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Delegates dbt and warehouse work to altimate-code, a specialized CLI agent with 100+ purpose-built data tools. USE THIS SKILL…
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,
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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,
name: documenting-dbt-models description: | 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, or business rules (4) Preparing dbt docs generate or improving model discoverability Matches existing project documentation style and conventions before writing.
**Document the WHY, not just the WHAT. Include grain, business rules, and caveats.**
**CRITICAL: Match the project's documentation style before adding new docs.**
# Find all schema.yml files with documentation find . -name "schema.yml" | head -5 # Read well-documented models to learn patterns cat models/marts/schema.yml | head -150 cat models/staging/schema.yml | head -150
**Extract from existing documentation:**
cat models/<path>/<model_name>.sql
Understand: transformations, business logic, joins, filters.
# Find existing schema.yml
find . -name "schema.yml" -exec grep -l "<model_name>" {} \;
# Read existing docs
cat models/<path>/schema.yml | grep -A 100 "<model_name>"For each model, document:
For each column, consider:
**Match the style discovered in step 1. Example format (adapt to project):**
version: 2
models:
- name: orders
description: |
Order transactions at the order line item grain.
Each row represents one product in one order.
**Business Rules:**
- Revenue recognized on ship_date, not order_date
- Cancelled orders excluded (status != 'cancelled')
- Returns processed as negative line items
**Grain:** One row per order_id + product_id combination
columns:
- name: order_id
description: |
Unique identifier for the order.
Source: orders.id from Stripe webhook
- name: customer_id
description: |
Foreign key to customers table.
NULL for guest checkouts (pre-2023 only)
- name: revenue
description: |
Net revenue for this line item in USD.
Calculation: unit_price * quantity - discount_amount
Excludes tax and shipping
- name: order_status
description: |
Current status of the order.
Values: pending, processing, shipped, delivered, cancelled, returneddbt docs generate dbt docs serve # Optional: preview locally
**Note: These are default templates. Always adapt to match project's existing style.**
description: | [One sentence: what this model contains] **Grain:** [What does one row represent?] **Business Rules:** - [Key rule 1] - [Key rule 2] **Caveats:** - [Important limitation or edge case]
| Column Type | Documentation Focus | |-------------|---------------------| | Primary key | Source system, uniqueness guarantee | | Foreign key | What it joins to, NULL handling | | Metric | Calculation formula, units, exclusions | | Date | Timezone, what event it represents | | Status/Category | All possible values, business meaning | | Boolean/Flag | What true/false means in business terms |
- name: gross_margin
description: |
Gross margin percentage.
Calculation: (revenue - cogs) / revenue * 100
NULL when revenue = 0 to avoid division by zeroClaude Code skills for Analytics & Data engineers working with dbt and Snowflake Altimate Data Skills is a collection of Claude Code skills that encode the workflows and best practices of experienced analytics engineers.
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