3. **Reward Component Analysis** - Binned relationships (idle, hold, exit), correlation matrix (constant features removed), PBRS analysis (activation rates, component stats, invariance summary).
4. **Feature Importance** - Random Forest importance + partial dependence.
5. **Statistical Validation** - Hypothesis tests, bootstrap confidence intervals, normality diagnostics, optional distribution shift (5.4) when real episodes provided.
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**Summary** - 7-point concise synthesis:
1. Reward distribution health (center, spread, tail asymmetry)
2. Action & position coverage (usage %, invalid rate, masking efficacy)