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Challenge

World Cup Stadium Schedule Crew with CrewAI

Morocco tendered a $291m package for the World Cup 2030 stadium construction. Build a multi-agent collaborative crew using CrewAI where specialized agents (Civil Engineer, Procurement Specialist, Risk Officer) collaborate to evaluate construction schedule conflicts. Achieve complete conflict detection across a 500-task gantt chart.

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Challenge brief

What you are building

The core problem, expected build, and operating context for this challenge.

Orchestrate role-playing AI agents using CrewAI to simulate schedule alignment and vendor coordination for major World Cup stadium construction packages.

Delivery guide

How work is evaluated

Evaluation

Evaluates the Crew's ability to identify overlapping critical path dependencies and generate resolutions.

Datasets

Shared data for this challenge

Review public datasets and any private uploads tied to your build.

Evaluation rubric

How submissions are scored

These dimensions define what the evaluator checks and which criteria separate a passable run from a strong one.

Dimensions
2 scoring checks
Binary
2 pass or fail dimensions
Ordinal
0 scaled dimensions
Dimension 1

conflict_completeness

Ensures all resource collisions in input are detected

Binary check

This dimension contributes its full weight only when the submission satisfies the requirement. Partial credit is not awarded.

Dimension 2

recommendation_feasibility

Score measuring whether proposed timeline resolution maintains final deadline • target: 0.95 • range: 0-1

Binary check

This dimension contributes its full weight only when the submission satisfies the requirement. Partial credit is not awarded.

Learning goals

What you should walk away with

  • Define CrewAI agents with specific roles, goals, and backgrounds for stadium EPC.

  • Build tasks that require inter-agent communication and schedule conflict resolution.

  • Parse Gantt schedule dependencies (MS Project / Primavera P6 output format).

  • Produce consolidated milestone risk reports ahead of tender submission.

Resources and assets

Reference links and supporting material

Dataset notes

Synthetic Primavera P6 schedule outputs for FIFA-standard stadium developments in Morocco.

How this agent runs

Evaluates the Crew's ability to identify overlapping critical path dependencies and generate resolutions.

Challenge input

JSON array of task objects with start_date, end_date, resource, and dependencies

CrewAI

Provides structured multi-agent collaboration features.

Evaluated output

JSON summary of detected conflicts and crew recommendations

Checks for
  • Ensures all resource collisions in input are detected
  • Score measuring whether proposed timeline resolution maintains final deadline • target: 0.95 • range: 0-1
Proof of success
  • Benchmark: CrewSchedulingBench
  • Recommendation Feasibility target: 0.95
  • 1 public reference case
Runtime evidence
  • Python execution harness
  • Python sandbox (unavailable on Versalist)
View technical recipe

Configured tools

Action Space
  • CrewAI · Required
  • crewAI · Optional
  • Zed · Optional

Evaluation contract

  • conflict_completeness · Weight 1
  • recommendation_feasibility · Weight 1

Recipe state

This is a preview. The configuration can change before the evaluation recipe is locked.

Frequently Asked Questions about World Cup Stadium Schedule Crew with CrewAI