Can I validate files that don't follow the naming convention?

Yes, while the tool automatically infers table names from filenames, you can manually specify a table name using the --table option for custom files.

What specific checks does the validator perform?

It validates column order against templates, checks CSV format integrity, ensures mandatory fields are populated, and verifies that values match the database schema types and enum definitions.

What happens if a template file is missing?

The script will issue a warning and skip the template-specific check, but it can still proceed with format and schema-based validations if those files are available.

Does this skill modify my CSV files automatically?

No, the validation is strictly non-destructive. It identifies and reports errors, but requires the user to perform manual corrections to ensure data accuracy.

Master Data CSV Validator

Name: Master Data CSV Validator
Author: Wonderplanet

byWonderplanet

Database Management

Validates master data CSV files against database schemas and templates to ensure data integrity and deployment readiness.

About

The Master Data CSV Validator is a specialized tool designed to automate the verification of CSV files before they are imported into a database. It ensures that files adhere to specific templates (column order and naming), follow correct CSV formatting rules, respect database constraints like non-null requirements, and align with defined schemas including data types and enum values. This skill is particularly useful for developers working on the GLOW project or similar data-heavy environments where maintaining synchronization between CSV assets and database implementations is critical for preventing runtime errors and deployment failures.

Key Features

Automated template matching for column order and naming consistency
Deep CSV format validation for line breaks, escapes, and quoting
0 GitHub stars
Schema consistency checks for data types and enum value sets
Smart table name inference based on PascalCase filename conventions
Detailed JSON report generation with specific row/column error mapping

Use Cases

Verifying consistency between server/client implementations and data assets
Pre-deployment validation of game master data to prevent database import errors
Bulk validation of large CSV datasets during migration or updates

About

Key Features

Automated template matching for column order and naming consistency
Deep CSV format validation for line breaks, escapes, and quoting
0 GitHub stars
Schema consistency checks for data types and enum value sets
Smart table name inference based on PascalCase filename conventions
Detailed JSON report generation with specific row/column error mapping

Use Cases

Verifying consistency between server/client implementations and data assets
Pre-deployment validation of game master data to prevent database import errors
Bulk validation of large CSV datasets during migration or updates