Skip to content
cccskills
FreePublished on GitHub

ai-agent-orchestration

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.

The English summary is being prepared. Showing the original description.

Run score Not tested

See how to install

Files included (1)

  • SKILL.md2.7 KB

SKILL.md (original)

Review the instructions the agent will receive before you install.

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

AgentOwnsTools it calls
Estimator agentBOQ + costCWICR search, QTO, market catalogs, costs API
Scheduler agentTime (4D)task graph, dependencies, critical path, resource leveling
Document agentSpecs & contractsPDF/OCR extraction, clause NER, submittal/RFI routing
QA agentQualityvalidation rule packs (DIN276/NRM/GAEB), reconciliation checks
Safety agentHSEchecklist generation, incident classification, regulations lookup
Supervisor agentOrchestrationroutes 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

Reviews

No reviews yet. Tell others what you thought.

Comments

No login needed. Share how it worked for you, ask a question, or note where it did not run.

No comments yet. Be the first to write one.

Comments are published right away. Do not include personal information such as email addresses or phone numbers. Up to 2 URLs.

0 / 1,000 characters

This form is protected by reCAPTCHA, and the Google Privacy Policy and Terms of Service apply.

More skills from this repository

Create 4D construction simulations by linking BIM elements to project schedules. Generate time-based visualizations, sequence analysis, and construction phasing with Gantt integration.

The English summary is being prepared. Showing the original description.

datadrivenconstruction/DDC_Skills_for_AI_Agents_in_Construction368Updated Oct 20, 2026

Analyze 5000+ IFC and Revit projects at scale for patterns, benchmarks, and insights. Big data analysis for construction.

The English summary is being prepared. Showing the original description.

datadrivenconstruction/DDC_Skills_for_AI_Agents_in_Construction368Updated Oct 20, 2026

Check construction AI systems against the EU AI Act (Regulation 2024/1689): classify risk of estimation, scheduling, CV and agent tools, document transparency, keep human oversight. Use when deploying or auditing AI in construction.

The English summary is being prepared. Showing the original description.

datadrivenconstruction/DDC_Skills_for_AI_Agents_in_Construction368Updated Oct 20, 2026

Create Apache Airflow DAGs for construction data pipelines. Orchestrate ETL, validation, and reporting workflows.

The English summary is being prepared. Showing the original description.

datadrivenconstruction/DDC_Skills_for_AI_Agents_in_Construction368Updated Oct 20, 2026

Manage as-built documentation for project closeout. Track drawing markups, coordinate updates, and verify completeness.

The English summary is being prepared. Showing the original description.

datadrivenconstruction/DDC_Skills_for_AI_Agents_in_Construction368Updated Oct 20, 2026

Automate as-built documentation and digital handover for construction. Compile project records, generate O&M manuals, create asset databases, and ensure complete project closeout.

The English summary is being prepared. Showing the original description.

datadrivenconstruction/DDC_Skills_for_AI_Agents_in_Construction368Updated Oct 20, 2026

See all skills by datadrivenconstruction

Report a problem with this skill