diff --git a/scripts/eval/bond_geometry_eval.py b/scripts/eval/bond_geometry_eval.py
index 63eb2caf..d4984361 100644
--- a/scripts/eval/bond_geometry_eval.py
+++ b/scripts/eval/bond_geometry_eval.py
@@ -4,8 +4,6 @@
 # but static analysis can't always prove that.
 import argparse
 import itertools
-import sys
-from pathlib import Path
 
 import numpy as np
 import pandas as pd
@@ -14,7 +12,7 @@
 from biotite.structure.io.pdbx import CIFFile, get_structure
 from loguru import logger
 from peppr.bounds import get_distance_bounds
-from sampleworks.eval.grid_search_eval_utils import parse_args, scan_grid_search_results
+from sampleworks.eval.grid_search_eval_utils import parse_eval_args, setup_evaluation_parameters
 from scipy.special import comb
 from tqdm import tqdm
 
@@ -40,19 +38,9 @@ def bond_length_violations(pose: AtomArray, tolerance: float = 0.1) -> tuple[flo
     outlier_info : pd.DataFrame
         DataFrame containing information about the outliers, including atom indices and distances.
     """
-    if pose.array_length() == 0:
-        return np.nan, pd.DataFrame()
-
     try:
-        bounds = get_distance_bounds(pose)  # this fetches values from RDKit
-    except BadStructureError:
-        return np.nan, pd.DataFrame()
-
-    if not pose.bonds:
-        logger.error(
-            "Models must have bonds, use "
-            "`biotite.structure.io.pdbx.get_structure(..., include_bonds=True)`"
-        )
+        bounds = check_pose_and_get_bounds(pose)
+    except (ValueError, BadStructureError) as e:
         return np.nan, pd.DataFrame()
 
     bond_indices = np.sort(pose.bonds.as_array()[:, :2], axis=1)
@@ -99,6 +87,23 @@ def bond_length_violations(pose: AtomArray, tolerance: float = 0.1) -> tuple[flo
     return invalid_fraction, pd.DataFrame(outlier_info)
 
 
+def check_pose_and_get_bounds(pose: AtomArray):
+    if pose.array_length() == 0:
+        raise ValueError("The structure is empty.")
+
+    if not pose.bonds:
+        logger.error(
+            "Models must have bonds, use "
+            "`biotite.structure.io.pdbx.get_structure(..., include_bonds=True)`"
+        )
+        raise ValueError("The structure does not have bonds.")
+    
+    # this fetches values from RDKit, raises BadStructureError if the structure is bad
+    bounds = get_distance_bounds(pose)
+    return bounds
+
+
+
 def bond_angle_violations(pose: AtomArray, tolerance: float = 0.1) -> tuple[float, pd.DataFrame]:
     """
     Calculate the percentage of bonds that are outside acceptable ranges.
@@ -123,22 +128,10 @@ def bond_angle_violations(pose: AtomArray, tolerance: float = 0.1) -> tuple[floa
     outlier_info : pd.DataFrame
         DataFrame containing information about the outliers, including atom indices and distances.
     """
-    if pose.array_length() == 0:
-        return np.nan, pd.DataFrame()
+    bounds = check_pose_and_get_bounds(pose)
 
-    try:
-        bounds = get_distance_bounds(pose)
-    except BadStructureError:
-        return np.nan, pd.DataFrame()
-
-    if not pose.bonds:
-        logger.error(
-            "Models must have bonds, use "
-            "`biotite.structure.io.pdbx.get_structure(..., include_bonds=True)`"
-        )
-        return np.nan, pd.DataFrame()
-
-    # in the original, bonds were fetched from the reference structure, but we don't have one here.
+    # in bond_length_violations, bonds are fetched from the reference structure,
+    # but we don't have one here.
     all_bonds, _ = pose.bonds.get_all_bonds()
     # For a bond angle 'ABC', this list contains the atom indices for 'A' and 'C'
     bond_indices = []
@@ -203,20 +196,8 @@ def bond_angle_violations(pose: AtomArray, tolerance: float = 0.1) -> tuple[floa
 
 
 def main(args: argparse.Namespace):
-    workspace_root = Path(args.workspace_root)
-    # TODO make more general: https://github.com/diff-use/sampleworks/issues/93
-    grid_search_dir = workspace_root / "grid_search_results"
-    logger.info(f"Grid search directory: {grid_search_dir}")
-
-    # Scan for trials (look for refined.cif files)
-    all_trials = scan_grid_search_results(grid_search_dir, target_filename=args.target_filename)
-    logger.info(f"Found {len(all_trials)} trials with refined.cif files")
-
-    if all_trials:
-        all_trials.summarize()  # Prints some summary stats, e.g. number of unique proteins
-    else:
-        logger.error("No trials found in grid search directory. Exiting with status 1.")
-        sys.exit(1)
+    # The unused variable is a list of ProteinConfigs, not used yet in this script
+    all_trials, _ = setup_evaluation_parameters(args)
 
     all_bond_length_outliers = []
     all_bond_angle_outliers = []
@@ -254,6 +235,7 @@ def main(args: argparse.Namespace):
                 }
             )
 
+    grid_search_dir = args.grid_search_results_path
     pd.concat(all_bond_length_outliers).to_csv(
         grid_search_dir / "bond_length_outliers.csv", index=False
     )
@@ -269,5 +251,7 @@ def main(args: argparse.Namespace):
 
 
 if __name__ == "__main__":
-    args = parse_args("Evaluate bond angle and length outliers on grid search results.")
-    main(args)
+    eval_args = parse_eval_args(
+        description="Evaluate bond angle and length outliers on grid search results."
+    )
+    main(eval_args)
diff --git a/scripts/eval/lddt_evaluation_script.py b/scripts/eval/lddt_evaluation_script.py
index 61188b51..4e3caff9 100644
--- a/scripts/eval/lddt_evaluation_script.py
+++ b/scripts/eval/lddt_evaluation_script.py
@@ -1,9 +1,7 @@
 import argparse
 import itertools
 import re
-import sys
 import traceback
-from pathlib import Path
 
 import numpy as np
 import pandas as pd
@@ -13,7 +11,7 @@
 from joblib import delayed, Parallel
 from loguru import logger
 from sampleworks.eval.eval_dataclasses import ProteinConfig, Trial
-from sampleworks.eval.grid_search_eval_utils import parse_args, scan_grid_search_results
+from sampleworks.eval.grid_search_eval_utils import parse_eval_args, setup_evaluation_parameters
 from sampleworks.eval.structure_utils import get_reference_atomarraystack
 from sampleworks.metrics.lddt import AllAtomLDDT
 from sampleworks.utils.atom_array_utils import filter_to_common_atoms, map_altlocs_to_stack
@@ -194,28 +192,9 @@ def translate_selection(selection: str) -> str:
     return new_selection
 
 
+# TODO make more general: https://github.com/diff-use/sampleworks/issues/93
 def main(args: argparse.Namespace):
-    workspace_root = Path(args.workspace_root)
-
-    # TODO make more general: https://github.com/diff-use/sampleworks/issues/93
-    grid_search_dir = workspace_root / "grid_search_results"
-
-    # Protein configurations: base map paths, structure selections, and resolutions
-    protein_inputs_dir = args.grid_search_inputs_path or workspace_root
-    protein_configs = ProteinConfig.from_csv(protein_inputs_dir, args.protein_configs_csv)
-
-    logger.info(f"Grid search directory: {grid_search_dir}")
-    logger.info(f"Proteins configured: {list(protein_configs.keys())}")
-
-    # Scan for trials (look for refined.cif files)
-    all_trials = scan_grid_search_results(grid_search_dir, target_filename=args.target_filename)
-    logger.info(f"Found {len(all_trials)} trials with refined.cif files")
-
-    if all_trials:
-        all_trials.summarize()  # Prints some summary stats, e.g. number of unique proteins
-    else:
-        logger.error("No trials found in grid search directory. Exiting with status 1.")
-        sys.exit(1)
+    all_trials, protein_configs = setup_evaluation_parameters(args)
 
     logger.info("Pre-loading reference structures for each protein for coordinate extraction")
     reference_atom_arrays = {}
@@ -313,7 +292,7 @@ def main(args: argparse.Namespace):
     )
 
     df = pd.DataFrame(null_results + all_results)
-    df.to_csv(grid_search_dir / "lddt_results.csv", index=False)
+    df.to_csv(args.grid_search_results_path / "lddt_results.csv", index=False)
 
 
 def process_trial_with_selection(
@@ -378,5 +357,5 @@ def process_trial_with_selection(
 
 
 if __name__ == "__main__":
-    args = parse_args("Evaluate LDDT on grid search results.")
+    args = parse_eval_args("Evaluate LDDT on grid search results.")
     main(args)
diff --git a/scripts/eval/rscc_grid_search_script.py b/scripts/eval/rscc_grid_search_script.py
index 1819c5f1..78bbca61 100644
--- a/scripts/eval/rscc_grid_search_script.py
+++ b/scripts/eval/rscc_grid_search_script.py
@@ -17,7 +17,6 @@
 import argparse
 import copy
 import traceback
-from pathlib import Path
 
 import numpy as np
 import pandas as pd
@@ -29,8 +28,7 @@
 from loguru import logger
 from sampleworks.core.forward_models.xray.real_space_density_deps.qfit.volume import XMap
 from sampleworks.eval.constants import DEFAULT_SELECTION_PADDING
-from sampleworks.eval.eval_dataclasses import ProteinConfig
-from sampleworks.eval.grid_search_eval_utils import parse_args, scan_grid_search_results
+from sampleworks.eval.grid_search_eval_utils import parse_eval_args, setup_evaluation_parameters
 from sampleworks.eval.metrics import rscc
 from sampleworks.eval.structure_utils import (
     get_asym_unit_from_structure,
@@ -50,31 +48,7 @@
 
 # TODO consolidate eval script logic: https://github.com/diff-use/sampleworks/issues/93
 def main(args: argparse.Namespace):
-    workspace_root = Path(args.workspace_root)
-    grid_search_dir = workspace_root / "grid_search_results"
-
-    # Protein configurations: base map paths, structure selections, and resolutions
-    protein_inputs_dir = args.grid_search_inputs_path or workspace_root
-    protein_configs = ProteinConfig.from_csv(protein_inputs_dir, args.protein_configs_csv)
-
-    logger.info(f"Grid search directory: {grid_search_dir}")
-    logger.info(f"Proteins configured: {list(protein_configs.keys())}")
-
-    # Test base map path resolution
-    logger.debug("Testing base map path resolution:")
-    for _, config in protein_configs.items():
-        for occ in args.occupancies:
-            altloc_occ = {"A": occ, "B": 1.0 - occ}
-            path = config.get_base_map_path_for_occupancy(altloc_occ)  # will warn if not found
-            if path:
-                logger.debug(f"  {config.protein} occupancies={altloc_occ}: {path}")
-
-    # Scan for trials (look for refined.cif files)
-    all_trials = scan_grid_search_results(grid_search_dir, target_filename=args.target_filename)
-    logger.info(f"Found {len(all_trials)} trials with refined.cif files")
-
-    if all_trials:
-        all_trials.summarize()  # Prints some summary stats, e.g. number of unique proteins
+    all_trials, protein_configs = setup_evaluation_parameters(args)
 
     logger.info("Pre-loading reference structures for each protein for coordinate extraction")
     ref_coords = {}
@@ -87,7 +61,6 @@ def main(args: argparse.Namespace):
                 ref_coords[(protein_key, selection)] = protein_ref_coords[selection]
 
     # Calculate RSCC for all trials
-    # (BIG) TODO: implement a sliding-window version (global can be achieved with diff't selections.
     logger.info("Calculating RSCC values for all trials...")
     logger.warning(
         "Note: RSCC is computed on the region around altloc residues (defined by selection)"
@@ -296,7 +269,7 @@ def main(args: argparse.Namespace):
 
     # Create DataFrame from results
     df = pd.DataFrame(results)
-    df.to_csv(grid_search_dir / "rscc_results.csv", index=False)
+    df.to_csv(args.grid_search_results_path / "rscc_results.csv", index=False)
 
     if not df.empty:
         # Remove error column for display if present
@@ -321,5 +294,5 @@ def main(args: argparse.Namespace):
 
 
 if __name__ == "__main__":
-    args = parse_args("Evaluate RSCC on grid search results.")
+    args = parse_eval_args("Evaluate RSCC on grid search results.")
     main(args)
diff --git a/scripts/eval/run_and_process_phenix_clashscore.py b/scripts/eval/run_and_process_phenix_clashscore.py
index c291458c..72c90c1b 100644
--- a/scripts/eval/run_and_process_phenix_clashscore.py
+++ b/scripts/eval/run_and_process_phenix_clashscore.py
@@ -1,4 +1,3 @@
-import argparse
 import json
 import subprocess
 from pathlib import Path
@@ -7,41 +6,10 @@
 import pandas as pd
 from loguru import logger
 from sampleworks.eval.eval_dataclasses import Trial
-from sampleworks.eval.grid_search_eval_utils import scan_grid_search_results
-
-
-# TODO unify this with the other parse_args most eval scripts use.
-#  https://github.com/diff-use/sampleworks/issues/110
-def parse_args() -> argparse.Namespace:
-    """
-    Arguments required for evaluating clashscores with phenix.
-    These are currently slightly different from the other eval scripts.
-    """
-    parser = argparse.ArgumentParser(
-        description="Crawl the workspace root for CIF files matching --target-filename and"
-        " run phenix.clashscore on them."
-    )
-    parser.add_argument(
-        "--workspace-root",
-        type=Path,
-        required=True,
-        help="Path containing the grid search results directory, e.g. if results are "
-        "at $HOME/grid_search_results, $HOME should be what you pass",
-    )
-    parser.add_argument(
-        "--n-jobs",
-        type=int,
-        help="Number of parallel jobs to run. -1 uses all CPUs.",
-        default=16,
-    )
-    parser.add_argument(
-        "--target-filename",
-        default="refined.cif",
-        help="Target filename for the CIF files to process",
-    )
-    return parser.parse_args()
+from sampleworks.eval.grid_search_eval_utils import parse_eval_args, setup_evaluation_parameters
 
 
+# TODO make more general: https://github.com/diff-use/sampleworks/issues/93
 def main(args) -> None:
     # check that phenix is installed and available, bail early if not.
     try:
@@ -51,13 +19,8 @@ def main(args) -> None:
             "phenix.clashscore is not available, make sure phenix is installed "
             " and that you have activated it, e.g. `source phenix-dir/phenix_env.sh`"
         )
-
-    workspace_root = Path(args.workspace_root)
-
-    # TODO make more general: https://github.com/diff-use/sampleworks/issues/93
-    grid_search_dir = workspace_root / "grid_search_results"
-    all_trials = scan_grid_search_results(grid_search_dir, target_filename=args.target_filename)
-    logger.info(f"Found {len(all_trials)} trials with {args.target_filename} files")
+    # The dropped variable is a list of ProteinConfigs, not used yet in this script
+    all_trials, _ = setup_evaluation_parameters(args)
 
     # Now loop over trials with joblib and get back tuples of trial level metrics
     clashscore_metrics = joblib.Parallel(n_jobs=args.n_jobs)(
@@ -75,7 +38,7 @@ def main(args) -> None:
 
     clashscore_df = pd.concat(clashscore_metrics, ignore_index=True)
     clashscore_df.to_csv(
-        workspace_root / "grid_search_results" / "clashscore_metrics.csv", index=False
+        args.grid_search_results_path / "clashscore_metrics.csv", index=False
     )
 
 
@@ -93,11 +56,11 @@ def process_one_trial(trial: Trial) -> pd.DataFrame:
     if retcode != 0:
         raise RuntimeError(f"grep failed with code {retcode}, the command was {' '.join(grep_cmd)}")
 
-    # phenix needs to be installed and on path for this to work. Also sh won't work with
+    # phenix needs to be installed and on path for this to work. Also, sh won't work with
     # phenix.clashscore because of that pesky period in the name.
     with logfile.open("w") as fn:
-        # phenix.clashscore generates a JSON file with both per-model scores as well as per-model
-        # lists of clashes.
+        # phenix.clashscore generates a JSON file with both per-model scores,
+        # as well as per-model lists of clashes.
         retcode = subprocess.call(
             ["phenix.clashscore", str(file_with_no_nans), "--json-filename", str(json_output)],
             stderr=fn,
@@ -110,7 +73,7 @@ def process_one_trial(trial: Trial) -> pd.DataFrame:
 
 def process_clashscore_json_output(json_output: Path) -> pd.DataFrame:
     """
-    Opens the json output file `json_output` and parses out the
+    Opens the JSON output file `json_output` and parses out the
     "summary_results", flattening it into rows which include the "model_name" field
 
     """
@@ -118,7 +81,7 @@ def process_clashscore_json_output(json_output: Path) -> pd.DataFrame:
         json_data = json.load(f)
 
     model_name = json_data.get("model_name")
-    # For now we're only collecting model-level summary statistics, but
+    # For now, we're only collecting model-level summary statistics, but
     # there are lists of specific clashes in each model too.
     summary_results = json_data.get("summary_results", {})
 
@@ -136,5 +99,7 @@ def process_clashscore_json_output(json_output: Path) -> pd.DataFrame:
 
 
 if __name__ == "__main__":
-    args = parse_args()
-    main(args)
+    argparse_description = "Crawl the workspace root for CIF files matching "
+    argparse_description += "--target-filename and run phenix.clashscore on them."
+    eval_args = parse_eval_args(description=argparse_description)
+    main(eval_args)
diff --git a/src/sampleworks/eval/grid_search_eval_utils.py b/src/sampleworks/eval/grid_search_eval_utils.py
index 0048f0f3..6bed7059 100644
--- a/src/sampleworks/eval/grid_search_eval_utils.py
+++ b/src/sampleworks/eval/grid_search_eval_utils.py
@@ -5,12 +5,13 @@
 
 import argparse
 import re
+import sys
 from importlib.resources import files
 from pathlib import Path
 
 from loguru import logger
 from sampleworks.eval.constants import OCCUPANCY_LEVELS
-from sampleworks.eval.eval_dataclasses import Trial, TrialList
+from sampleworks.eval.eval_dataclasses import Trial, TrialList, ProteinConfig
 from sampleworks.eval.occupancy_utils import extract_protein_and_occupancy
 from sampleworks.utils.guidance_constants import StructurePredictor
 
@@ -161,7 +162,7 @@ def get_method_and_model_name(model_name: str) -> tuple[str | None, str]:
     return method, model
 
 
-def parse_args(description: str | None = None):
+def parse_eval_args(description: str | None = None):
     """
     Return a common set of arguments for grid search evaluation scripts,
     with a custom description, which is passed to argparse.ArgumentParser.
@@ -170,24 +171,26 @@ def parse_args(description: str | None = None):
     """
     parser = argparse.ArgumentParser(description=description)
     parser.add_argument(
-        "--workspace-root",
+        "--grid-search-results-path",
         type=Path,
         required=True,
-        help="Path containing the grid search results directory, e.g. if results are "
-        "at $HOME/grid_search_results, $HOME should be what you pass",
+        help="Path to the top-level grid search results directory, usu. called "
+             "``grid_search_results``",
     )
+    # not technically used everywhere yet, but requiring it future-proofs.
     parser.add_argument(
         "--grid-search-inputs-path",
         type=Path,
-        help="Path to the directory containing the grid search inputs, if it is different "
-        "than the workspace root.",
+        required=True,
+        help="Path to the directory containing the grid search inputs, in particular "
+             "the protein configuration CSV file, maps, and reference structures.",
         default=None,
     )
     parser.add_argument(
         "--protein-configs-csv",
         type=Path,
-        help="Path to the CSV file containing protein configurations, like ${HOME}/configs.csv "
-        "Defaults to sampleworks/data/protein_configs.csv",
+        help="Path to the CSV file containing protein configurations, like "
+             "``${HOME}/configs.csv``. Defaults to sampleworks/data/protein_configs.csv",
         default=files("sampleworks.data") / "protein_configs.csv",
     )
     parser.add_argument(
@@ -209,3 +212,30 @@ def parse_args(description: str | None = None):
         default=16,
     )
     return parser.parse_args()
+
+
+def setup_evaluation_parameters(
+        args: argparse.Namespace
+) -> tuple[TrialList, dict[str, ProteinConfig]]:
+    grid_search_dir = Path(args.grid_search_results_path)
+
+    # Protein configurations: base map paths, structure selections, and resolutions
+    protein_inputs_dir = args.grid_search_inputs_path
+    protein_configs = ProteinConfig.from_csv(protein_inputs_dir, args.protein_configs_csv)
+
+    logger.info(f"Grid search directory: {grid_search_dir}")
+    logger.info(f"Proteins configured: {list(protein_configs.keys())}")
+
+    # Scan for experiments (look for refined.cif files)
+    all_trials = scan_grid_search_results(
+        grid_search_dir, target_filename=args.target_filename
+    )
+    logger.info(f"Found {len(all_trials)} experiments with refined.cif files")
+
+    if all_trials:
+        all_trials.summarize()  # Prints some summary stats, e.g. number of unique proteins
+    else:
+        logger.error("No experiments found in grid search directory. Exiting with status 1.")
+        sys.exit(1)
+
+    return all_trials, protein_configs