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Found 22 Skills
Detects data integrity issues including orphaned records, broken foreign key relationships, constraint violations, and provides automated fix migrations. Use for "data integrity", "orphaned records", "broken relationships", or "data quality".
Guide for using molt verify to compare source and target databases for schema and row-level consistency after a migration. Use when running verify commands, tuning concurrency/sharding, handling schema mismatches, or validating data integrity post-migration.
Audit a spreadsheet for formula accuracy, errors, and common mistakes. Scopes to a selected range, a single sheet, or the entire model (including financial-model integrity checks like BS balance, cash tie-out, and logic sanity). Triggers on "audit this sheet", "check my formulas", "find formula errors", "QA this spreadsheet", "sanity check this", "debug model", "model check", "model won't balance", "something's off in my model", "model review".
Audits SQL migration files for destructive actions, potential table locks, and compatibility issues. Use before applying migrations to production databases to prevent downtime and ensure data integrity.
Verify accounting integrity. Compare totals to source docs, check lots vs holdings, detect duplicates, report gaps.
Process use when you need to archive historical database records to reduce primary database size. This skill automates moving old data to archive tables or cold storage (S3, Azure Blob, GCS). Trigger with phrases like "archive old database records", "implement data retention policy", "move historical data to cold storage", or "reduce database size with archival".
Use when backing up, restoring, or validating golden datasets. Prevents data loss and ensures test data integrity for AI/ML evaluation systems.
Validate database integrity, test migrations forward and backward, verify schema constraints, manage seed data, detect migration drift, and identify query performance issues. Covers PostgreSQL, MySQL, MongoDB with Prisma, TypeORM, Drizzle, and SQLAlchemy, plus Testcontainers test databases. Use when: "database test," "migration test," "migration rollback," "rollback test," "data integrity," "SQL test," "schema validation," "seed data," "query performance," "Testcontainers." Not for: synthetic data generation/masking at scale — use test-data-management; Docker/IaC test-environment provisioning — use test-environments; SQL injection — use security-testing. Related: test-data-management, test-environments, security-testing, ci-cd-integration.
Guidance on how to upgrade your Qdrant version without interrupting the availability of your application and ensuring data integrity.
Apply Benford's Law to detect anomalies in numerical datasets by analyzing first-digit frequency distributions. Use this skill when the user needs to audit financial data for fraud indicators, validate data integrity, or detect fabricated numbers — even if they say 'data manipulation detection', 'first digit test', or 'accounting fraud screening'.
Use when SwiftData migrations crash, fail to preserve relationships, lose data, or work in simulator but fail on device - systematic diagnostics for schema version mismatches, relationship errors, and migration testing gaps
Adds schema tests and data quality validation to dbt models. Use when working with dbt tests for: (1) Adding or modifying tests in schema.yml files (2) Task mentions "test", "validate", "data quality", "unique", "not_null", or "accepted_values" (3) Ensuring data integrity - primary keys, foreign keys, relationships (4) Debugging test failures or understanding why dbt test failed Matches existing project test patterns and YAML style before adding new tests.