APEX-Agents · Management Consulting

World 132_PM_Task02

0/2Fail

APEX-Agents task World 132_PM_Task02 in AI Agents for Legal Contract Review. Compare dual-harness agent runs across models — rubric criteria, scores, and public traces.

AI Agents for Legal Contract ReviewManagement Consulting World 132Dual harnessGrader: rubric

Task IDtask_4ab23f273c9f4e0a89684c3703302e25

WorldManagement Consulting World 132

Expected outputmessage_in_console

Published runs5 models · dual config

Task prompt

What the agent was asked to do

Let us assess average price points of sub-categories in 2027 across these 7 markets - Australia, China, Germany, India, Mexico, UAE and UK. The client has informed us of some errors in the data. TAM - 2020 Value is actually TAM - 2022 Value. TAM - 2025 Volume is actually TAM - 2023 Volume. Let's use historic CAGRs for TAM Value and TAM Volume to calculate 2027 TAM Value and Volume respectively. Average price point ($M/ton) can be calculated by using TAM Value ($M) and TAM Volume (tons). Consider all values for Australia, China, Germany, India, Mexico, UAE and UK put together. Round off all final values to 2 decimal places. Report the following in a short reply to me: (1) What % of sub-categories have an average price greater than or equal to $300K/ton (2) Which sub-category has the highest average price? (3) Which sub-category has the lowest average price? (4) What is the difference between highest and lowest average price sub-categories?

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 that the competitor which was in top 5 in terms of the original Online Market Share % but not in top 5 with the revised data is EuroCore Nutrition
Fail
Evidence: <TEXT_RESPONSE> discusses sub-category average prices: “Highest average price: Gourmet Protein Powders” and “Lowest average price: Thermogenic / Metabolic Support Drinks.” It does not mention any competitor, top 5 Online Market Share %, revised data, or “EuroCore Nutrition.” Assessment: Criterion requires stating the competitor was EuroCore Nutrition; fail because the response contains no such statement.
States that the revised Online Market Share % of EuroCore Nutrition is 35.43
Fail
Evidence: <TEXT_RESPONSE> states “67.27% of sub-categories…” and average prices such as “$390.07K/ton,” but does not mention EuroCore Nutrition or a revised Online Market Share % of 35.43. Assessment: Criterion requires stating EuroCore Nutrition’s revised Online Market Share % is 35.43; fail because this is absent.