Cross-Border Trade Compliance Verification Engine for Cross-Straits Logistics
Truck freight logistics moving across Singapore, Malaysia, and Indonesia require strict verification of cross-border customs documentation, driver permits, and hazardous cargo clearance declarations before vehicles approach border checkpoints. In this challenge, you will implement a cross-border customs verification agent using Pydantic AI. The agent validates multi-lingual consignment declarations against Singapore Customs and Royal Malaysian Customs regulations, checks permit expiration dates, and produces validated border pass authorization tokens.
What you are building
The core problem, expected build, and operating context for this challenge.
Develop a type-safe trade compliance verification agent using Pydantic AI for cross-straits logistics.
How work is evaluated
Evaluates accuracy of trade document validation and error detection.
Challenge datasets
Public datasets, plus the private datasets you have access to.
How submissions are scored
These dimensions define what the evaluator checks and which criteria separate a passable run from a strong one.
expired_permit_block
Must reject clearance if permit expiry precedes current date.
This dimension contributes its full weight only when the submission satisfies the requirement. Partial credit is not awarded.
validation_latency_ms
Agent execution time per validation payload • target: 450 • range: 10-3000
This dimension contributes its full weight only when the submission satisfies the requirement. Partial credit is not awarded.
What you should walk away with
Build a type-safe customs inspection agent using Pydantic AI
Validate dangerous goods (DG) compliance declarations against IMDG standards
Implement dynamic check-step tools with Pydantic validation guarantees
Output audit-compliant clearance receipts with cryptographic authorization tokens
Reference links and supporting material
Cross-border truck consignment declarations, driver permits, and hazardous goods transport manifests.
Challenge setup
Evaluates accuracy of trade document validation and error detection.
Challenge input
JSON containing driver permit dates, cargo classification, and customs declarant ID
Pydantic AI
Required Python framework for typed schema validation.
Evaluated output
JSON matching Pydantic schema with clearance_approved boolean and issue list
- Must reject clearance if permit expiry precedes current date.
- Agent execution time per validation payload • target: 450 • range: 10-3000
- Benchmark: LogiBench-Compliance
- Validation Latency Ms target: 450
- 1 public reference case
- 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.
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Configured tools
- Pydantic AI · Required
- RAI · Optional
- Yupp AI · Optional
- Pydantic AI · Required
Evaluation contract
- expired_permit_block · Weight 1
- validation_latency_ms · Weight 1
Metrics
- validation_latency_ms · Target 450
Benchmarks
- LogiBench-Compliance
- general
Reference cases
- 1 public reference case
Workflow tasks
- Task 1
Input: JSON containing driver permit dates, cargo classification, and customs declarant ID
Output: JSON matching Pydantic schema with clearance_approved boolean and issue list
Execution harness: Python
Evaluation tools
- Pydantic AI · Agent Framework
Recipe freeze marker
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