This skill manages database testing by generating test data, wrapping tests in transactions, and validating database schemas. It is used to create robust and reliable database interactions. Claude uses this skill when the user requests database testing utilities, including test data generation, transaction management, schema validation, or migration testing. Trigger this skill by mentioning "database testing," "test data factories," "transaction rollback," "schema validation," or using the `/db-test` or `/dbt` commands.
84
53%
Does it follow best practices?
Impact
90%
1.04xAverage score across 9 eval scenarios
Passed
No known issues
Optimize this skill with Tessl
npx tessl skill review --optimize ./backups/skills-migration-20251108-070147/plugins/testing/database-test-manager/skills/database-test-manager/SKILL.mdTest data generation with Faker and factories
Faker import
100%
100%
Faker instance used
100%
100%
Python implementation
100%
100%
DB library used
100%
100%
INSERT executed
100%
100%
Factory function or class
0%
100%
Realistic name values
100%
100%
Realistic email values
100%
100%
Multiple entities seeded
100%
100%
Usage instructions
100%
100%
Transaction wrapping with automatic rollback
Transaction wrapping
0%
100%
Automatic rollback
0%
100%
No DELETE/TRUNCATE cleanup
100%
100%
Isolation level set
0%
0%
Context manager or fixture
100%
100%
Python test framework
100%
100%
Per-test transaction scope
50%
100%
Rollback on exception
60%
100%
DB library used
100%
100%
Python implementation
100%
100%
Database schema validation
Structured expected schema
100%
100%
Actual schema queried
100%
100%
Column comparison
100%
100%
Data type comparison
100%
100%
Table existence check
100%
100%
Constraint validation
100%
100%
Mismatch reporting
100%
100%
Failure signaling
100%
100%
Python implementation
100%
100%
Migration issue framing
100%
60%
Database migration test execution and post-migration integrity verification
Migration script applied
100%
100%
Initial schema setup
100%
100%
New table existence check
100%
100%
New column existence check
100%
100%
Dropped column absence check
100%
100%
Structured expected schema
0%
0%
Data type validation
100%
100%
Failure signaling
100%
100%
Migration framing
100%
100%
Python implementation
100%
100%
DB library used
100%
100%
Execution instructions
100%
100%
Schema-driven test data generation with Faker
Schema file consumed
100%
100%
Faker import
100%
100%
Realistic name values
100%
100%
Realistic email values
100%
100%
Factory function or class
53%
46%
DB library for INSERT
100%
100%
Python implementation
100%
100%
Multiple tables seeded
100%
100%
Configurable row count
100%
100%
Execution instructions
100%
100%
Integrated database test suite combining data generation, transactions, and schema validation
Transaction wrapping present
100%
100%
Automatic rollback
100%
100%
No DELETE/TRUNCATE cleanup
100%
100%
Isolation level set
100%
50%
Faker import and usage
100%
100%
Factory functions or classes
100%
100%
Realistic name and email data
75%
100%
Schema validation present
100%
100%
Schema validation failure signaling
100%
100%
All three components integrated
100%
100%
DB library used
100%
100%
Python implementation
100%
100%
Execution instructions
100%
100%
Relational test data factories with FK dependencies
Faker imported
100%
100%
Faker for names
100%
100%
Faker for emails
100%
100%
Factory per entity
100%
100%
FK insertion order
100%
100%
FK values passed explicitly
100%
100%
Python + DB library
100%
100%
Seed volume
100%
100%
Realistic financial values
100%
100%
Run instructions
100%
100%
Transaction isolation for parallel test execution
Transaction wrapping
0%
0%
Automatic rollback in teardown
0%
0%
No DELETE/TRUNCATE cleanup
100%
100%
Isolation level referenced
0%
0%
Per-test scope
100%
100%
Rollback on exception
25%
50%
Python test framework
100%
100%
DB library used
100%
100%
Isolation strategy documented
100%
100%
Run instructions
100%
100%
Schema constraint validation and data integrity checking
Structured baseline definition
100%
100%
Actual schema queried
100%
100%
Column type comparison
100%
100%
NOT NULL constraint check
100%
100%
UNIQUE constraint check
100%
100%
Foreign key check
100%
100%
Mismatch reporting
100%
100%
Non-zero exit on failure
100%
100%
Zero exit on clean
100%
100%
Python implementation
100%
100%
Run instructions
100%
100%
c8a915c
Table of Contents
If you maintain this skill, you can claim it as your own. Once claimed, you can manage eval scenarios, bundle related skills, attach documentation or rules, and ensure cross-agent compatibility.