diff --git a/.github/workflows/python_package.yml b/.github/workflows/python_package.yml
index 1da0c77..113386c 100644
--- a/.github/workflows/python_package.yml
+++ b/.github/workflows/python_package.yml
@@ -5,7 +5,7 @@ on:
   workflow_call:
 
 env:
-  UV_VERSION: 0.9.5
+  UV_VERSION: 0.11.28
 
 jobs:
   Tests:
diff --git a/.github/workflows/workflow_linting.yml b/.github/workflows/workflow_linting.yml
index 2704d44..cfcd6bb 100644
--- a/.github/workflows/workflow_linting.yml
+++ b/.github/workflows/workflow_linting.yml
@@ -4,7 +4,7 @@ on:
   push:
 
 env:
-  PIXI_VERSION: v0.65.0
+  PIXI_VERSION: v0.72.2
 
 jobs:
   Tests:
@@ -21,4 +21,4 @@ jobs:
           cache: true
 
       - name: Run linting
-        run: pixi run lint --check
+        run: pixi run --locked lint --check
diff --git a/README.md b/README.md
index 7b1c84f..0a18d4a 100644
--- a/README.md
+++ b/README.md
@@ -30,7 +30,7 @@ To install the GCS connector for Hail/Spark, run
 pixi run setup-gcs
 ```
 
-Log in before running any Hail-dependent tools:
+Log in before running any Hail-dependent tools, requires [the gcloud cli be installed](https://docs.cloud.google.com/sdk/docs/install-sdk):
 
 ```bash
 gcloud auth application-default login
@@ -51,7 +51,7 @@ To install both connectors at once, run `pixi run setup-cloud`.
 
 ### Running the workflow
 
-The workflow does not bundle a default `configfile:` — pass one explicitly with
+The workflow does not set a default `configfile:` — pass one explicitly with
 `--configfile`. Two ready-made configs are provided under `workflows/config/`:
 
 - `config_gcs.yml` — reads all cloud inputs from GCS (`gs://gcp-public-data--gnomad/`,
diff --git a/divref/divref/alias.py b/divref/divref/alias.py
index f5a9989..3b9c05f 100644
--- a/divref/divref/alias.py
+++ b/divref/divref/alias.py
@@ -1,4 +1,2 @@
-from typing import TypeAlias
-
-HailPath: TypeAlias = str
+type HailPath = str
 """Type alias for filesystem paths accepted by Hail: local, S3 (s3a://), GCS (gs://), or HDFS (hdfs://)."""  # noqa: E501
diff --git a/divref/divref/defaults.py b/divref/divref/defaults.py
index 5edef46..fe821de 100644
--- a/divref/divref/defaults.py
+++ b/divref/divref/defaults.py
@@ -22,8 +22,11 @@
 )
 """HGDP+1KG sample metadata (AWS S3 alternative)."""
 
-POPULATIONS: list[str] = ["afr", "amr", "eas", "sas", "nfe"]
+# The five continental genetic-ancestry groups DivRef selects from the gnomAD HGDP+1KG legend
+# (a subset of gnomAD's full ancestry set, which also includes e.g. fin, asj, ami, mid, oth).
+# Update this list only to track a deliberate change to the DivRef population definition.
+POPULATIONS: Final[list[str]] = ["afr", "amr", "eas", "sas", "nfe"]
 """Default HGDP+1KG populations."""
 
-REFERENCE_GENOME: str = "GRCh38"
+REFERENCE_GENOME: Final[str] = "GRCh38"
 """Default reference genome assembly."""
diff --git a/divref/divref/duckdb_index.py b/divref/divref/duckdb_index.py
index bf16c3c..eab4e14 100644
--- a/divref/divref/duckdb_index.py
+++ b/divref/divref/duckdb_index.py
@@ -30,6 +30,24 @@ class TablePair(Metric):
     sites_table_path: Path
 
 
+def sequences_table_exists(conn: duckdb.DuckDBPyConnection) -> bool:
+    """
+    Return whether the `sequences` table exists in the connected DuckDB index.
+
+    Args:
+        conn: Open DuckDB connection to a DivRef index.
+
+    Returns:
+        True if a `sequences` table is present.
+    """
+    return (
+        conn.execute(
+            "SELECT 1 FROM information_schema.tables WHERE table_name = 'sequences'"
+        ).fetchone()
+        is not None
+    )
+
+
 def read_pops_legend(table_path: Path) -> list[str]:
     """
     Read a Hail table's population legend from its globals.
diff --git a/divref/divref/hail.py b/divref/divref/hail.py
index 044c701..bf0d095 100644
--- a/divref/divref/hail.py
+++ b/divref/divref/hail.py
@@ -18,7 +18,7 @@ def _export_gcs_credentials(gcs_credentials_path: Path | None) -> None:
     """
     if gcs_credentials_path is None:
         raise ValueError("gcs_credentials_path is required when use_s3 is False.")
-    if not gcs_credentials_path.exists():
+    if not gcs_credentials_path.is_file():
         raise FileNotFoundError(
             f"GCS credentials file not found at {gcs_credentials_path}. Run "
             "`gcloud auth application-default login` or pass a valid --gcs-credentials-path."
@@ -83,19 +83,19 @@ def hail_init(
     if not use_s3:
         _export_gcs_credentials(gcs_credentials_path)
 
-    jars_dir = os.path.join(pyspark.__path__[0], "jars")
+    jars_dir = Path(pyspark.__path__[0]) / "jars"
     cloud_jars: list[str] = []
     spark_conf: dict[str, str] = {}
 
     if use_s3:
-        hadoop_aws_jar = os.path.join(jars_dir, "hadoop-aws.jar")
-        aws_sdk_bundle_jar = os.path.join(jars_dir, "aws-java-sdk-bundle.jar")
+        hadoop_aws_jar = jars_dir / "hadoop-aws.jar"
+        aws_sdk_bundle_jar = jars_dir / "aws-java-sdk-bundle.jar"
         for jar in (hadoop_aws_jar, aws_sdk_bundle_jar):
-            if not os.path.exists(jar):
+            if not jar.is_file():
                 raise FileNotFoundError(
                     f"S3 connector JAR not found at {jar}. Run 'pixi run setup-s3' to download it."
                 )
-        cloud_jars.extend([hadoop_aws_jar, aws_sdk_bundle_jar])
+        cloud_jars.extend([str(hadoop_aws_jar), str(aws_sdk_bundle_jar)])
         spark_conf.update({
             "spark.hadoop.fs.s3a.impl": "org.apache.hadoop.fs.s3a.S3AFileSystem",
             # All workflow inputs live on public Open Data buckets that allow anonymous
@@ -112,13 +112,13 @@ def hail_init(
             "spark.hadoop.fs.s3a.threads.max": "64",
         })
     else:
-        gcs_jar = os.path.join(jars_dir, "gcs-connector.jar")
-        if not os.path.exists(gcs_jar):
+        gcs_jar = jars_dir / "gcs-connector.jar"
+        if not gcs_jar.is_file():
             raise FileNotFoundError(
                 f"GCS connector JAR not found at {gcs_jar}. "
                 "Run 'pixi run setup-gcs' to download it."
             )
-        cloud_jars.append(gcs_jar)
+        cloud_jars.append(str(gcs_jar))
         spark_conf.update({
             "spark.hadoop.fs.gs.impl": "com.google.cloud.hadoop.fs.gcs.GoogleHadoopFileSystem",
             "spark.hadoop.fs.AbstractFileSystem.gs.impl": "com.google.cloud.hadoop.fs.gcs.GoogleHadoopFS",  # noqa: E501
diff --git a/divref/divref/haplotype.py b/divref/divref/haplotype.py
index 10537c6..28eb810 100644
--- a/divref/divref/haplotype.py
+++ b/divref/divref/haplotype.py
@@ -1,28 +1,9 @@
 """Shared utilities for Hail-based DivRef pipeline tools."""
 
-from typing import Hashable
-from typing import TypeVar
-
 import hail as hl
 
 from divref import defaults
 
-_V = TypeVar("_V", bound=Hashable)
-"""Type variable for hashable dictionary values used in to_hashable_items."""
-
-
-def to_hashable_items(d: dict[str, _V]) -> tuple[tuple[str, _V], ...]:
-    """
-    Convert a dictionary to a sorted tuple of items for use as a hashable key.
-
-    Args:
-        d: Dictionary with hashable values to convert.
-
-    Returns:
-        Sorted tuple of (key, value) pairs.
-    """
-    return tuple(sorted(d.items()))
-
 
 def _max_reference_end(variants: hl.Expression) -> hl.Expression:
     """
@@ -83,7 +64,13 @@ def get_haplo_sequence(
         raise ValueError(
             "get_haplo_sequence requires at least one variant; received an empty sequence"
         )
-    sorted_variants = hl.sorted(variants, key=lambda x: (x.locus.position, hl.len(x.alleles[0])))
+    # Tertiary tiebreak on alt length so a substitution (len(alt) == 1) composes before a pure
+    # insertion (len(alt) > 1) at the same position. A remaining tie (same position, ref length,
+    # and alt length) falls back to input order, but that requires two alleles at one site, which
+    # cannot occur on a single phased haplotype.
+    sorted_variants = hl.sorted(
+        variants, key=lambda x: (x.locus.position, hl.len(x.alleles[0]), hl.len(x.alleles[1]))
+    )
     min_pos = sorted_variants[0].locus.position
     max_ref_end = _max_reference_end(sorted_variants)
     full_context = hl.get_sequence(
@@ -168,7 +155,9 @@ def haplo_coordinates(
     """
     # Same sort key as get_haplo_sequence so the two stay in lockstep; only the minimum position
     # (`[0].locus.position`) is read here, and `_max_reference_end` is order-independent.
-    sorted_variants = hl.sorted(variants, key=lambda x: (x.locus.position, hl.len(x.alleles[0])))
+    sorted_variants = hl.sorted(
+        variants, key=lambda x: (x.locus.position, hl.len(x.alleles[0]), hl.len(x.alleles[1]))
+    )
     min_variant = sorted_variants[0]
     return hl.struct(
         start=min_variant.locus.position - 1 - window_size,
diff --git a/divref/divref/haplotype_compat.py b/divref/divref/haplotype_compat.py
index ff78f25..e2344e1 100644
--- a/divref/divref/haplotype_compat.py
+++ b/divref/divref/haplotype_compat.py
@@ -12,7 +12,9 @@
 # A component variant: (contig, pos, ref, alt). pos is 1-based.
 Variant = tuple[str, int, str, str]
 
-# Reason labels in precedence order (first match wins in classify_pair) and stable output order.
+# The complete set of incompatibility reason labels classify_pair can return. This tuple is
+# documentation only: classify_pair selects a reason via its own if/elif order (not this tuple),
+# and compatibility_flag emits flags alphabetically (not in this order).
 # A SNP co-located with an indel is NOT listed: the SNP substitutes the shared base and the indel
 # acts on/after it, so the overlap composes to a well-defined haplotype (see classify_pair). An
 # insertion anchored inside a deletion IS a conflict (`insertion_in_deletion`): its anchor base is
@@ -69,11 +71,21 @@ def parse_variants_string(s: str) -> list[Variant]:
 
     Returns:
         Variants sorted by ascending position, then by reference-allele length.
+
+    Raises:
+        ValueError: If a token is not `contig:position:ref:alt` or its position is not an integer.
     """
     out: list[Variant] = []
     for token in s.split(","):
-        contig, pos, ref, alt = token.split(":")
-        out.append((contig, int(pos), ref, alt))
+        fields = token.split(":")
+        if len(fields) != 4:
+            raise ValueError(f"expected 'contig:pos:ref:alt', got {token!r} in {s!r}")
+        contig, pos, ref, alt = fields
+        try:
+            position = int(pos)
+        except ValueError as e:
+            raise ValueError(f"non-integer position in variant token {token!r} in {s!r}") from e
+        out.append((contig, position, ref, alt))
     out.sort(key=lambda v: (v[1], len(v[2])))
     return out
 
@@ -126,7 +138,7 @@ def _same_position_reason(v1: Variant, v2: Variant, k1: str, k2: str) -> str:
 
 def classify_pair(v1: Variant, v2: Variant) -> str | None:
     """
-    Classify an adjacent variant pair into an incompatibility reason.
+    Classify a variant pair (`v1` at or before `v2` by position) into an incompatibility reason.
 
     Returns `None` when the pair is compatible: either it does not overlap (`variant_distance >= 0`)
     or it is a SNP co-located with an indel, which composes to a well-defined haplotype (the SNP
diff --git a/divref/divref/main.py b/divref/divref/main.py
index b240ced..7fd8d9a 100644
--- a/divref/divref/main.py
+++ b/divref/divref/main.py
@@ -46,7 +46,7 @@ def run() -> None:
     """Set up logging, then hand over to defopt for running command line tools."""
     setup_logging()
     logger = logging.getLogger("divref")
-    logger.info("Executing: " + " ".join(sys.argv))
+    logger.info("Executing: %s", " ".join(sys.argv))
     defopt.run(
         funcs=_tools,
         argv=sys.argv[1:],
diff --git a/divref/divref/tools/append_contig_to_duckdb_index.py b/divref/divref/tools/append_contig_to_duckdb_index.py
index 0f0c068..b65da08 100644
--- a/divref/divref/tools/append_contig_to_duckdb_index.py
+++ b/divref/divref/tools/append_contig_to_duckdb_index.py
@@ -17,6 +17,7 @@
 from divref import defaults
 from divref.duckdb_index import TablePair
 from divref.duckdb_index import read_and_validate_pops_legends
+from divref.duckdb_index import sequences_table_exists
 from divref.haplotype import get_haplo_sequence
 from divref.haplotype import haplo_coordinates
 from divref.haplotype_compat import compatibility_flag
@@ -65,10 +66,7 @@ def read_window_size(conn: duckdb.DuckDBPyConnection) -> int:
 
 def sequences_row_count(conn: duckdb.DuckDBPyConnection) -> int:
     """Current number of rows in `sequences`, or 0 if the table does not exist yet."""
-    exists = conn.execute(
-        "SELECT 1 FROM information_schema.tables WHERE table_name = 'sequences'"
-    ).fetchone()
-    if exists is None:
+    if not sequences_table_exists(conn):
         return 0
     row = conn.execute("SELECT COUNT(*) FROM sequences").fetchone()
     if row is None:
@@ -78,10 +76,7 @@ def sequences_row_count(conn: duckdb.DuckDBPyConnection) -> int:
 
 def _contig_already_appended(conn: duckdb.DuckDBPyConnection, contig: str) -> bool:
     """Whether the `sequences` table already holds any rows for `contig` (False if no table yet)."""
-    exists = conn.execute(
-        "SELECT 1 FROM information_schema.tables WHERE table_name = 'sequences'"
-    ).fetchone()
-    if exists is None:
+    if not sequences_table_exists(conn):
         return False
     row = conn.execute("SELECT 1 FROM sequences WHERE contig = ? LIMIT 1", [contig]).fetchone()
     return row is not None
@@ -279,6 +274,7 @@ def build_contig_sequences_table(
     seq_ht = seq_ht.annotate(
         sequence=get_haplo_sequence(window_size, seq_ht.variants),
         contig=seq_ht.variants[0].locus.contig,
+        # `start`/`end` are 0-based half-open (from `haplo_coordinates`; variant loci are 1-based).
         start=coords.start,
         end=coords.end,
     )
@@ -456,7 +452,10 @@ def iter_dataframe_chunks(
             yield df
 
 
-@dataclass(frozen=True, kw_only=True)
+# eq=False so the frozen dataclass keeps a (default, identity-based) __hash__ despite its list
+# fields; without it, frozen+eq would synthesize a __hash__ that raises TypeError on unhashable
+# lists. The struct is only ever field-accessed, never compared or hashed by value.
+@dataclass(frozen=True, kw_only=True, eq=False)
 class _RemapArrays:
     """
     The four pop-legend remap arrays used to build a contig's sequences table.
@@ -579,10 +578,7 @@ def _stream_tsv_into_sequences(
     Returns:
         The number of rows appended for this contig.
     """
-    table_exists = conn.execute(
-        "SELECT 1 FROM information_schema.tables WHERE table_name = 'sequences'"
-    ).fetchone()
-    if table_exists is None:
+    if not sequences_table_exists(conn):
         # `haplotype_filter` is appended last in both the schema-defining empty frame and every
         # inserted chunk, so column order stays consistent across the CREATE and the INSERTs.
         empty_df = _add_compatibility_flag(
@@ -600,7 +596,9 @@ def _stream_tsv_into_sequences(
     ):
         chunk_df = _add_compatibility_flag(chunk)
         conn.register("chunk_df", chunk_df)
-        conn.execute("INSERT INTO sequences SELECT * FROM chunk_df")
+        # BY NAME matches columns by name, not position, so a future change to the export/scan
+        # column order surfaces as a bind error rather than silently misaligning columns.
+        conn.execute("INSERT INTO sequences BY NAME SELECT * FROM chunk_df")
         conn.unregister("chunk_df")
         appended_rows += chunk_df.height
     return appended_rows
@@ -728,7 +726,8 @@ def append_contig_to_duckdb_index(
             f"Spark executor memory must be at least 1GB. Saw {spark_executor_memory_gb}GB."
         )
 
-    out_duckdb_file: Path = Path(f"{str(output_base)}.haplotypes_gnomad_merge.index.duckdb")
+    out_duckdb_file: Path = Path(f"{output_base}.haplotypes_gnomad_merge.index.duckdb")
+    # readable (not writable): enforces the index file already exists, i.e. init_duckdb_index ran.
     assert_path_is_readable(out_duckdb_file)
 
     table_pairs: list[TablePair] = list(TablePair.read(in_table_pairs_tsv))
diff --git a/divref/divref/tools/compute_haplotypes.py b/divref/divref/tools/compute_haplotypes.py
index 7f996d2..e9a67ae 100644
--- a/divref/divref/tools/compute_haplotypes.py
+++ b/divref/divref/tools/compute_haplotypes.py
@@ -43,7 +43,7 @@ def _haploid_adjusted_call(
 def _compute_locus_groups(
     variants_ht: hl.Table,
     window_size: int,
-) -> tuple[dict[int, int], int]:
+) -> dict[int, int]:
     """
     Assign each variant a global `locus_group` id by cutting at gaps ≥ `window_size`.
 
@@ -60,8 +60,7 @@ def _compute_locus_groups(
         window_size: adjacency-gap threshold in bp.
 
     Returns:
-        `(group_of, n_groups)` where `group_of` maps `row_idx → locus_group_id` and
-        `n_groups` is the total number of groups.
+        `group_of`, mapping `row_idx → locus_group_id`.
     """
     rows = variants_ht.key_by().select("row_idx", "locus", "ref_len").collect()
     logger.info("compute_locus_groups: collected %d variants to the driver", len(rows))
@@ -76,7 +75,7 @@ def _compute_locus_groups(
         group_of[v.row_idx] = current_group
         prev_end = max(prev_end, v.locus.position + v.ref_len)
         prev_contig = v.locus.contig
-    return group_of, current_group + 1
+    return group_of
 
 
 def _multi_member_locus_groups(rows_with_groups: hl.Table) -> hl.Table:
@@ -296,7 +295,8 @@ def _attach_component_info(hap_table: hl.Table, variants_ht: hl.Table) -> hl.Tab
     logger.info("attach_component_info: collected %d variant components for broadcast", len(pairs))
     # Keyed by int32 to match the `hl.int32(idx)` lookup below; the explicit dtype also keeps the
     # literal well-typed when `pairs` is empty (no haplotype-referenced variants), where
-    # `hl.literal({})` would otherwise fail to infer the key/value types.
+    # `hl.literal({})` would otherwise fail to infer the key/value types. The int64->int32 downcast
+    # of `row_idx` at the lookup is safe: `row_idx` is a per-contig variant index, well below 2^31.
     components_dict = hl.literal(
         dict(pairs),
         dtype=hl.tdict(
@@ -607,8 +607,10 @@ def compute_haplotypes(
         variant_freq_threshold: Minimum gnomAD population allele frequency to retain a variant.
         haplotype_freq_threshold: Minimum estimated gnomAD allele frequency for the haplotype to
             be retained.
-        output_base: Base output path; writes `{output_base}.variants.ht` (per-variant
-            checkpoint) and the final `{output_base}.ht`.
+        output_base: Base output path. Writes intermediate checkpoints
+            `{output_base}.variants.ht`, `.blocks.ht`, `.parents.ht`, and `.hap_ac.ht`
+            (the tool does not delete them; the Snakemake rule removes them post-run) and
+            the final `{output_base}.ht`.
         temp_dir: Local directory for Hail temporary files.
         spark_driver_memory_gb: Memory in GB to allocate to the Spark driver.
         spark_executor_memory_gb: Memory in GB to allocate to the Spark executor.
@@ -660,6 +662,17 @@ def compute_haplotypes(
         pop_int=hl.literal(pop_ints).get(sa_row.pop),
         sex_karyotype=sa_row.sex_karyotype,
     )
+    sample_counts = mt.aggregate_cols(
+        hl.struct(total=hl.agg.count(), assigned=hl.agg.count_where(hl.is_defined(mt.pop_int)))
+    )
+    logger.info(
+        "Dropped %d of %d samples whose population is not in the DivRef legend "
+        "(a gnomAD ancestry outside %s, or an unassigned population, indicating an "
+        "aneuploid karyotype)",
+        sample_counts.total - sample_counts.assigned,
+        sample_counts.total,
+        pop_legend,
+    )
     mt = mt.filter_cols(hl.is_defined(mt.pop_int))
     mt = mt.add_row_index().add_col_index()
     mt = mt.filter_entries(mt.freq[mt.pop_int].AF >= variant_freq_threshold)
@@ -668,6 +681,7 @@ def compute_haplotypes(
     # `_haploid_adjusted_call`. Autosomes, PAR, and chrY keep the original diploid call.
     adjusted_gt = _haploid_adjusted_call(mt.locus, mt.GT, mt.sex_karyotype)
     mt = mt.annotate_rows(
+        # call_stats n_alleles=2: gnomAD HGDP+1KG sites are biallelic (one alt per row).
         frequencies_by_pop=hl.agg.group_by(mt.pop_int, hl.agg.call_stats(adjusted_gt, 2)),
         ref_len=hl.len(mt.alleles[0]),
     )
@@ -678,7 +692,7 @@ def compute_haplotypes(
     if variants_ht.head(1).count() == 0:
         raise ValueError(f"No variants found with minimum population AF {variant_freq_threshold}.")
 
-    group_of, _n_groups = _compute_locus_groups(variants_ht, window_size)
+    group_of = _compute_locus_groups(variants_ht, window_size)
     group_lit = hl.literal(group_of, dtype=hl.tdict(hl.tint64, hl.tint32))
     mt = mt.annotate_rows(locus_group=group_lit[mt.row_idx])
 
@@ -747,4 +761,6 @@ def compute_haplotypes(
 
     logger.info("Writing final %s.ht ...", output_base)
     hap_table = hap_table.annotate_globals(pops=hl.literal(pop_legend))
+    # Coalesce to a fixed output partition count (independent of the input-side `min_partitions`)
+    # to bound the number of part-files written for the final table.
     hap_table.key_by("haplotype").naive_coalesce(64).write(f"{str(output_base)}.ht", overwrite=True)
diff --git a/divref/divref/tools/create_divref_fasta.py b/divref/divref/tools/create_divref_fasta.py
index 347adca..7626ec2 100644
--- a/divref/divref/tools/create_divref_fasta.py
+++ b/divref/divref/tools/create_divref_fasta.py
@@ -9,6 +9,8 @@
 from fgpyo.io import assert_path_is_readable
 from fgpyo.io import assert_path_is_writable
 
+from divref.duckdb_index import sequences_table_exists
+
 logger = logging.getLogger(__name__)
 
 
@@ -34,7 +36,7 @@ def create_divref_fasta(
         polars_chunk_size: Maximum number of rows per polars DataFrame batch read from DuckDB.
 
     Raises:
-        ValueError: If ``contigs`` is empty.
+        ValueError: If ``contigs`` is empty, or the index has no ``sequences`` table.
     """
     if not contigs:
         raise ValueError("Contig list must be provided.")
@@ -49,6 +51,11 @@ def create_divref_fasta(
         assert_path_is_writable(out_path)
 
     with duckdb.connect(str(duckdb_path), read_only=True) as conn:
+        if not sequences_table_exists(conn):
+            raise ValueError(
+                f"DuckDB index {duckdb_path} has no 'sequences' table; "
+                f"run append_contig_to_duckdb_index and finalize_duckdb_index first."
+            )
         for contig in contigs:
             logger.info(f"Creating FASTA for chromosome {contig} at {out_paths[contig]}")
             rows_written: int = 0
@@ -75,10 +82,12 @@ def iter_sequence_chunks(
     chunk_size: int,
 ) -> Iterator[polars.DataFrame]:
     """
-    Yield polars DataFrames of ``(sequence_id, sequence)`` rows for one contig.
+    Yield polars DataFrames of ``(sequence_id, sequence)`` rows for one contig, in genomic order.
 
-    Streams the DuckDB result set as Arrow record batches and converts each batch to polars,
-    bounding in-process memory by ``chunk_size`` rows.
+    Rows are ordered by genomic ``start`` (then ``sequence_id`` to break ties) so the FASTA output
+    is deterministic across runs. Streams the DuckDB result set as Arrow record batches via
+    ``to_arrow_reader`` and converts each batch to polars, bounding in-process memory by
+    ``chunk_size`` rows.
 
     Args:
         conn: Open DuckDB connection to the DivRef index.
@@ -88,11 +97,14 @@ def iter_sequence_chunks(
     Yields:
         Polars DataFrame batches with ``sequence_id`` and ``sequence`` columns.
     """
+    # ORDER BY genomic start (contig is fixed by the filter) so FASTA output is deterministic
+    # across runs; sequence_id is a unique tiebreak for rows sharing a start position.
     result = conn.execute(
-        "SELECT sequence_id, sequence FROM sequences WHERE contig = $contig",
+        "SELECT sequence_id, sequence FROM sequences WHERE contig = $contig "
+        "ORDER BY start, sequence_id",
         {"contig": contig},
     )
-    for batch in result.fetch_record_batch(chunk_size):
+    for batch in result.to_arrow_reader(chunk_size):
         df = polars.from_arrow(batch)
         # from_arrow on a RecordBatch always returns a DataFrame; assert to narrow the type and
         # fail loudly rather than silently dropping rows should that ever change.
diff --git a/divref/divref/tools/extract_gnomad_afs.py b/divref/divref/tools/extract_gnomad_afs.py
index ada66fc..2537fa3 100644
--- a/divref/divref/tools/extract_gnomad_afs.py
+++ b/divref/divref/tools/extract_gnomad_afs.py
@@ -1,4 +1,4 @@
-"""Tool to extract gnomAD variant and sample frequency data for the DivRef pipeline."""
+"""Tool to extract gnomAD per-population variant allele frequencies for the DivRef pipeline."""
 
 from pathlib import Path
 
@@ -8,7 +8,6 @@
 from divref import defaults
 from divref.alias import HailPath
 from divref.hail import hail_init
-from divref.haplotype import to_hashable_items
 
 
 def extract_gnomad_afs(
@@ -25,11 +24,11 @@ def extract_gnomad_afs(
     use_s3: bool = False,
 ) -> None:
     """
-    Extract gnomAD variant and sample frequency data for downstream pipeline tools.
+    Extract gnomAD per-population variant allele frequencies for downstream pipeline tools.
 
     Reads the gnomAD v3.1.2 HGDP/1KG subset, extracts per-population allele frequencies
     for the specified populations, filters to variants above the frequency threshold in at
-    least one population, and writes compact variant annotation and sample metadata tables.
+    least one population, and writes a compact variant annotation Hail table.
 
     Args:
         in_gnomad_sites_table: Path to the gnomAD HGDP/1KG sites table.
@@ -64,11 +63,11 @@ def extract_gnomad_afs(
     va = hl.filter_intervals(va_all, [interval])
 
     freq_meta = va.globals.gnomad_freq_meta.collect()[0]
-    map_to_index = {to_hashable_items(x): i for i, x in enumerate(freq_meta)}
+    map_to_index = {frozenset(x.items()): i for i, x in enumerate(freq_meta)}
 
     pop_indices = []
     for pop in populations:
-        idx = map_to_index.get(to_hashable_items({"group": "adj", "pop": pop}))
+        idx = map_to_index.get(frozenset({"group": "adj", "pop": pop}.items()))
         if idx is None:
             raise ValueError(f"Population {pop!r} not found in gnomAD frequency metadata")
         pop_indices.append(idx)
diff --git a/divref/divref/tools/extract_gnomad_single_afs.py b/divref/divref/tools/extract_gnomad_single_afs.py
index 0fa0ef0..1c7a6b1 100644
--- a/divref/divref/tools/extract_gnomad_single_afs.py
+++ b/divref/divref/tools/extract_gnomad_single_afs.py
@@ -1,4 +1,4 @@
-"""Tool to extract gnomAD variant and sample frequency data for the DivRef pipeline."""
+"""Tool to extract gnomAD per-population single-variant allele frequencies."""
 
 import operator
 from dataclasses import dataclass
@@ -11,7 +11,6 @@
 
 from divref import defaults
 from divref.hail import hail_init
-from divref.haplotype import to_hashable_items
 
 
 @unique
@@ -44,13 +43,12 @@ class GnomadCloud(StrEnum):
     (GnomadVersion.GENOMES_312, GnomadCloud.GCS): (
         "gs://gcp-public-data--gnomad/release/3.1.2/ht/genomes/gnomad.genomes.v3.1.2.sites.ht"
     ),
+    # Same tables as extract_gnomad_afs reads; single-sourced from defaults to avoid drift.
     (GnomadVersion.HGDP_1KG_312, GnomadCloud.S3): (
-        "s3a://gnomad-public-us-east-1/release/3.1.2/ht/genomes/"
-        "gnomad.genomes.v3.1.2.hgdp_1kg_subset_variant_annotations.ht"
+        defaults.GNOMAD_HGDP_1KG_VARIANT_ANNOTATION_HAIL_TABLE_S3
     ),
     (GnomadVersion.HGDP_1KG_312, GnomadCloud.GCS): (
-        "gs://gcp-public-data--gnomad/release/3.1.2/ht/genomes/"
-        "gnomad.genomes.v3.1.2.hgdp_1kg_subset_variant_annotations.ht"
+        defaults.GNOMAD_HGDP_1KG_VARIANT_ANNOTATION_HAIL_TABLE
     ),
 }
 
@@ -138,7 +136,7 @@ def extract_gnomad_single_afs(
     *,
     gnomad_version: GnomadVersion,
     contig: str,
-    freq_threshold: float = 0,
+    freq_threshold: float = 0.0,
     no_apply_filters: bool = False,
     populations: list[str] = defaults.POPULATIONS,
     reference_genome: str = defaults.REFERENCE_GENOME,
@@ -150,7 +148,7 @@ def extract_gnomad_single_afs(
     spark_executor_memory_gb: int = 1,
 ) -> None:
     """
-    Extract gnomAD variant and sample frequency data for downstream pipeline tools.
+    Extract gnomAD per-population single-variant allele frequencies for downstream pipeline tools.
 
     Reads a gnomAD sites table and filters to variants above the frequency threshold in at least one
     population. Writes up to two outputs: a Hail table at `out_sites_hail_table` for downstream
@@ -185,6 +183,8 @@ def extract_gnomad_single_afs(
         raise ValueError("At least one of out_sites_hail_table or out_sites_tsv must be provided")
 
     # validate output paths before starting Hail
+    if out_sites_hail_table is not None:
+        assert_path_is_writable(out_sites_hail_table)
     if out_sites_tsv is not None:
         assert_path_is_writable(out_sites_tsv)
 
@@ -205,11 +205,11 @@ def extract_gnomad_single_afs(
     va = hl.filter_intervals(va_all, [interval])
 
     freq_meta = operator.attrgetter(schema.freq_meta_path)(va.globals).collect()[0]
-    map_to_index = {to_hashable_items(x): i for i, x in enumerate(freq_meta)}
+    map_to_index = {frozenset(x.items()): i for i, x in enumerate(freq_meta)}
 
     pop_indices = []
     for pop in populations:
-        idx = map_to_index.get(to_hashable_items({"group": "adj", schema.pop_key: pop}))
+        idx = map_to_index.get(frozenset({"group": "adj", schema.pop_key: pop}.items()))
         if idx is None:
             raise ValueError(f"Population {pop!r} not found in gnomAD frequency metadata")
         pop_indices.append(idx)
diff --git a/divref/divref/tools/finalize_duckdb_index.py b/divref/divref/tools/finalize_duckdb_index.py
index 9ba4a78..49a7b89 100644
--- a/divref/divref/tools/finalize_duckdb_index.py
+++ b/divref/divref/tools/finalize_duckdb_index.py
@@ -6,6 +6,8 @@
 import duckdb
 from fgpyo.io import assert_path_is_readable
 
+from divref.duckdb_index import sequences_table_exists
+
 logger = logging.getLogger(__name__)
 
 
@@ -25,14 +27,11 @@ def finalize_duckdb_index(
     Raises:
         ValueError: If the DuckDB index has no `sequences` table.
     """
-    out_duckdb_file: Path = Path(f"{str(output_base)}.haplotypes_gnomad_merge.index.duckdb")
+    out_duckdb_file: Path = Path(f"{output_base}.haplotypes_gnomad_merge.index.duckdb")
     assert_path_is_readable(out_duckdb_file)
 
     with duckdb.connect(str(out_duckdb_file)) as conn:
-        sequences_exists = conn.execute(
-            "SELECT 1 FROM information_schema.tables WHERE table_name = 'sequences'"
-        ).fetchone()
-        if sequences_exists is None:
+        if not sequences_table_exists(conn):
             raise ValueError(
                 f"DuckDB index {out_duckdb_file} has no 'sequences' table; "
                 f"run append_contig_to_duckdb_index before finalizing."
diff --git a/divref/divref/tools/gnomad_hail_table_test_data.py b/divref/divref/tools/gnomad_hail_table_test_data.py
index 04583c5..e410565 100644
--- a/divref/divref/tools/gnomad_hail_table_test_data.py
+++ b/divref/divref/tools/gnomad_hail_table_test_data.py
@@ -125,6 +125,9 @@ def gnomad_hail_table_test_data(
         gcs_credentials_path: Path to GCS default credentials JSON file.
         spark_driver_memory_gb: Memory in GB to allocate to the Spark driver.
         spark_executor_memory_gb: Memory in GB to allocate to the Spark executor.
+
+    Raises:
+        ValueError: If `loci` is empty.
     """
     if not loci:
         raise ValueError("loci must contain at least one interval.")
diff --git a/divref/divref/tools/init_duckdb_index.py b/divref/divref/tools/init_duckdb_index.py
index 21f9cff..095c0ac 100644
--- a/divref/divref/tools/init_duckdb_index.py
+++ b/divref/divref/tools/init_duckdb_index.py
@@ -51,7 +51,7 @@ def init_duckdb_index(
     """
     assert_path_is_readable(in_table_pairs_tsv)
 
-    out_duckdb_file: Path = Path(f"{str(output_base)}.haplotypes_gnomad_merge.index.duckdb")
+    out_duckdb_file: Path = Path(f"{output_base}.haplotypes_gnomad_merge.index.duckdb")
     if out_duckdb_file.exists():
         if not force:
             raise FileExistsError(
diff --git a/divref/pyproject.toml b/divref/pyproject.toml
index c041ab6..9d95de8 100644
--- a/divref/pyproject.toml
+++ b/divref/pyproject.toml
@@ -11,7 +11,7 @@ authors         = [{ name="Fulcrum Genomics LLC", email="contact@fulcrumgenomics
 requires-python = ">=3.12,<3.14"
 dependencies    = [
     "defopt~=6.4",
-    "duckdb>=1.0",
+    "duckdb>=1.4.0",
     "fgmetric>=0.2.0",
     "fgpyo>=1.5.1",
     "hail>=0.2",
diff --git a/divref/tests/test_hail.py b/divref/tests/test_hail.py
index 879425c..5e1ff57 100644
--- a/divref/tests/test_hail.py
+++ b/divref/tests/test_hail.py
@@ -17,3 +17,18 @@ def test_hail_init_requires_credentials_for_gcs() -> None:
     """GCS mode with no credentials path raises ValueError."""
     with pytest.raises(ValueError, match="gcs_credentials_path is required"):
         hail_init(gcs_credentials_path=None, use_s3=False)
+
+
+@pytest.mark.parametrize(("driver_gb", "executor_gb"), [(0, 1), (1, 0)])
+def test_hail_init_rejects_sub_1gb_memory(driver_gb: int, executor_gb: int) -> None:
+    """
+    Spark driver/executor memory below 1GB fails loudly before starting Hail.
+
+    The memory guards run before any credentials/JAR resolution, so ``use_s3=True`` isolates them.
+    """
+    with pytest.raises(ValueError, match="at least 1GB"):
+        hail_init(
+            spark_driver_memory_gb=driver_gb,
+            spark_executor_memory_gb=executor_gb,
+            use_s3=True,
+        )
diff --git a/divref/tests/test_haplotype.py b/divref/tests/test_haplotype.py
index 36ba4d9..b011a62 100644
--- a/divref/tests/test_haplotype.py
+++ b/divref/tests/test_haplotype.py
@@ -9,7 +9,6 @@
 
 from divref.haplotype import get_haplo_sequence
 from divref.haplotype import haplo_coordinates
-from divref.haplotype import to_hashable_items
 from divref.haplotype import variant_distance
 
 # ---------------------------------------------------------------------------
@@ -21,31 +20,6 @@ def _make_variant(position: int, ref: str, alt: str, contig: str = "chr1") -> hl
     return hl.Struct(locus=hl.Struct(contig=contig, position=position), alleles=[ref, alt])
 
 
-def _make_haplotype_table(variant_positions: list[tuple[str, int, str, str]]) -> hl.Table:
-    variant_type = hl.tstruct(
-        locus=hl.tstruct(contig=hl.tstr, position=hl.tint32), alleles=hl.tarray(hl.tstr)
-    )
-    row_type = hl.tstruct(
-        variants=hl.tarray(variant_type),
-        haplotype=hl.tarray(hl.tstr),
-        gnomad_freqs=hl.tarray(hl.tfloat64),
-    )
-    variants = [
-        {"locus": {"contig": contig, "position": pos}, "alleles": [ref, alt]}
-        for contig, pos, ref, alt in variant_positions
-    ]
-    return hl.Table.parallelize(
-        [
-            {
-                "variants": variants,
-                "haplotype": [str(i) for i in range(len(variants))],
-                "gnomad_freqs": [0.1] * len(variants),
-            }
-        ],
-        schema=row_type,
-    )
-
-
 # ---------------------------------------------------------------------------
 # get_haplo_sequence
 # ---------------------------------------------------------------------------
@@ -116,6 +90,9 @@ def test_get_haplo_sequence_deletion_consumes_interior_variant(
         # Composable overlaps: the alt is composed onto the reference, not concatenated.
         ([(4, "AAA", "D"), (6, "G", "GTT")], "23DTT78", "insertion composes inside a deletion"),
         ([(4, "X", "Y"), (4, "X", "XZZ")], "23YZZ56", "snp + insertion at one site"),
+        # Same pair with the insertion listed first: the alt-length tiebreak must still compose the
+        # SNP before the insertion, so the SNP is not dropped.
+        ([(4, "X", "XZZ"), (4, "X", "Y")], "23YZZ56", "snp + insertion, insertion listed first"),
         ([(4, "X", "Y"), (4, "XBC", "X")], "23Y78", "snp + deletion at one site"),
         # Genuinely-incompatible overlaps still resolve to a defined (flagged) sequence.
         ([(4, "AAA", "A"), (4, "AAAA", "A")], "23A89", "two deletions: the longer one wins"),
@@ -178,26 +155,6 @@ def test_get_haplo_sequence_empty_tuple_raises() -> None:
         get_haplo_sequence(context_size=2, variants=())
 
 
-# ---------------------------------------------------------------------------
-# to_hashable_items
-# ---------------------------------------------------------------------------
-
-
-def test_to_hashable_items_empty() -> None:
-    """to_hashable_items should return an empty tuple for an empty dict."""
-    assert to_hashable_items({}) == ()
-
-
-def test_to_hashable_items_single_entry() -> None:
-    """to_hashable_items should return a one-element tuple for a single-entry dict."""
-    assert to_hashable_items({"key": "value"}) == (("key", "value"),)
-
-
-def test_to_hashable_items_sorted_by_key() -> None:
-    """to_hashable_items should return items sorted by key regardless of insertion order."""
-    assert to_hashable_items({"b": 2, "a": 1, "c": 3}) == (("a", 1), ("b", 2), ("c", 3))
-
-
 # ---------------------------------------------------------------------------
 # variant_distance
 # ---------------------------------------------------------------------------
diff --git a/divref/tests/test_main.py b/divref/tests/test_main.py
index 409a7cd..b737372 100644
--- a/divref/tests/test_main.py
+++ b/divref/tests/test_main.py
@@ -1,5 +1,5 @@
+from collections.abc import Callable
 from inspect import isfunction
-from typing import Callable
 
 import pytest
 from defopt import signature
diff --git a/divref/tests/tools/test_create_divref_fasta.py b/divref/tests/tools/test_create_divref_fasta.py
index f20a472..61542a9 100644
--- a/divref/tests/tools/test_create_divref_fasta.py
+++ b/divref/tests/tools/test_create_divref_fasta.py
@@ -9,19 +9,21 @@
 from divref.tools.create_divref_fasta import create_divref_fasta
 
 
-def _build_index(db_path: Path, rows: list[tuple[str, str, str]]) -> None:
+def _build_index(db_path: Path, rows: list[tuple[str, str, str, int]]) -> None:
     """
     Build a minimal DuckDB index with just the columns create_divref_fasta reads.
 
     Args:
         db_path: Path to the DuckDB file to create.
-        rows: ``(sequence_id, sequence, contig)`` rows to insert into ``sequences``.
+        rows: ``(sequence_id, sequence, contig, start)`` rows to insert into ``sequences``.
+            ``start`` is the genomic start the tool orders output by.
     """
     with duckdb.connect(str(db_path)) as conn:
         conn.execute(
-            "CREATE TABLE sequences (sequence_id VARCHAR, sequence VARCHAR, contig VARCHAR)"
+            "CREATE TABLE sequences "
+            "(sequence_id VARCHAR, sequence VARCHAR, contig VARCHAR, start BIGINT)"
         )
-        conn.executemany("INSERT INTO sequences VALUES (?, ?, ?)", rows)
+        conn.executemany("INSERT INTO sequences VALUES (?, ?, ?, ?)", rows)
 
 
 def _parse_fasta(path: Path) -> list[tuple[str, str]]:
@@ -49,9 +51,9 @@ def test_writes_only_the_requested_contig(tmp_path: Path) -> None:
     _build_index(
         db_path,
         rows=[
-            ("DR-1-0", "ACGT", "chr1"),
-            ("DR-1-1", "TTTT", "chr1"),
-            ("DR-1-2", "GGGG", "chr2"),
+            ("DR-1-0", "ACGT", "chr1", 100),
+            ("DR-1-1", "TTTT", "chr1", 200),
+            ("DR-1-2", "GGGG", "chr2", 50),
         ],
     )
     output_base = tmp_path / "out"
@@ -70,8 +72,8 @@ def test_writes_one_file_per_requested_contig(tmp_path: Path) -> None:
     _build_index(
         db_path,
         rows=[
-            ("DR-1-0", "ACGT", "chr1"),
-            ("DR-1-1", "GGGG", "chr2"),
+            ("DR-1-0", "ACGT", "chr1", 100),
+            ("DR-1-1", "GGGG", "chr2", 100),
         ],
     )
     output_base = tmp_path / "out"
@@ -88,7 +90,7 @@ def test_contig_with_no_rows_writes_empty_file_and_warns(
 ) -> None:
     """A requested contig absent from the index yields an empty FASTA plus a warning."""
     db_path = tmp_path / "index.duckdb"
-    _build_index(db_path, rows=[("DR-1-0", "ACGT", "chr1")])
+    _build_index(db_path, rows=[("DR-1-0", "ACGT", "chr1", 100)])
     output_base = tmp_path / "out"
 
     with caplog.at_level(logging.WARNING):
@@ -103,7 +105,7 @@ def test_contig_with_no_rows_writes_empty_file_and_warns(
 def test_empty_contigs_raises_value_error(tmp_path: Path) -> None:
     """An empty contig list is rejected."""
     db_path = tmp_path / "index.duckdb"
-    _build_index(db_path, rows=[("DR-1-0", "ACGT", "chr1")])
+    _build_index(db_path, rows=[("DR-1-0", "ACGT", "chr1", 100)])
 
     with pytest.raises(ValueError, match="[Cc]ontig"):
         create_divref_fasta(duckdb_path=db_path, output_base=tmp_path / "out", contigs=[])
@@ -112,7 +114,7 @@ def test_empty_contigs_raises_value_error(tmp_path: Path) -> None:
 def test_streams_all_rows_across_chunk_boundaries(tmp_path: Path) -> None:
     """All rows are written even when the result spans multiple read chunks."""
     db_path = tmp_path / "index.duckdb"
-    rows = [(f"DR-1-{i}", "A" * (i + 1), "chr1") for i in range(5)]
+    rows = [(f"DR-1-{i}", "A" * (i + 1), "chr1", i) for i in range(5)]
     _build_index(db_path, rows=rows)
     output_base = tmp_path / "out"
 
@@ -124,5 +126,31 @@ def test_streams_all_rows_across_chunk_boundaries(tmp_path: Path) -> None:
     )
 
     written = _parse_fasta(Path(f"{output_base}.chr1.fasta"))
-    assert set(written) == {(sid, seq) for sid, seq, _ in rows}
+    assert set(written) == {(sid, seq) for sid, seq, _, _ in rows}
     assert len(written) == 5
+
+
+def test_output_is_ordered_by_genomic_start(tmp_path: Path) -> None:
+    """Rows are written in genomic-start order regardless of insertion order."""
+    db_path = tmp_path / "index.duckdb"
+    # Inserted out of start order; expect ascending-start output (ties broken by sequence_id).
+    _build_index(
+        db_path,
+        rows=[
+            ("DR-1-2", "GGGG", "chr1", 300),
+            ("DR-1-0", "ACGT", "chr1", 100),
+            ("DR-1-1b", "CCCC", "chr1", 200),
+            ("DR-1-1a", "TTTT", "chr1", 200),
+        ],
+    )
+    output_base = tmp_path / "out"
+
+    create_divref_fasta(duckdb_path=db_path, output_base=output_base, contigs=["chr1"])
+
+    written = _parse_fasta(Path(f"{output_base}.chr1.fasta"))
+    assert written == [
+        ("DR-1-0", "ACGT"),
+        ("DR-1-1a", "TTTT"),
+        ("DR-1-1b", "CCCC"),
+        ("DR-1-2", "GGGG"),
+    ]
diff --git a/divref/uv.lock b/divref/uv.lock
index 564eeb9..5963ad5 100644
--- a/divref/uv.lock
+++ b/divref/uv.lock
@@ -585,7 +585,7 @@ ipython = [
 [package.metadata]
 requires-dist = [
     { name = "defopt", specifier = "~=6.4" },
-    { name = "duckdb", specifier = ">=1.0" },
+    { name = "duckdb", specifier = ">=1.4.0" },
     { name = "fgmetric", specifier = ">=0.2.0" },
     { name = "fgpyo", specifier = ">=1.5.1" },
     { name = "hail", specifier = ">=0.2" },
diff --git a/pixi.lock b/pixi.lock
index d5658fb..6bc185f 100644
--- a/pixi.lock
+++ b/pixi.lock
@@ -1,4 +1,21 @@
-version: 6
+version: 7
+platforms:
+- name: linux-64
+  virtual-packages:
+  - __unix=0=0
+  - __linux=4.18
+  - __glibc=2.28
+  - __archspec=0=x86_64
+- name: osx-64
+  virtual-packages:
+  - __unix=0=0
+  - __osx=13.0
+  - __archspec=0=x86_64
+- name: osx-arm64
+  virtual-packages:
+  - __unix=0=0
+  - __osx=13.0
+  - __archspec=0=m1
 environments:
   analysis:
     channels:
@@ -6,17 +23,19 @@ environments:
     - url: https://conda.anaconda.org/bioconda/
     indexes:
     - https://pypi.org/simple
-    options:
-      pypi-prerelease-mode: if-necessary-or-explicit
     packages:
       linux-64:
+      - conda: https://conda.anaconda.org/bioconda/linux-64/bcftools-1.23.1-hb2cee57_0.conda
+      - conda: https://conda.anaconda.org/bioconda/linux-64/htslib-1.23.1-h633afcb_0.conda
+      - conda: https://conda.anaconda.org/bioconda/linux-64/samtools-1.23.1-ha83d96e_0.conda
+      - conda: https://conda.anaconda.org/bioconda/noarch/snakefmt-1.1.0-pyhdfd78af_0.conda
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-- conda: https://conda.anaconda.org/conda-forge/osx-arm64/zstd-1.5.7-hbf9d68e_6.conda
-  sha256: 9485ba49e8f47d2b597dd399e88f4802e100851b27c21d7525625b0b4025a5d9
-  md5: ab136e4c34e97f34fb621d2592a393d8
-  depends:
-  - __osx >=11.0
-  - libzlib >=1.3.1,<2.0a0
-  license: BSD-3-Clause
-  license_family: BSD
-  purls: []
-  size: 433413
-  timestamp: 1764777166076
diff --git a/pixi.toml b/pixi.toml
index bf7dc0c..1108005 100644
--- a/pixi.toml
+++ b/pixi.toml
@@ -33,7 +33,7 @@ analysis = { features = ["workflow", "analysis"] }
 check-toolkit = "uv run --directory divref poe check-all"
 fix-and-check-toolkit = "uv run --directory divref poe fix-and-check-all"
 
-check-lock   = "pixi lock --check"
+check-lock = "pixi lock --check"
 
 check-all = [
     { task = "check-toolkit" },
diff --git a/workflows/compare_divref_gnomad.smk b/workflows/compare_divref_gnomad.smk
index 38959af..a4dd570 100644
--- a/workflows/compare_divref_gnomad.smk
+++ b/workflows/compare_divref_gnomad.smk
@@ -14,7 +14,7 @@ COMPARISON_NAME: str = "compare_divref_gnomad"
 CONTIG: str = "chr22"
 FREQUENCY_THRESHOLD: float = 0.005
 DIVREF_DUCKDB_URL: str = (
-    "https://zenodo.org/records/14802613/files/" "DivRef-v1.1.haplotypes_gnomad_merge.index.duckdb"
+    "https://zenodo.org/records/14802613/files/DivRef-v1.1.haplotypes_gnomad_merge.index.duckdb"
 )
 # Zenodo-published md5 for the DuckDB above (record 14802613). Verified after download so a
 # truncated or corrupted fetch fails the rule instead of silently feeding a bad index downstream.
@@ -72,7 +72,9 @@ rule download_divref_index:
     shell:
         """
         (
-            wget --no-verbose -O {output.duckdb} {params.url}
+            # curl (not wget): ships on macOS by default; --fail exits non-zero on an HTTP
+            # error so the checksum step isn't handed an error page.
+            curl --fail --location --silent --show-error --output {output.duckdb} {params.url}
             # Verify against the Zenodo-published md5 (md5sum on Linux, md5 on macOS).
             if command -v md5sum >/dev/null 2>&1; then
                 actual=$(md5sum "{output.duckdb}" | awk '{{print $1}}')
diff --git a/workflows/config/config_schema.yml b/workflows/config/config_schema.yml
index ecffc02..aa15c29 100644
--- a/workflows/config/config_schema.yml
+++ b/workflows/config/config_schema.yml
@@ -32,6 +32,9 @@ properties:
     type: array
     items:
       type: string
+      # chr1-chr22, chrX, chrY; rejects typos (chrM, chr23, ...) at config-validation time
+      # rather than deep in a "no rule to produce ..." error.
+      pattern: "^chr([1-9]|1[0-9]|2[0-2]|X|Y)$"
     minItems: 1
     uniqueItems: true
     description: |
diff --git a/workflows/create_test_data.smk b/workflows/create_test_data.smk
index 11faaec..eaa265a 100644
--- a/workflows/create_test_data.smk
+++ b/workflows/create_test_data.smk
@@ -27,7 +27,8 @@ MIN_POP_AF_COMPUTE_HAPLOTYPES: float = 0.005
 WINDOW_SIZE_COMPUTE_HAPLOTYPES: int = 25
 # Hail-using divref tools require a GCS credentials path when reading from local-only Hail
 # tables, because hail_init currently sets `use_s3=False` by default and asserts the path is
-# present. Threaded through every rule below for consistency.
+# present. Passed explicitly to the rules below (the first subset rule relies on the tool's
+# matching default of this same path).
 GCS_CREDENTIALS_PATH: str = "~/.config/gcloud/application_default_credentials.json"
 
 ####################################################################################################
diff --git a/workflows/generate_divref.smk b/workflows/generate_divref.smk
index f57abc1..2e9f832 100644
--- a/workflows/generate_divref.smk
+++ b/workflows/generate_divref.smk
@@ -411,6 +411,8 @@ rule index_reference_genome:
     log:
         "logs/generate_divref/index_reference_genome.log",
     shell:
+        # Force the `.fai` name (not samtools' default `<fasta>.fasta.fai`) to match the
+        # `reference_fasta.with_suffix(".fai")` lookup in append_contig_to_duckdb_index.
         """
         (
             samtools faidx \