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Challenge

Maritime Fuel Oil Trade & Tariff Compliance Agent for Saudi Seaborne Imports

Saudi Arabia was the top buyer of Russian seaborne fuel oil in July. Build an automated maritime shipment compliance agent in Python that tracks vessel AIS pathways, verifies price cap declarations, and flags customs classification codes. Maintain 100% detection of unauthorized or unverified fuel oil shipments.

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Challenge brief

What you are building

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

Develop an automated maritime compliance tracking system in Python to verify fuel oil tanker origin, price cap compliance, and port customs clearance.

Delivery guide

How work is evaluated

Evaluation

Evaluates AIS anomaly detection and price cap attestation verification.

Datasets

Challenge datasets

Public datasets, plus the private datasets you have access to.

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

ais_gap_flag_check

Ensures AIS gap over 12 hours automatically flags for physical inspection

Binary check

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

Dimension 2

compliance_flagging_recall

Recall of flagged illicit trade indicators • target: 1 • 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

  • Track tanker voyage AIS history to detect ship-to-ship (STS) transfer anomalies.

  • Verify export price attestation documents against current price ceiling rules.

  • Parse Harmonized System (HS) codes for fuel oil grade classification.

  • Generate automated customs clearance risk reports.

Resources and assets

Reference links and supporting material

Dataset notes

AIS tanker trajectory logs and price attestation records for Mediterranean and Red Sea shipping routes.

Challenge setup

Evaluates AIS anomaly detection and price cap attestation verification.

Challenge input

JSON with imo_number, price_usd_per_barrel, ais_gap_hours, and sts_transfers_detected

Python Maritime Analytics

Evaluates vessel AIS trajectory gaps and customs rules.

Evaluated output

JSON with clearance_status, compliance_flags, and risk_tier

Evaluation checks
  • Ensures AIS gap over 12 hours automatically flags for physical inspection
  • Recall of flagged illicit trade indicators • target: 1 • range: 0-1
Configured evaluation evidence
  • Benchmark: TradeSanctionsBench
  • Compliance Flagging Recall target: 1
  • 1 public reference case
Configured runtime
  • Python execution harness
  • Python sandbox (unavailable on Versalist)

Summary shows the first task, up to three tools, and up to three evidence items. Open the technical recipe to view all configured items.

View technical recipe

Configured tools

Action Space
  • Zed · Required
  • Adept · Optional
  • LiveKit · Optional

Evaluation contract

  • ais_gap_flag_check · Weight 1
  • compliance_flagging_recall · Weight 1

Metrics

  • compliance_flagging_recall · Target 1

Benchmarks

  • TradeSanctionsBench
  • security

Reference cases

  • 1 public reference case

Workflow tasks

  1. Task 1

    Input: JSON with imo_number, price_usd_per_barrel, ais_gap_hours, and sts_transfers_detected

    Output: JSON with clearance_status, compliance_flags, and risk_tier

    Execution harness: Python

Evaluation tools

  • Python Maritime Analytics · Compliance Engine

Recipe freeze marker

No recipe freeze time is recorded.

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