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User Prompt

“Create a benchmark that tests whether my agent can submit a prior auth for an MRI.”

Tool Call Sequence

1

Create benchmark

Call: benchmarks
Response:
What the agent learns: The benchmark is created and linked to the environment. The 300-second timeout gives the agent-under-test five minutes to complete each task.
2

Create task

Call: tasks
Response:
What the agent learns: The task defines what the agent-under-test should do. The instruction is specific about the procedure type and CPT code so criteria can verify exact behavior.
3

Create criteria

The agent creates two criteria: one to verify submission and one to verify the correct CPT code.Call 1: criteria
Response:
Call 2: criteria
Response:
What the agent learns: The first criterion (weight 1.0) is the critical check: did the agent actually submit a PA? The second criterion (weight 0.5) verifies correctness of the CPT code. Weighted scoring means the submission check counts twice as much as the code check.
4

Start run

Call: benchmark_runs
Response:
What the agent learns: The run is in progress. The agent-under-test is now executing against the live playground. The agent should poll for completion.
5

Check results

The agent polls the run, then drills into task-level and criterion-level results.Call 1: benchmark_runs
Response:
Call 2: task-runs
Response:
Call 3: criterion-runs
Response:
What the agent learns: The run passed with a score of 0.87. The PA was submitted successfully (full marks), but the CPT code check scored 0.6 because the agent needed a correction attempt. The reasoning field explains exactly what happened.

Agent Response

Your prior auth benchmark completed with a Pass verdict and a score of 0.87. The agent successfully submitted the prior authorization, though it initially entered the wrong CPT code before self-correcting. You might want to improve your agent’s CPT code lookup logic.

Summary