Provides a curated index of dbt models to guide BigQuery query writing.
npx skills add https://github.com/warpdotdev/oz-skills --skill dbt-model-index
Please help me install this Agent Skill. Skill: dbt-model-index Source: https://github.com/warpdotdev/oz-skills/tree/main/.agents/skills/dbt-model-index Command: npx skills add https://github.com/warpdotdev/oz-skills --skill dbt-model-index
When writing SQL against a dbt-powered data warehouse, it is hard to know which BigQuery tables exist, what each one contains, and which model fits a vague data question. This Skill gives the agent a lookup index of dbt models so queries target the right tables with the right grain, filters, and join keys.
Ask the agent to find which dbt models answer your data question and write a BigQuery query using the indexed tables.
High-intent search queries and answers about installing and using this skill.
Consult the model index organized by domain sections such as Users, Activity, Revenue, and Events. Each entry describes the table's grain and lists "Useful for" bullets covering common query patterns, so you can match your question to the appropriate model.
First identify the correct model from the index, then write SQL using the fully-qualified production path like your-gcp-project.prod.model_name. Apply documented standard filters and constrain the partition field and date range to avoid full-table scans.
Check the documented grain of each model, which states what one row represents, before joining. The index notes key join keys per model so you can join on the canonical dimension without duplicating rows.
Organize your models into logical domain sections, then for each model add the table name, a one-to-two sentence description of its grain and content, and "Useful for" bullets. Also document standard filters, plan types, and any sensitive datasets.
Large partitioned tables incur high scan costs when queried without partition filters. The index instructs always filtering on the partition field and constraining the date range to control costs and improve query performance.
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