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APEX-Agents · Management Consulting

Task_World130_CamilleMoingeon_2

8/8Pass

APEX-Agents task Task_World130_CamilleMoingeon_2 in AI Agents for Real Estate Lease Review. Compare dual-harness agent runs across models — rubric criteria, scores, and public traces.

AI Agents for Real Estate Lease ReviewManagement Consulting World 130Dual harnessGrader: rubric
Task IDtask_1137ecf56e014b749a7af76a40057560
WorldManagement Consulting World 130
Expected outputmessage_in_console
Published runs5 models · dual config

Task prompt

What the agent was asked to do

I'm trying to get a sense of which HarFeast employees are most ready for the digital training rollout. Can you pull the workforce survey data and identify all employees who are above their role type's median readiness score, willing to pilot new tools, willing to spend >2 days in training with dedicated training time, and above the overall median digital comfort score? Once you've identified that "high-priority" group, can you tell me: 1. How many employees qualify and what percentage of the total workforce that represents 2. How many hours these employees spend on manual entry / searching / fixing errors, and what percentage of total manual entry / searching / error fixing hours that represents 3. How many "high-priority" employees there are for each role type Just give me the final answers as a reply in this box, rounded to one decimal place.

Published trajectories

Agent runs on this task

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

ModelHarnessScoreResultLinks
GPT-5.5showcasedual8/8PassShare pagePublic trace
Gemini 3.1 Produal8/8PassShare pagePublic trace
GPT-5.4dual8/8PassShare pagePublic trace
GPT-5.4 minidual8/8PassShare pagePublic trace
GPT-5.4 nanodual8/8PassShare pagePublic trace

Grading rubric

Criteria and grader verdict (showcase run)

  1. States that the number of "high-priority" employees is 30

    Pass

    Evidence: TEXT_RESPONSE states, “High-priority employees: 30 employees.” Assessment: Criterion requires stating the number is 30; pass.

  2. States that the percentage of all employees the "high-priority employees represent is 1.0%

    Pass

    Evidence: TEXT_RESPONSE states, “representing 1.0% of the total workforce.” Assessment: Criterion requires 1.0%; pass.

  3. States that the total number of hours "high-priority" employees spend on manual entry, searching data or fixing errors is 168

    Pass

    Evidence: TEXT_RESPONSE states, “Manual entry / searching / fixing errors hours: 168.0 hours per week.” Assessment: Criterion requires total hours of 168; 168.0 preserves the value; pass.

  4. States that the percentage of all hours spent on manual entry, searching data or fixing errors that come from "high-priority" employees is 0.5%

    Pass

    Evidence: TEXT_RESPONSE states, “representing 0.5% of total workforce hours in those categories.” Assessment: Criterion requires 0.5%; pass.

  5. States that the number of "high-priority" employees in the Frontline role type is 22

    Pass

    Evidence: TEXT_RESPONSE lists “Front-line employee: 22.” Assessment: Criterion requires 22 high-priority employees in the Frontline role type; pass.

  6. States that the number of "high-priority" employees in the Back-office/Support role type is 4

    Pass

    Evidence: TEXT_RESPONSE lists “Back-office/Support function: 4.” Assessment: Criterion requires 4 in Back-office/Support role type; pass.

  7. States that the number of "high-priority" employees in the Supervisor/Team Lead role type is 3

    Pass

    Evidence: TEXT_RESPONSE lists “Supervisory/Team Lead: 3.” Assessment: Criterion requires 3 in Supervisor/Team Lead role type; pass.

  8. States that the number of "high-priority" employees in the Management role type is 1

    Pass

    Evidence: TEXT_RESPONSE lists “Management: 1.” Assessment: Criterion requires 1 in Management role type; pass.