JevBenchmarkLab

Overview & Result

JevBenchmarkLab is described as an open harness with 200 ground-truth cases across 20 suites, covering consistency, adversarial failures, option-order bias, probability drift, and latency.

How Jev fits in the loop

1. The harness sends fixed decision tasks to Jev and records structured outputs.
2. It compares outputs with expected labels and repeated-run behavior.
3. It produces reports that separate quality, calibration, and latency evidence.

How to reproduce

1. Clone the repository and identify the datasets, expected labels, and report-generation command.
2. Run one suite twice with fixed inputs to inspect consistency and answer flips.
3. Record latency percentiles and calibration separately from task accuracy.

Why this build matters

It is useful infrastructure for the evaluation side of JevForAgents, where reproducibility matters more than a single impressive demo number.

Limitations

• The reviewed post does not establish that the suites represent production traffic.
• A benchmark harness can reveal failure modes but cannot guarantee generalization to a new domain.
• Results should be labeled as community evidence until independently rerun.

Patterns