APEX-Agents · Management Consulting

World131_IB_Task 12

0/2Fail

APEX-Agents task World131_IB_Task 12 in AI Agents for Infrastructure Finance. Compare dual-harness agent runs across models — rubric criteria, scores, and public traces.

AI Agents for Infrastructure FinanceManagement Consulting World 131Dual harnessGrader: rubric

Task IDtask_0ea0001d6cb34cc6abf9bf6dc4e8e30b

WorldManagement Consulting World 131

Expected outputmessage_in_console

Published runs5 models · dual config

Task prompt

What the agent was asked to do

Using the Digital Twin Input and Additional bus datasets, identify the Bus IDs associated with renewable energy generation. For each of these Bus IDs, calculate the average (in GW) of their three highest load values. Based on these averages, shortlist the top 2. Round to 3 places. Give the answers here.

Published trajectories

Agent runs on this task

Curated dual-harness runs (parsed + original sandbox). Best scored run per model.

Model	Harness	Score	Result	Links
GPT-5.5showcase	dual	0/2	Fail	Share page Public trace
Gemini 3.1 Pro	dual	0/2	Fail	Share page Public trace
GPT-5.4	dual	0/2	Fail	Share page Public trace
GPT-5.4 mini	dual	0/2	Fail	Share page Public trace
GPT-5.4 nano	dual	0/2	Fail	Share page Public trace

Grading rubric

Criteria and grader verdict (showcase run)

States the forecasted load of B010 is 0.156 GW
Fail
Evidence: TEXT_RESPONSE table states for B010: “Average of 3 highest load values (GW)” = “0.348”. Assessment: Criterion requires the response to state the forecasted load of B010 is 0.156 GW. The response does not state 0.156 GW for B010; it states 0.348 GW, so fail.
States the forecasted load of B006 is 0.182 GW
Fail
Evidence: TEXT_RESPONSE table states for B006: “Average of 3 highest load values (GW)” = “0.343”. Assessment: Criterion requires the response to state the forecasted load of B006 is 0.182 GW. The response does not state 0.182 GW for B006; it states 0.343 GW, so fail.