Raycaster/ Eval

APEX-Agents

gpt-5.5 on CW134 Aditi 03

2/6Fail
Domain
Management Consulting
Category
AI Agents for M&A Legal Due Diligence
Harness
dual

Grader rubric

Criteria verdict

  1. States that % of Syncore customers actively using the in-app analytics feature within the mobile app in 2024 is 66.42%

    Fail
  2. States that % of Velocity customers actively using the in-app analytics feature within the mobile app in 2024 is 19.00%

    Fail
  3. States that % of UpSkill customers actively using the in-app analytics feature within the mobile app in 2024 is 7.91%

    Fail
  4. States that % of TrainIQ customers actively using the in-app analytics feature within the mobile app in 2024 is 0%

    Fail
  5. States that a company with instances of In-app Analytics Feature Satisfaction Score > Mobile App Satisfaction Score is Syncore

    Pass
  6. States that one company with instances of In-app Analytics Feature Satisfaction Score > Mobile App Satisfaction Score is Velocity

    Pass

Prompt excerpt

Task context

To better understand the market dynamics, the client wants to analyze customer engagement with the mobile app features. Use the feature dataset for competitors from 2016-24 to calculate the following using aggregated data across 2016-24: - For each company, determine the 2024 percentage of customers actively using the in-app analytics feature within the mobile app. - Identify all the companies with instances of In-app Analytics Feature Satisfaction Score (out of 10) > Mobile App Satisfaction Score (out of 10). Round all final answers to the nearest 0.01%. Give me the answer right back here as a short message.

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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.