Add evaluation module: RelevancyEvaluator and FactCheckingEvaluator, golden dataset with a pass-rate gate, deterministic CI judge and simulated judge noise

Co-Authored-By: Claude Sonnet 5.5 <[email protected]>
Claude-Session: https://claude.ai/code/session_01JXVi2GMQ7bR5EmbUFdDj7N

evaluation/output/04-noisy-judge.txt

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+# Simulated judge noise: 200 runs of a 12-case suite per build
+
+noise-free pass rate: healthy build 1.00, regressed build 0.75
+
+== 3% of judge verdicts flipped (mean pass rate: healthy 0.947, regressed 0.706) ==
+gate                   healthy build fails it       regressed build fails it
+every case must pass   96 of 200 runs               200 of 200 runs
+pass rate >= 0.90      29 of 200 runs               200 of 200 runs
+pass rate >= 0.85      29 of 200 runs               200 of 200 runs
+pass rate >= 0.80      2 of 200 runs                200 of 200 runs
+
+== 8% of judge verdicts flipped (mean pass rate: healthy 0.859, regressed 0.640) ==
+gate                   healthy build fails it       regressed build fails it
+every case must pass   166 of 200 runs              200 of 200 runs
+pass rate >= 0.90      102 of 200 runs              200 of 200 runs
+pass rate >= 0.85      102 of 200 runs              200 of 200 runs
+pass rate >= 0.80      47 of 200 runs               200 of 200 runs