dbt-skills

Plugin dbt-skills from marketplace data-engineering-skills in AltimateAI/data-engineering-skills. Commands read from the repo's manifest — 16 days ago.

Skills (17)

• altimate-code

  Delegates dbt and warehouse work to altimate-code, a specialized CLI agent with 100+ purpose-built data tools. USE THIS SKILL FIRST whenever the task mentions or implies: warehouse access (Snowflake, BigQuery, Redshift, Databricks, Postgres, MySQL, DuckDB), column-level lineage, downstream-impact an

• optimizing-databricks-sql

  Analyze DBSQL queries, including SQL embedded in notebooks (`spark.sql(...)`, `%sql` cells), for anti-patterns, lint issues, and performance problems, using Databricks-specific dialect and platform knowledge (Delta, Photon, Unity Catalog) layered on top of altimate-code's generic SQL engine. Use whe

• creating-dbt-models

  Creates dbt models following project conventions. Use when working with dbt models for: (1) Creating new models (any layer - discovers project's naming conventions first) (2) Task mentions "create", "build", "add", "write", "new", or "implement" with model, table, or SQL (3) Modifying existing model

• dbt-model-enhancement

  Scoped enhancement of ONE existing dbt model from a ticket, with a validated PR as the deliverable. Use when: (1) User says "update <model> per JIRA-123", "add column X to this model", "enhance <model> based on this ticket" (2) Task is a scoped change to a specific existing model — one model, one ti

• debugging-dbt-errors

  Debugs and fixes dbt errors systematically. Use when working with dbt errors for: (1) Task mentions "fix", "error", "broken", "failing", "debug", "wrong", or "not working" (2) Compilation Error, Database Error, or test failures occur (3) Model produces incorrect output or unexpected results (4) Need

• developing-incremental-models

  Develops and troubleshoots dbt incremental models. Use when working with incremental materialization for: (1) Creating new incremental models (choosing strategy, unique_key, partition) (2) Task mentions "incremental", "append", "merge", "upsert", or "late arriving data" (3) Troubleshooting increment

• documenting-dbt-models

  Documents dbt models and columns in schema.yml. Use when working with dbt documentation for: (1) Adding model descriptions or column definitions to schema.yml (2) Task mentions "document", "describe", "description", "dbt docs", or "schema.yml" (3) Explaining business context, grain, meaning of data,

• migrating-sql-to-dbt

  Converts legacy SQL to modular dbt models. Use when migrating SQL to dbt for: (1) Converting stored procedures, views, or raw SQL files to dbt models (2) Task mentions "migrate", "convert", "legacy SQL", "transform to dbt", or "modernize" (3) Breaking monolithic queries into modular layers (discover

• mssql-to-snowflake-dbt-migration

  Convert MS SQL Server source code (stored procs, views, T-SQL scripts) into dbt models targeting Snowflake, with build-first-then-parity, isolated-schema deployment, and a migration dashboard. Use when: (1) User says "migrate this T-SQL to dbt on Snowflake", "convert these stored procs end-to-end",

• refactoring-dbt-models

  Safely refactors dbt models with downstream impact analysis. Use when restructuring dbt models for: (1) Task mentions "refactor", "restructure", "extract", "split", "break into", or "reorganize" (2) Extracting CTEs to intermediate models or creating macros (3) Modifying model logic that has downstre

• testing-dbt-models

  Adds schema tests and data quality validation to dbt models. Use when working with dbt tests for: (1) Adding or modifying tests in schema.yml files (2) Task mentions "test", "validate", "data quality", "unique", "not_null", or "accepted_values" (3) Ensuring data integrity - primary keys, foreign key

• end-to-end-snowflake-pipeline

  Build an end-to-end Snowflake pipeline — ticket → dbt models + orchestration DAG → PR → self-review → ticket comment. Use when: (1) User says "build a pipeline for X **end-to-end**", "create an end-to-end flow", "set up the <X> pipeline per JIRA-123" (2) Scope spans dbt models AND orchestration AND

• finding-expensive-queries

  Finds and ranks expensive Snowflake queries by cost, time, or data scanned. Use when: (1) User asks to find slow, expensive, or problematic queries (2) Task mentions "query history", "top queries", "most expensive", or "slowest queries" (3) Analyzing warehouse costs or identifying optimization candi

• optimizing-query-by-id

  Optimizes Snowflake query performance using query ID from history. Use when optimizing Snowflake queries for: (1) User provides a Snowflake query_id (UUID format) to analyze or optimize (2) Task mentions "slow query", "optimize", "query history", or "query profile" with a query ID (3) Analyzing quer

• optimizing-query-text

  Optimizes Snowflake SQL query performance from provided query text. Use when optimizing Snowflake SQL for: (1) User provides or pastes a SQL query and asks to optimize, tune, or improve it (2) Task mentions "slow query", "make faster", "improve performance", "optimize SQL", or "query tuning" (3) Rev

• snowflake-dbt-model-refactoring

  Refactor a bloated dbt model on Snowflake safely and produce a quantified before/after report that explains **which qualities improved and why** — not just raw deltas. Extends the standard refactor flow with (1) downstream impact analysis via `dbt-analyze`, (2) row-count + column-hash parity validat

• snowflake-query-optimization

  End-to-end Snowflake query optimization — fetch, rewrite, prove parity, benchmark, report. Use when: (1) User wants an **end-to-end flow** (fetch + rewrite + parity + benchmark + report), not just a rewrite (2) Input is a `.sql` file path in the repo (optionally `:L10-L80` line range), OR a Snowflak