultant and need a quality check.

Pré-requisitos
  • Python with ifcopenshell — pip install ifcopenshell
  • Skill cloned — git clone https://github.com/datadrivenconstruction/DDC_Skills_for_AI_Agents_in_Construction ~/.claude/skills/DDC_Skills_for_AI_Agents_in_Construction
Fluxo
  1. Parse the IFC
    Audit model.ifc — count entities by class, find missing Psets, flag orphan geometry.✓ Copiado
    → Entity counts + quality flags
  2. Check naming and classification
    Verify wall and room naming against our company standard.✓ Copiado
    → Per-element conformance report
  3. Produce a coordinator-ready report
    Generate an issue list the consultant can act on.✓ Copiado
    → Ordered issue list

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

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

Produce a quick order-of-magnitude cost estimate

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

Quando usar: Early-phase numbers for a concept before you commit to a detailed estimate.

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

Resultado: A defensible concept estimate ready for internal review.

Armadilhas
  • 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

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

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

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

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

Combinações

Combine com outros MCPs para 10× de alavancagem

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.✓ Copiado

Ferramentas

O que este MCP expõe

FerramentaEntradasQuando chamarCusto
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

Custo e limites

O que custa rodar

Cota de API
none
Tokens por chamada
5–30k per task
Monetário
free at skill level
Dica
Use only the sub-skills relevant to your role — this bundle is wide

Segurança

Permissões, segredos, alcance

Armazenamento de credenciais: none
Saída de dados: none

Solução de problemas

Erros comuns e correções

ifcopenshell install fails

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

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

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

Alternativas

DDC_Skills_for_AI_Agents_in_Construction vs. outros

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

Mais

Recursos

📖 Leia o README oficial no GitHub

🐙 Ver issues abertas

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