dbt-transformation-patterns

dbt Transformation Patterns

Production-ready patterns for dbt (data build tool) including model organization, testing strategies, documentation, and incremental processing.

Use this skill when

• Building data transformation pipelines with dbt
• Organizing models into staging, intermediate, and marts layers
• Implementing data quality tests and documentation
• Creating incremental models for large datasets
• Setting up dbt project structure and conventions

Do not use this skill when

• The project is not using dbt or a warehouse-backed workflow
• You only need ad-hoc SQL queries
• There is no access to source data or schemas

Instructions

• Define model layers, naming, and ownership.
• Implement tests, documentation, and freshness checks.
• Choose materializations and incremental strategies.
• Optimize runs with selectors and CI workflows.
• If detailed patterns are required, open resources/​implementation-playbook.md.

Resources

• resources/​implementation-playbook.md for detailed dbt patterns and examples.

---

<!-- AGI-INTEGRATION-START -->

AGI Framework Integration

Adapted for @techwavedev/​agi-agent-kit Original source: antigravity-awesome-skills

Memory-First Protocol

Retrieve prior API design decisions, database schema choices, and error handling patterns. Cache API response templates for consistent error formatting.

# Check for prior backend/​API context before starting
python3 execution/​memory_manager.py auto --query "API design patterns and architecture decisions for Dbt Transformation Patterns"

Storing Results

After completing work, store backend/​API decisions for future sessions:

python3 execution/​memory_manager.py store \
  --content "API architecture: REST with HATEOAS, JWT auth, rate limiting at 100 req/​min per tenant" \
  --type decision --project <project> \
  --tags dbt-transformation-patterns backend

Multi-Agent Collaboration

Share API contract changes with frontend agents so they update their client code, and with QA agents for test coverage.

python3 execution/​cross_agent_context.py store \
  --agent "<your-agent>" \
  --action "Implemented API endpoints — 5 new routes with OpenAPI spec and integration tests" \
  --project <project>

Agent Team: Code Review

After implementation, dispatch code_review_team for two-stage review (spec compliance + code quality) before merging.

<!-- AGI-INTEGRATION-END -->