Expose dataset/conversion scripts as uv entry points

scripts/ is now a proper package (scripts/__init__.py, added to the wheel's
packages), with each script registered under [project.scripts] using its
bare dashed name (e.g. `uv run migrate-geant-steps`). Tests now import these
modules normally instead of loading them by file path.

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>

README.md

@@ -34,7 +34,7 @@ The model is developed in two phases:
 
 ## Data
 
-Input: parquet files produced by [miniCaloSim](https://gitlab.etp.kit.edu/lbogner/minicalosim), or converted from a ROOT file via `scripts/steps_to_parquet.py`. Each row is one Geant4 step. Train/val split is by `event_id` (not row shuffle) to avoid leaking correlated steps from the same shower.
+Input: parquet files produced by [miniCaloSim](https://gitlab.etp.kit.edu/lbogner/minicalosim), or converted from a ROOT file via `uv run steps-to-parquet`. Each row is one Geant4 step. Train/val split is by `event_id` (not row shuffle) to avoid leaking correlated steps from the same shower.
 
 ## Project structure
 
@@ -55,9 +55,13 @@ giant/
 │   ├── validate.py         # step-level marginal + KL-divergence validation
 │   ├── analysis.py         # notebook diagnostics: marginals, correlations, constraint checks
 │   └── cli.py              # `giant train` / `giant predict` Typer app
-├── scripts/
-│   ├── train.py              # argparse training entry point
-│   └── steps_to_parquet.py   # ROOT → parquet conversion (uproot/awkward/polars)
+├── scripts/                            # also exposed as uv entry points, e.g. `uv run steps-to-parquet`
+│   ├── steps_to_parquet.py             # ROOT → parquet conversion (uproot/awkward/polars)
+│   ├── steps_to_parquet_parallel.py    # fan out steps_to_parquet.py over several ROOT files
+│   ├── migrate_geant_steps.py          # one-time move into the raw/processed/pools/derived layout
+│   ├── bump_dataset_version.py         # cut a new raw gen or parquet schema, with a logged reason
+│   ├── create_root_files.py            # generate new ROOT shards via a minicalosim executable
+│   └── hparam_scan.py                  # hyperparameter grid scan over `giant train` runs
 └── tests/
 ```