check_allowed_values    QC-09: Check for values outside the allowed set
check_col_count         QC-05: Report column count
check_distinct_counts   QC-08: Report distinct value counts for
                        character columns
check_duplicate_rows    QC-03: Check for fully-duplicate rows
check_empty_column      QC-02: Check for entirely empty columns
check_inferred_types    QC-06: Report inferred column types
check_key_uniqueness    QC-12: Check uniqueness of key column(s)
check_min_row_count     QC-14: Check row count bounds and optional file
                        size
check_missing_rate      QC-01: Check missing rate per column
check_non_numeric       QC-11: Check non-numeric rate in numeric
                        columns
check_numeric_bounds    QC-10: Check for out-of-range numeric values
check_numeric_stats     QC-07: Report numeric summary statistics
check_outliers          QC-15: Detect statistical outliers in numeric
                        columns
check_pattern           QC-13: Check values against a regex pattern
check_row_count         QC-04: Report row count
check_schema_contract   SC-01 / SC-02: Check columns against the
                        expected schema contract
compare_snapshots       Compare two snapshots from the SQLite database
detect_files            Detect current and previous dataset files
dq_result               Construct a data quality result object
infer_col_type          Infer the logical type of a character column
list_snapshots          List snapshots available in the database
load_config             Load and merge dataset configuration
overall_status          Compute the worst status across a list of
                        dq_result objects
read_dataset            Read a dataset file into a data frame
read_recent_snapshots   Read recent snapshot history from the SQLite
                        database
resolve_col_type        Resolve the effective type of a column,
                        respecting config overrides
run_comparison_checks   Run all version comparison checks between two
                        dataset snapshots
run_custom_checks       Run organisation-specific custom checks
run_dq_check            Run a full data quality check pipeline
run_qc_checks           Run all generic quality checks on a dataset
