RAEL (2026)

A local evaluation instrument that tests whether an agent can accurately predict how external evaluators will score its work before judgment occurs. For each task, the harness records the agent’s action trace, prompts the agent to forecast its own rubric scores and failure modes, and runs independent LLM judges alongside deterministic reference checks.

An optional intervention pass feeds the agent’s self-audit back into a linked revision run so calibration and self-correction can be measured separately. Every run emits a self-contained directory bundle (manifest.json, trace logs, per-judge verdicts, and disagreement matrices) plus a single-file HTML report.