Loading...
Loading...
Found 15 Skills
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
Idempotent Redundancy
Database schema design, optimization, and migration patterns for PostgreSQL, MySQL, and NoSQL databases. Use for designing schemas, writing migrations, or optimizing queries.
Error handling patterns for ERPNext/Frappe database operations. Use when handling DoesNotExistError, DuplicateEntryError, transaction failures, and query errors. Covers retry patterns and data integrity. V14/V15/V16 compatible. Triggers: database error, DoesNotExistError, DuplicateEntryError, transaction failed, query error.
Standards and best practices for writing LookML tests to ensure data integrity, accuracy, and logic validation.
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.
Guidance for data resharding tasks that involve reorganizing files across directory structures with constraints on file sizes and directory contents. This skill applies when redistributing datasets, splitting large files, or reorganizing data into shards while maintaining constraints like maximum files per directory or maximum file sizes. Use when tasks involve resharding, data partitioning, or directory-constrained file reorganization.
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.
Test database interactions, schemas, and 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'.
Verify accounting integrity. Compare totals to source docs, check lots vs holdings, detect duplicates, report gaps.