Database Workflow Bundle
Overview
Comprehensive database workflow for database design, development, optimization, migrations, and data engineering. Covers SQL, NoSQL, and modern data platforms.
When to Use This Workflow
Use this workflow when:
- Designing database schemas
- Implementing database migrations
- Optimizing query performance
- Setting up data pipelines
- Managing database operations
- Implementing data quality
Workflow Phases
Phase 1: Database Design
Skills to Invoke
database-architect- Database architecturedatabase-design- Schema designpostgresql- PostgreSQL designnosql-expert- NoSQL design
Actions
- Gather requirements
- Design schema
- Define relationships
- Plan indexing strategy
- Design for scalability
Copy-Paste Prompts
Use @database-architect to design database schemaUse @postgresql to design PostgreSQL schemaPhase 2: Database Implementation
Skills to Invoke
prisma-expert- Prisma ORMdatabase-migrations-sql-migrations- SQL migrationsneon-postgres- Serverless Postgres
Actions
- Set up database connection
- Configure ORM
- Create migrations
- Implement models
- Set up seed data
Copy-Paste Prompts
Use @prisma-expert to set up Prisma ORMUse @database-migrations-sql-migrations to create migrationsPhase 3: Query Optimization
Skills to Invoke
database-optimizer- Database optimizationsql-optimization-patterns- SQL optimizationpostgres-best-practices- PostgreSQL optimization
Actions
- Analyze slow queries
- Review execution plans
- Optimize indexes
- Refactor queries
- Implement caching
Copy-Paste Prompts
Use @database-optimizer to optimize database performanceUse @sql-optimization-patterns to optimize SQL queriesPhase 4: Data Migration
Skills to Invoke
database-migration- Database migrationframework-migration-code-migrate- Code migration
Actions
- Plan migration strategy
- Create migration scripts
- Test migration
- Execute migration
- Verify data integrity
Copy-Paste Prompts
Use @database-migration to plan database migrationPhase 5: Data Pipeline Development
Skills to Invoke
data-engineer- Data engineeringdata-engineering-data-pipeline- Data pipelinesairflow-dag-patterns- Airflow workflowsdbt-transformation-patterns- dbt transformations
Actions
- Design data pipeline
- Set up data ingestion
- Implement transformations
- Configure scheduling
- Set up monitoring
Copy-Paste Prompts
Use @data-engineer to design data pipelineUse @airflow-dag-patterns to create Airflow DAGsPhase 6: Data Quality
Skills to Invoke
data-quality-frameworks- Data qualitydata-engineering-data-driven-feature- Data-driven features
Actions
- Define quality metrics
- Implement validation
- Set up monitoring
- Create alerts
- Document standards
Copy-Paste Prompts
Use @data-quality-frameworks to implement data quality checksPhase 7: Database Operations
Skills to Invoke
database-admin- Database administrationbackup-automation- Backup automation
Actions
- Set up backups
- Configure replication
- Monitor performance
- Plan capacity
- Implement security
Copy-Paste Prompts
Use @database-admin to manage database operationsDatabase Technology Workflows
PostgreSQL
Skills: postgresql, postgres-best-practices, neon-postgres, prisma-expertMongoDB
Skills: nosql-expert, azure-cosmos-db-pyRedis
Skills: bullmq-specialist, upstash-qstashData Warehousing
Skills: clickhouse-io, dbt-transformation-patternsQuality Gates
- Schema designed and reviewed
- Migrations tested
- Performance benchmarks met
- Backups configured
- Monitoring in place
- Documentation complete
Related Workflow Bundles
development- Application developmentcloud-devops- Infrastructureai-ml- AI/ML data pipelinestesting-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.