Build a Marine Tourism Footprint Analyst using OpenAI Agents SDK
Balancing Oman's expanding marine tourism projects with coastal ecosystem preservation requires rapid environmental impact assessment. Build an autonomous agent with OpenAI Agents SDK to analyze marine vessel traffic, evaluate reef risk indices, and generate sustainable mooring plans.
What you are building
The core problem, expected build, and operating context for this challenge.
Deploy an OpenAI Agents SDK workflow to calculate coastal sensitivity indices and optimize marine vessel mooring assignments in Oman.
How work is evaluated
Evaluates calculation accuracy for coastal coral reef proximity and vessel capacity allocation.
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.
capacity_exceeded_check
Ensure overflow status is correctly assigned
This dimension contributes its full weight only when the submission satisfies the requirement. Partial credit is not awarded.
spatial_precision
Precision of reef buffer proximity calculations • target: 0.98 • range: 0.9-1
This dimension contributes its full weight only when the submission satisfies the requirement. Partial credit is not awarded.
What you should walk away with
Process marine vessel AIS location telemetry and coastal reef proximity datasets
Implement OpenAI Agents SDK tools for calculating coral sensitivity scores
Automate generation of mooring zone recommendations to mitigate ecosystem damage
Output standardized environmental assessment reports for tourism ministries
Reference links and supporting material
Vessel tracking logs, coral reef map vectors, and visitor capacity metrics along the Musandam and Daymaniyat coasts.
How this agent runs
Evaluates calculation accuracy for coastal coral reef proximity and vessel capacity allocation.
Challenge input
JSON containing vessel density and reef distance
OpenAI Agents SDK
Provides tool integration capabilities for geospatial calculation
Evaluated output
JSON capacity allocation
- Ensure overflow status is correctly assigned
- Precision of reef buffer proximity calculations • target: 0.98 • range: 0.9-1
- Benchmark: EcoGISBench
- Spatial Precision target: 0.98
- 1 public reference case
- Python execution harness
- Python sandbox
View technical recipe
Configured tools
- OpenAI · Required
- Alibi Detect · Optional
- Voiceflow · Optional
Evaluation contract
- capacity_exceeded_check · Weight 1
- spatial_precision · Weight 1
Recipe state
This is a preview. The configuration can change before the evaluation recipe is locked.