Database

Actions

1. Gather requirements
2. Design schema
3. Define relationships
4. Plan indexing strategy
5. Design for scalability

Copy-Paste Prompts

Use @database-architect to design database schema

Use @postgresql to design PostgreSQL schema

Phase 2: Database Implementation

Skills to Invoke

• prisma-expert - Prisma ORM
• database-migrations-sql-migrations - SQL migrations
• neon-postgres - Serverless Postgres

Actions

1. Set up database connection
2. Configure ORM
3. Create migrations
4. Implement models
5. Set up seed data

Copy-Paste Prompts

Use @prisma-expert to set up Prisma ORM

Use @database-migrations-sql-migrations to create migrations

Phase 3: Query Optimization

Skills to Invoke

• database-optimizer - Database optimization
• sql-optimization-patterns - SQL optimization
• postgres-best-practices - PostgreSQL optimization

Actions

1. Analyze slow queries
2. Review execution plans
3. Optimize indexes
4. Refactor queries
5. Implement caching

Copy-Paste Prompts

Use @database-optimizer to optimize database performance

Use @sql-optimization-patterns to optimize SQL queries

Phase 4: Data Migration

Skills to Invoke

• database-migration - Database migration
• framework-migration-code-migrate - Code migration

Actions

1. Plan migration strategy
2. Create migration scripts
3. Test migration
4. Execute migration
5. Verify data integrity

Copy-Paste Prompts

Use @database-migration to plan database migration

Phase 5: Data Pipeline Development

Skills to Invoke

• data-engineer - Data engineering
• data-engineering-data-pipeline - Data pipelines
• airflow-dag-patterns - Airflow workflows
• dbt-transformation-patterns - dbt transformations

Actions

1. Design data pipeline
2. Set up data ingestion
3. Implement transformations
4. Configure scheduling
5. Set up monitoring

Copy-Paste Prompts

Use @data-engineer to design data pipeline

Use @airflow-dag-patterns to create Airflow DAGs

Phase 6: Data Quality

Skills to Invoke

• data-quality-frameworks - Data quality
• data-engineering-data-driven-feature - Data-driven features

Actions

1. Define quality metrics
2. Implement validation
3. Set up monitoring
4. Create alerts
5. Document standards

Copy-Paste Prompts

Use @data-quality-frameworks to implement data quality checks

Phase 7: Database Operations

Skills to Invoke

• database-admin - Database administration
• backup-automation - Backup automation

Actions

1. Set up backups
2. Configure replication
3. Monitor performance
4. Plan capacity
5. Implement security

Copy-Paste Prompts

Use @database-admin to manage database operations

Database Technology Workflows

PostgreSQL

Skills: postgresql, postgres-best-practices, neon-postgres, prisma-expert

MongoDB

Skills: nosql-expert, azure-cosmos-db-py

Redis

Skills: bullmq-specialist, upstash-qstash

Data Warehousing

Skills: clickhouse-io, dbt-transformation-patterns

Quality Gates

• Schema designed and reviewed
• Migrations tested
• Performance benchmarks met
• Backups configured
• Monitoring in place
• Documentation complete

Related Workflow Bundles

• development - Application development
• cloud-devops - Infrastructure
• ai-ml - AI/ML data pipelines
• testing-qa - Data testing

Limitations

• Use this skill only when the task clearly matches the scope described above.
• Do not treat the output as a substitute for environment-specific validation, testing, or expert review.
• Stop and ask for clarification if required inputs, permissions, safety boundaries, or success criteria are missing.