diff --git a/evalharness/cli.py b/evalharness/cli.py
index 1877e9a..47019b0 100644
--- a/evalharness/cli.py
+++ b/evalharness/cli.py
@@ -784,9 +784,22 @@ def _cmd_eval_run(args) -> int:
                 if _repeats > 1 and _scores:
                     _mean = sum(_scores) / len(_scores)
                     _spread = f'{min(_scores):.3f}–{max(_scores):.3f}' if len(_scores) > 1 else f'{_scores[0]:.3f}'
-                    print(f'\n{name}: {_repeats} runs | mean={_mean:.4f} | range={_spread}', flush=True)
+                    _runs_txt = ' '.join(f'{s:.2f}' for s in _scores)
+                    print(f'\n{name}: {_repeats} runs | mean={_mean:.4f} | range={_spread} '
+                          f'| runs=[{_runs_txt}]', flush=True)
                     # summary/xlsx report the MEAN over repeats (es parity);
-                    # per-run scores stay in report.jsonl / the per-run metrics
+                    # EVERY per-run score lands in metric_groups['repeats'] so
+                    # the 12 runs are queryable in report.jsonl / the categories
+                    # columns instead of only scrolling past on the terminal
+                    _var = sum((s - _mean) ** 2 for s in _scores) / len(_scores)
+                    report.metric_groups['repeats'] = {
+                        'n_runs': len(_scores),
+                        'scores': [round(s, 4) for s in _scores],
+                        'mean': round(_mean, 4),
+                        'min': round(min(_scores), 4),
+                        'max': round(max(_scores), 4),
+                        'std': round(_var ** 0.5, 4),
+                    }
                     _primary = next(iter(report.metrics), '')
                     if _primary:
                         report.metrics[f'{_primary}_last_run'] = report.metrics[_primary]