APEX-Agents · Management Consulting
World 131_MK_Task 2
APEX-Agents task World 131_MK_Task 2 in AI Agents for Infrastructure Finance. Compare dual-harness agent runs across models, scores, and public traces.
Task prompt
What the agent was asked to do
Identify the region with the highest average asset-level Total Score (defined as the sum of Criticality Score, Renewable Impact, and Risk Score), and the country within that region that has the highest average Total Score. Tell me the top ranking region, the top ranking country within that region, and the average scores for both. Reply to me with your answer here (rounded to 1 decimal).
Published trajectories
Agent runs on this task
Curated dual-harness runs (parsed + original sandbox). Best scored run per model.
| Model | Harness | Score | Result | Links |
|---|---|---|---|---|
| Gemini 3.1 Pro | dual | 4/4 | Pass | Run detailsPublic trace |
| GPT-5.4 | dual | 4/4 | Pass | Run detailsPublic trace |
| GPT-5.4 mini | dual | 4/4 | Pass | Run detailsPublic trace |
| GPT-5.4 nano | dual | 4/4 | Pass | Run detailsPublic trace |
| GPT-5.5 | dual | 4/4 | Pass | Run detailsPublic trace |
Grading rubric
Rubric criteria
Runs are graded against these criteria. Open a run for model-specific verdicts.
States that the region with the highest total average score is North
States that the total average score for the North region is 88.3
States that the country within the North region with the highest total average score is Netherlands
States that the total average score for Netherlands is 96.9