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Model in dbt across staging -> intermediate -> marts layers, choose materialization (view/table/incremental) by the trade, write correct incremental models (reliable unique key, is_incremental filter, late-data strategy), and keep it DRY with refs/sources/macros.
How this skill is triggered — by the user, by Claude, or both
Slash command
/analytics-engineering:dbt-modelingThe summary Claude sees in its skill listing — used to decide when to auto-load this skill
**staging** (1 model/source: rename, cast, light clean) -> **intermediate** (compose, business logic) -> **marts** (business-facing fct/dim). Don't collapse into one giant model.
staging (1 model/source: rename, cast, light clean) -> intermediate (compose, business logic) -> marts (business-facing fct/dim). Don't collapse into one giant model.
| Use | Choice |
|---|---|
| cheap / rarely read | view |
| fast read, rebuild ok | table |
| large append-mostly fact | incremental |
Reliable unique key + is_incremental() window filter + late-arriving-data strategy. A broken incremental silently drops/dups rows.
ref()/source() for lineage; macros for repeated logic. Never copy-paste SQL.
npx claudepluginhub mcorbett51090/ravenclaude --plugin analytics-engineeringGuides completion of development work by verifying tests, detecting environment, and presenting structured options for merge, PR, or cleanup.
Enforces test-driven development: write failing test first, then minimal code to pass. Use when implementing features or bugfixes.
Guides creation and editing of skills using test-driven development with pressure scenarios and subagents to verify agent compliance.