APEX-Agents
gpt-5.5 on World126_EFA_01
Grader rubric
Criteria verdict
States that the overall risk score of the sub-region with the highest overall risk score is 83.70
PassStates that the overall risk score of the sub-region with the second-highest overall risk score is 83.55
PassStates that the overall risk score of the sub-region with the third-highest overall risk score is 75.30
PassStates that North America's average overall risk score is 54.69
PassStates that South America's average overall risk score is 63.97
PassStates that Europe's average overall risk score is 41.95
PassStates that Africa's average overall risk score is 73.95
PassStates that Asia's average overall risk score is 67.80
PassStates that Oceania's average overall risk score is 59.81
PassStates that the standard deviation across all sub-regions is 15.18
Fail
Prompt excerpt
Task context
Based on Planet Defense's climate risk data and their scoring methodology, give me the top 3 sub-regions by overall risk score and their overall risk scores. Once you've done that, calculate for each continent the average overall risk score and the standard deviation of all the overall risk scores. Report numeric final answers to 2 decimal places. Write your answer here.
Response trace
Agent response, tools, files, and edits
On a phone, the interactive viewer works best full-screen — pick the narrative report or the files & trajectory workspace.
Why Eval exists · why Workspace exists
Public evidence and cloud agents are the same harness.
Eval exists so scores are inspectable—tasks, trajectories, artifacts, and rubric verdicts anyone can open.Workspace exists so people can automate real file work with that harness, and so Raycaster never evaluates work it cannot perform.