data-validator

CSV data validation checks all 26 mandatory fields for correct types (dates as YYYY-MM-DD, booleans as True/False, numbers with dot decimals), enum ranges, UTF-8 encoding, and business rules like policy year 2024–2025 and non-negative amounts. The skill generates a detailed report identifying passes, failures, warnings, and specific fixes needed before import.

Data quality validation enforces strict type checking, mandatory field presence, allowed value ranges (e.g., week_number 28–105), business rule compliance, and detects encoding or delimiter errors. It outputs statistics and fix recommendations for each failed row.

Yes. Data validation scans CSV files during import workflows to identify missing fields, incorrect date formats, out-of-range values, and business rule violations before data enters your system, preventing downstream analysis errors.

Data validation expects CSV files with comma delimiters, UTF-8 encoding, and 26 specific insurance policy fields including dates, booleans, amounts, and policy metadata. Rows missing mandatory fields or containing mismatched types trigger validation failures.

Yes. Data validation applies during CSV import, data migration, and quality-check workflows. It ensures migrated insurance data meets schema requirements and business rules, surfacing errors that would compromise data integrity in the target system.

The skill outputs a Markdown report listing each failed or warned row with the specific field error, type mismatch, or business rule violation. This guidance lets you correct source data precisely before re-import.