diff --git a/docs/scenarios.md b/docs/scenarios.md
index 1251097..3a87c8c 100644
--- a/docs/scenarios.md
+++ b/docs/scenarios.md
@@ -64,3 +64,15 @@ These scenarios test the business rule validations inside `validate_train_params
 | `test_scenario_3_1_1_cleanup_with_no_temp_dirs` | Temp directory is empty. Activity completes without error. |
 | `test_scenario_3_1_2_cleanup_removes_old_temp_dirs` | Two stale directories matching `name_YYYYMMDD_HHMMSS_microseconds` are removed when older than retention. |
 | `test_scenario_3_1_3_cleanup_nonexistent_temp_path` | Target path does not exist. Handled gracefully without error. |
+
+## 4. PluginStore Wiring (`test_plugin_store_wiring.py`)
+
+`Activities` receives `plugin_store_config` and builds the `PluginStore` itself. These scenarios run `01-linear-regression-basic.json` on a worker built from a per-test config (`activities_factory`) against the Gitea `model-store` repo.
+
+| Test Function | Config Change | Expected Status | Description |
+|---|---|---|---|
+| `test_scenario_4_1_1_plugin_store_from_env_config` | `STORE_*` env vars → `build_plugin_store_config()` | `TRAINING_SUCCESS` | Same path as the worker. With `STORE_BRANCH` unset the store resolves the branch to `main`. |
+| `test_scenario_4_1_2_explicit_branch` | `branch = 'main'` | `TRAINING_SUCCESS` | Explicit branch skips resolution and is used for every read. |
+| `test_scenario_4_1_3_explicit_branch_without_model` | `branch = 'e2e-no-linear-regression'` | `ORCHESTRATOR_VALIDATION_ERROR` | Branch forked from `main` without `models/linear_regression/index.yaml`; error mentions `linear_regression/index.yaml`. |
+| `test_scenario_4_1_4_nonexistent_repository` | `repo = 'no-such-store'` | `ORCHESTRATOR_VALIDATION_ERROR` | `Activities` still builds (branch falls back to `main`); fails when loading model metadata. |
+| `test_scenario_4_1_5_wrong_credentials` | `password = 'wrong-password'` | `ORCHESTRATOR_VALIDATION_ERROR` | Gitea rejects the read; error mentions `401`. |
diff --git a/model_manager/workflows/train_model.py b/model_manager/workflows/train_model.py
index e3e0c73..4270bd1 100644
--- a/model_manager/workflows/train_model.py
+++ b/model_manager/workflows/train_model.py
@@ -131,7 +131,9 @@ class TrainModel:
             training_succeeded = True
         finally:
             try:
-                if train_result is not None:
+                # train_result is only None when training raised, so the false branch
+                # always leaves through the re-raise and never reaches the return below.
+                if train_result is not None:  # pragma: no branch
                     await self._cleanup_resources(
                         run_dir=train_result.get('run_dir'),
                         metadata=metadata,
diff --git a/tests/utils/repository/test_data_manager_repository.py b/tests/utils/repository/test_data_manager_repository.py
index c0b7e7c..57d0ffa 100644
--- a/tests/utils/repository/test_data_manager_repository.py
+++ b/tests/utils/repository/test_data_manager_repository.py
@@ -92,6 +92,52 @@ def test_ensure_date_column_parsed_invalid_raises():
         dmr._ensure_date_column_parsed(df, p)
 
 
+def test_ensure_date_column_parsed_unmapped_format_raises():
+    df = pd.DataFrame({'ts': ['2024-01-01 10:00:00']})
+    p = _params(date_column='ts')
+    # Bypasses validate_business_rules, which would reject it earlier
+    p.date_format = 'dd/MM/yyyy HH:mm'
+    with pytest.raises(ValueError, match='is not mapped to a strftime pattern'):
+        dmr._ensure_date_column_parsed(df, p)
+
+
+def test_drop_rows_with_missing_timestamp_without_date_column_returns_input():
+    repo = dmr.DataManagerRepository(MagicMock())
+    df = pd.DataFrame({'v1': [1.0, 2.0]})
+    assert repo._drop_rows_with_missing_timestamp(df, _params(), {}) is df
+
+
+def test_drop_rows_with_missing_timestamp_non_object_dtype_drops_nat():
+    repo = dmr.DataManagerRepository(MagicMock())
+    df = pd.DataFrame(
+        {'timestamp': pd.to_datetime(['2024-01-01', None, '2024-01-03']), 'v1': [1, 2, 3]}
+    )
+    out = repo._drop_rows_with_missing_timestamp(df, _params(), {})
+    assert list(out['v1']) == [1, 3]
+
+
+def test_coerce_non_timestamp_columns_to_numeric_skips_date_column():
+    repo = dmr.DataManagerRepository(MagicMock())
+    df = pd.DataFrame({'timestamp': ['2024-01-01 10:00:00'], 'v1': ['1.5']})
+    out = repo._coerce_non_timestamp_columns_to_numeric(df, _params(), {})
+    assert out['timestamp'].iloc[0] == '2024-01-01 10:00:00'
+    assert float(out['v1'].iloc[0]) == 1.5
+
+
+def test_set_timezone_on_index_converts_aware_index_to_utc():
+    repo = dmr.DataManagerRepository(MagicMock())
+    idx = pd.DatetimeIndex(['2024-01-01 00:00'], tz='America/Sao_Paulo')
+    out = repo._set_timezone_on_index(pd.DataFrame({'v1': [1]}, index=idx))
+    assert str(out.index.tz) == 'UTC'
+    assert out.index[0] == pd.Timestamp('2024-01-01 03:00', tz='UTC')
+
+
+def test_set_timezone_on_index_non_datetime_index_raises():
+    repo = dmr.DataManagerRepository(MagicMock())
+    with pytest.raises(ValueError, match='Index is not a DatetimeIndex'):
+        repo._set_timezone_on_index(pd.DataFrame({'v1': [1]}))
+
+
 def test_prepare_training_data_csv_load_failure():
     repo = dmr.DataManagerRepository(MagicMock())
     p = _params()