dcc_apply_codebook      Apply a declarative codebook to a dataset
dcc_audit_log           Accessors for dcc_result objects
dcc_capabilities        Machine-readable DCC capability document
dcc_check               Check a strict DCC project without changing
                        data
dcc_codebook_changes    The planned changes of a codebook preview
dcc_config              A cleaning configuration
dcc_data                The dcc_data container
dcc_detect              Run a rule set against data (Detect stage)
dcc_detect_chunked      Run record-local checks over a file in chunks
dcc_detect_encoding     Detect the character encoding of a text file
dcc_dictionary          Canonical variable dictionary
dcc_dispositions        Terminal dispositions of a cleaning result
dcc_doctor              Run every validator over a dataset and rule set
dcc_execute             Execute actions on detected findings (Execute
                        stage)
dcc_export_log          Export an audit log for external auditors
dcc_findings            The dcc_findings table
dcc_help                Explain a DCC workflow code in Chinese or
                        English
dcc_import              Strict canonical import
dcc_item_map            Master item map of a form-mapped dataset
dcc_l0_diagnose         Level-0 structural diagnostics
dcc_manifest            Build a reproducibility manifest for a cleaning
                        run
dcc_map_forms           Map multi-form responses onto the master item
                        bank
dcc_mapping_findings    Mapping problems found while aligning forms
dcc_missing_states      Canonical cell-level missing states
dcc_provenance          Provenance chain of a dcc_data object
dcc_read                Read a data file into a dcc_data object
dcc_read_config         Read an Excel cleaning-plan configuration
dcc_read_plan           Read a strict DCC Excel or JSON plan
dcc_read_report         Read report of a dcc_data object
dcc_reconcile           Reconcile findings against logged changes
                        (closed loop)
dcc_report              Generate a cleaning report (Report stage)
dcc_report_machine      Render the machine report bundle
dcc_report_model        Build and validate the normalized report model
dcc_report_staff        Render the bilingual staff report
dcc_report_statistical
                        Render the statistical report bundle
dcc_rerun               Re-run a cleaning pipeline from its manifest
                        and verify the output
dcc_result_summary      Create a structured AI summary of a DCC result
dcc_rules               Load a declarative rule set from a YAML file
dcc_run                 Run a cleaning workflow with one command
dcc_run_files           Output files written by a run
dcc_schema              Published JSON Schema for a DCC object
dcc_score               Score responses against an answer key
dcc_template            Create the strict bilingual DCC Excel template
dcc_trace               Trace the cleaning history of a record or cell
dcc_unhandled           Findings left unhandled by execution
dcc_validate_config     Validate a cleaning configuration
dcc_validate_data       Validate data against a rule set before
                        detection
dcc_validate_json       Validate DCC JSON and JSON Lines artifacts
dcc_validate_plan       Validate a strict DCC project plan
dcc_validate_rules      Validate a rule set before it is used
dcc_validation_errors   The failing issues of a validation report
dcc_write_config_template
                        Write a starter Excel cleaning-plan template
detect_missing_items    Detect excessive item nonresponse per
                        respondent
detect_response_time    Detect implausibly fast or anomalous response
                        times
detect_score_anomaly    Detect group-wise score anomalies
detect_straightlining   Detect straight-lining (longstring)
detect_trap_items       Detect failed trap (attention-check) items
