Orchestrate multiple AI agents for construction workflows: estimator, scheduler, document, QA and safety agents coordinated by a supervisor agent, with human checkpoints. Use when automating end-to-end project processes with agentic AI.
Scanned 9/5/2026
Install to Claude Code
npx -y skills add datadrivenconstruction/DDC_Skills_for_AI_Agents_in_Construction --skill ai-agent-orchestration --agent claude-codeInstalls into .claude/skills of the current project.
Are you the author of Ai Agent Orchestration?
Add the live security badge to your README — it updates automatically with every re-scan.
[](https://www.skillsdirectory.com/skills/datadrivenconstruction-ai-agent-orchestration)More formats (shields.io, HTML) on the badges page.
---
name: "ai-agent-orchestration"
description: "Orchestrate multiple AI agents for construction workflows: estimator, scheduler, document, QA and safety agents coordinated by a supervisor agent, with human checkpoints. Use when automating end-to-end project processes with agentic AI."
---
# AI Agent Orchestration for Construction (2026)
## Why agents now
2026 construction automation is agentic: not single prompts, but specialized agents that own a domain (estimating, scheduling, documents, QA, safety), share a common data spine (the ERP + CWICR cost bases), and are coordinated by a supervisor with human checkpoints.
## Agent roles
| Agent | Owns | Tools it calls |
|---|---|---|
| **Estimator agent** | BOQ + cost | CWICR search, QTO, market catalogs, `costs` API |
| **Scheduler agent** | Time (4D) | task graph, dependencies, critical path, resource leveling |
| **Document agent** | Specs & contracts | PDF/OCR extraction, clause NER, submittal/RFI routing |
| **QA agent** | Quality | validation rule packs (DIN276/NRM/GAEB), reconciliation checks |
| **Safety agent** | HSE | checklist generation, incident classification, regulations lookup |
| **Supervisor agent** | Orchestration | routes tasks, resolves conflicts, escalates to humans |
## Coordination patterns
```
Supervisor ──► Estimator ──► BOQ draft ──► human approves
│ ▲
├──► Document ──► scope extracted (specs) ─┘
├──► Scheduler ──► draft schedule from BOQ quantities
└──► QA ──► validate BOQ + schedule, report violations
```
1. **Data spine first** — all agents read/write the same ERP data (BOQ, tasks, cost items); no agent keeps private state.
2. **Human checkpoints** — binding numbers (prices, contracts) always pass a human gate.
3. **Deterministic validation** — QA uses arithmetic and rules, not LLM judgement, for reconciliation (e.g. `qty × price = cost`, markup conventions).
4. **Idempotent actions** — every agent action is re-runnable (the ERP import is idempotent on `(code, region)`; use it as the model).
## Guardrails
- Never let an agent invent a price: unpriced bases stay rate 0 until a market sheet exists.
- Confidence-scored matches below threshold go to a human.
- Log every agent decision with its inputs (the ERP's usage ledger pattern).
- EU AI Act (2024/1689): construction estimation assistance is low/limited risk, but keep human oversight for safety-critical decisions.
## Resources
- OpenConstructionERP: https://github.com/datadrivenconstruction/OpenConstructionERP
- CWICR cost bases: https://github.com/datadrivenconstruction/OpenConstructionEstimate-DDC-CWICR
- Anthropic multi-agent patterns: https://www.anthropic.com/engineering/building-effective-agents

Is this your skill, or is something wrong with this listing? Request removal or report an issue. Author removals are honored within 72 hours.
No comments yet. Be the first to comment!