Build a Data Center Thermal Load Balancing Scheduler with Claude Agents SDK
Construct an intelligent compute workload scheduler for Singapore's 200MW data center infrastructure. Leveraging Claude Agents SDK with extended thinking and computer use capabilities, your agent will balance server power allocation against green energy constraints and thermal limits.
What you are building
The core problem, expected build, and operating context for this challenge.
Build an intelligent load-balancing agent using Claude Agents SDK to manage thermal limits and energy targets in Singapore data centers.
How work is evaluated
Evaluate capacity planning assignments for compliance with 200MW grid and PUE constraints.
Shared data for this challenge
Review public datasets and any private uploads tied to your build.
How submissions are scored
These dimensions define what the evaluator checks and which criteria separate a passable run from a strong one.
thermal_limit_safety
No hall temp exceeds maximum safety limit of 28C
This dimension contributes its full weight only when the submission satisfies the requirement. Partial credit is not awarded.
pue_score
Calculated Power Usage Effectiveness • target: 1.22 • range: 1-2
This dimension contributes its full weight only when the submission satisfies the requirement. Partial credit is not awarded.
What you should walk away with
Utilize Claude Agents SDK with extended thinking mode for complex constraint optimization
Design multi-objective scheduling tool definitions for rack power and thermal management
Enforce maximum Power Usage Effectiveness (PUE) target thresholds
Automate workload shifting based on dynamic green grid availability signals
Reference links and supporting material
Telemetry logs from simulated 200MW data center facility representing hall temperatures, PDU loads, and cooling energy.
How this agent runs
Evaluate capacity planning assignments for compliance with 200MW grid and PUE constraints.
Challenge input
JSON containing hall_states (temp, load_mw) and incoming_job_mw
Claude Agents SDK
Anthropic SDK supporting extended thinking capabilities.
Evaluated output
JSON with assigned_hall, revised_hall_temps, and pue_estimate
- No hall temp exceeds maximum safety limit of 28C
- Calculated Power Usage Effectiveness • target: 1.22 • range: 1-2
- Benchmark: DC_Energy_Opt_Bench
- Pue Score target: 1.22
- 1 public reference case
- Python execution harness
- Python sandbox (unavailable on Versalist)
View technical recipe
Configured tools
- RAI · Required
- Agentic Dev · Optional
- AutoGluon · Optional
Evaluation contract
- thermal_limit_safety · Weight 1
- pue_score · Weight 1
Recipe state
This is a preview. The configuration can change before the evaluation recipe is locked.