Multi-Modal Vessel Loading Inspection Agent with Claude SDK and Gemini 2.5 Flash
Maritime crude oil loading requires dynamic inspection of vessel draft marks, loading arm alignment, and safety compliance images at marine terminals. Build a multimodal vision-language agent using Claude Agents SDK and Gemini 2.5 Flash as high-speed secondary vision runtime. The agent analyzes port surveillance photos, checks safety compliance against international tanker standards (ISGOTT), and calculates estimated laytime remaining based on visual pump connections.
What you are building
The core problem, expected build, and operating context for this challenge.
Develop a multimodal marine terminal inspection agent using Claude Agents SDK and Gemini 2.5 Flash.
How work is evaluated
Evaluates visual terminal inspection agent on safety flag identification.
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.
safety_clearance_passed
Verify clearance is granted when sensors are normal.
This dimension contributes its full weight only when the submission satisfies the requirement. Partial credit is not awarded.
issue_detection_recall
Recall metric for detecting visual safety violations. • target: 0.95 • range: 0-1
This dimension contributes its full weight only when the submission satisfies the requirement. Partial credit is not awarded.
What you should walk away with
Implement multimodal tool execution with Claude Agents SDK.
Incorporate Gemini 2.5 Flash for high-speed image preprocessing and feature extraction.
Automate laytime and safety compliance auditing from visual feed streams.
Reference links and supporting material
Synthetic image metadata and terminal sensor frames from marine crude loading berths.
Challenge setup
Evaluates visual terminal inspection agent on safety flag identification.
Challenge input
JSON containing image_metadata and sensor_readings
Claude Agents SDK
Provides deep reasoning and tool invocation framework.
Gemini 2.5 Flash
Fast visual feature extraction and image processing runtime.
Evaluated output
JSON with safety_clearance, detected_issues, estimated_flow_rate_bph
- Verify clearance is granted when sensors are normal.
- Recall metric for detecting visual safety violations. • target: 0.95 • range: 0-1
- Benchmark: Vision-Logistics-Bench
- Issue Detection Recall target: 0.95
- 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
- Modal · Optional
- Google Gemini · Required
- Gemini 2.5 Flash · Optional
- Modal · Optional
Evaluation contract
- safety_clearance_passed · Weight 1
- issue_detection_recall · Weight 1
Metrics
- issue_detection_recall · Target 0.95
Benchmarks
- Vision-Logistics-Bench
- general
Reference cases
- 1 public reference case
Workflow tasks
- Task 1
Input: JSON containing image_metadata and sensor_readings
Output: JSON with safety_clearance, detected_issues, estimated_flow_rate_bph
Execution harness: Python
Evaluation tools
- Claude Agents SDK · Reasoning Core
- Gemini 2.5 Flash · Vision Model
Recipe freeze marker
No recipe freeze time is recorded.