Danyel.pr46 llm 051125

.github/prompts/ms1-response-format.md

@@ -7,54 +7,40 @@
 
 ## Changed Models
 
-**Modified Models** (X files):
-- `models/staging/stg_customers.sql`
-- `models/marts/customers.sql`
-- [list all modified .sql files]
+**Modified Models** (X models. Do not show this section if there are none.):
 
-**New Models** (Y files):
-- `models/marts/new_model.sql`
-- [list if any]
-
-**Removed Models** (Z files):
-- `models/deprecated/old_model.sql`
-- [list if any]
-
-**Other Changes**:
-- Schema files modified: [list .yml files if any]
-- Configuration changes: [packages.yml, dbt_project.yml if modified]
-
----
+- `stg_user_data` - note
+- `customers`
+- [list all modified models]
 
-## Change Breakdown by Layer
+**New Models** (Y models. Do not show this section if there are none.):
 
-### Staging Models
-- X models modified
-- Focus: [brief description of changes]
+- `new_model`
+- [list if any]
 
-### Marts Models
-- Y models modified
-- Focus: [brief description of changes]
+**Removed Models** (Z models. Do not show this section if there are none.):
 
-### Other Layers
-- [if applicable]
+- `old_model`
+- [list if any]
 
 ---
 
 ## Potential Impact (Qualitative Assessment)
 
 Based on file locations and dbt conventions:
+
 - **Scope**: [Wide/Medium/Narrow] - affects [staging/marts/specific area]
 - **Risk Level**: [High/Medium/Low] - based on number of models and model types
-- **Breaking Changes**: [Possible/Unlikely] - note if schema files also modified
+- **Breaking Changes**: [Possible/Unlikely] - what the changes are
 
-> **Note**: This assessment is based on file changes only. For precise dependency analysis and data validation, use `/ms2` (with dbt metadata) or `/ms3` (with full data diff).
+> **Note**: This assessment is based on file changes only. For precise dependency analysis and data validation, add dbt artifacts and data sources.
 
 ---
 
 ## Limitations of MS1 Analysis
 
 At this milestone, the analysis is limited to:
+
 - ✅ Identifying which models changed (from Git diff)
 - ✅ Categorizing changes by directory structure
 - ❌ Cannot analyze downstream dependencies (requires dbt lineage metadata)
@@ -65,17 +51,12 @@ At this milestone, the analysis is limited to:
 
 ## Recommended Next Steps
 
-### For Deeper Analysis
-
-1. **Run MS2 Analysis** (`@claude /ms2`):
-   - Requires: dbt artifacts (manifest.json, catalog.json)
-   - Provides: Lineage diff, downstream impact, breaking change detection
-   - Suggests: Preset checks based on recce.yml
+### Recommended Follow-up Checks
 
-2. **Run MS3 Analysis** (`@claude /ms3`):
-   - Requires: MS2 + data warehouse connection
-   - Provides: Row count diffs, profile diffs, value changes
-   - Quantifies: Actual data impact with metrics
+[] Check changed definitions, such as `old_model.changed_column`
+[] Check downstream impact of changed `old_model.changed_column`
+[] Validate new model, `new_model`
+[] Ensure no downstream impact for removed `old_model`
 
 ### Launch Recce for Interactive Validation
 
@@ -89,4 +70,3 @@ At this milestone, the analysis is limited to:
 - **Title**: [PR title]
 - **Files Changed**: [total count]
 - **Branch**: [head branch] → [base branch]
-

.github/prompts/ms1-system-prompt.md

@@ -9,6 +9,7 @@ Analyze which dbt models have been changed in this PR by examining Git diffs and
 ### Available Tools
 
 You are LIMITED to the following tools:
+
 - ✅ `Read(*)` - Read any files in the repository
 - ✅ `Bash(gh pr view *)` - Get PR information via GitHub CLI
 - ✅ `Bash(git *)` - Execute Git commands to analyze file changes
@@ -18,39 +19,46 @@ You are LIMITED to the following tools:
 ### Analysis Steps
 
 1. **Get PR Information**
+
    - Use `gh pr view` to get PR title, description, and basic metadata
    - Review PR body for context about the changes
 
 2. **Analyze Git Changes**
+
    - Use `git diff` to identify modified files
    - Focus on `.sql` files in the `models/` directory
    - Identify other relevant changes (`.yml` schema files, `packages.yml`, etc.)
 
 3. **Infer Model Changes**
+
    - From modified `.sql` files, infer which dbt models are affected
    - Group changes by directory (staging, marts, intermediate, etc.)
    - Note if any models are added or removed
 
 4. **Assess Potential Impact**
+
    - Based on file paths and dbt naming conventions, provide qualitative assessment
    - Note if changes affect staging vs marts models
-   - Highlight if schema files (`.yml`) are also modified
+
+5. **Suggest Next Steps**
+   - Suggest models and columns that the user should carefully check
 
 ### Output Requirements
 
 Generate a summary following the MS1 response format that includes:
-- List of changed dbt models (from Git diff)
-- Categorization by model type/directory
+
+- List of changed dbt models (from Git diff).
 - Qualitative impact assessment
+- Suggest follow-up checks for the highest-risk changes
 - Link to launch Recce for detailed validation
 
 ### Limitations to Communicate
 
 Since this is MS1 (Git context only), you should clearly state:
+
 - ✅ Can identify which models changed
 - ❌ Cannot analyze downstream dependencies (requires MS2)
 - ❌ Cannot validate data quality (requires MS3)
 - ❌ Cannot suggest preset checks (requires dbt metadata)
 
-**Next Steps for User**: Recommend running `/ms2` or `/ms3` for deeper analysis if dbt artifacts are available.
-
+**Next Steps for User**: List important changed

models/customer_segments.sql

@@ -3,6 +3,7 @@ SELECT
     customer_id,
     number_of_orders,
     customer_lifetime_value,
+    net_customer_lifetime_value,
     CASE 
         WHEN number_of_orders > 10 THEN 'Frequent Buyer'
         WHEN number_of_orders BETWEEN 5 AND 10 THEN 'Occasional Buyer'
@@ -12,5 +13,10 @@ SELECT
         WHEN customer_lifetime_value > 4000 THEN 'High Value'
         WHEN customer_lifetime_value BETWEEN 1500 AND 4000 THEN 'Medium Value'
         ELSE 'Low Value'
-    END AS value_segment
+    END AS value_segment,
+    CASE 
+        WHEN net_customer_lifetime_value > 4000 THEN 'High Value'
+        WHEN net_customer_lifetime_value BETWEEN 1500 AND 4000 THEN 'Medium Value'
+        ELSE 'Low Value'
+    END AS net_value_segment
 FROM {{ ref('customers') }}

models/customers.sql

@@ -34,12 +34,17 @@ customer_payments as (
 
     select
         orders.customer_id,
-        sum(amount)::bigint as total_amount
+        sum(amount)::bigint as gross_amount, -- Includes coupon amount
+        sum(amount - coupon_amount)::bigint as net_amount, -- Excludes coupon amount
 
     from payments
 
     left join orders on
          payments.order_id = orders.order_id
+        and orders.status = 'completed'
+
+    where payments.amount is not null -- Exclude incomplete payments
+        and payments.amount > 0 -- Exclude negative amounts
 
     group by orders.customer_id
 
@@ -54,7 +59,8 @@ final as (
         customer_orders.first_order,
         customer_orders.most_recent_order,
         customer_orders.number_of_orders,
-        customer_payments.total_amount as customer_lifetime_value
+        customer_payments.gross_amount as customer_lifetime_value, -- Gross CLV
+        customer_payments.net_amount as net_customer_lifetime_value -- Net CLV
 
     from customers
 

models/finance_revenue.sql

@@ -0,0 +1,31 @@
+ with payments as (
+    select * from {{ ref('stg_payments') }}
+),
+
+payments_revenue as (
+    select
+        order_id,
+        sum(amount) as gross_revenue,
+        sum(amount - coupon_amount) as net_revenue
+    from payments
+    group by order_id
+),
+
+orders as (
+    select * from {{ ref('stg_orders') }}
+),
+
+final as (  
+    select
+        orders.order_id,
+        orders.customer_id,
+        orders.order_date,
+        orders.status,
+        payments_revenue.gross_revenue,
+        payments_revenue.net_revenue
+    from orders
+    left join payments_revenue
+        on orders.order_id = payments_revenue.order_id
+)
+
+select * from final

models/schema.yml

@@ -2,7 +2,7 @@ version: 2
 
 models:
   - name: customers
-    description: This table has basic information about a customer, as well as some derived facts based on a customer's orders
+    description: This table has basic information about a customer, as well as some derived facts based on a customer's orders and payments, including both gross and profit-based customer lifetime value metrics
 
     columns:
       - name: customer_id
@@ -26,33 +26,57 @@ models:
       - name: number_of_orders
         description: Count of the number of orders a customer has placed
 
+      - name: customer_lifetime_value
+        description: Total value of a customer's orders including coupon amounts
+
+      - name: net_customer_lifetime_value
+        description: Total value of a customer's orders excluding coupon amounts
+
       - name: total_order_amount
         description: Total value (AUD) of a customer's orders
 
   - name: customer_segments
-    description: This table categorizes customers based on their ordering behavior and value to the company, using derived metrics from their order history.
+    description: This table categorizes customers based on their ordering behavior and value to the company, using derived metrics from their order history and payment information.
 
     columns:
       - name: customer_id
         description: This is a unique identifier for a customer.
         tests:
           - unique
           - not_null
+          - relationships:
+              to: ref('customers')
+              field: customer_id
 
       - name: number_of_orders
         description: Count of the number of orders a customer has placed.
+        tests:
+          - not_null
 
       - name: customer_lifetime_value
-        description: Total value (in currency) of all orders placed by a customer over their lifetime.
+        description: Total value of all orders including coupon amounts.
+
+      - name: net_customer_lifetime_value
+        description: Total value of all orders excluding coupon amounts.
 
       - name: order_frequency_segment
         description: Categorization of customers based on how frequently they place orders.
+        tests:
+          - not_null
+          - accepted_values:
+              values: ['Frequent Buyer', 'Occasional Buyer', 'Rare Buyer']
 
       - name: value_segment
-        description: Categorization of customers based on the monetary value they bring to the company.
+        description: Categorization of customers based on the gross monetary value they bring to the company.
         tests:
           - accepted_values:
-              values:  ['High Value', 'Medium Value', 'Low Value']
+              values: ['High Value', 'Medium Value', 'Low Value']
+
+      - name: net_value_segment
+        description: Categorization of customers based on the profit-based monetary value they bring to the company.
+        tests:
+          - accepted_values:
+              values: ['High Value', 'Medium Value', 'Low Value']
 
   - name: customer_order_pattern
     description: This table provides detailed insights into the ordering patterns of customers, including the frequency and recency of their orders.
@@ -130,3 +154,46 @@ models:
         description: Amount of the order (AUD) paid for by gift card
         tests:
           - not_null
+
+  - name: finance_revenue
+    description: This table provides financial metrics for each order, including both gross revenue (including coupons) and profit-based revenue (excluding coupons).
+
+    columns:
+      - name: order_id
+        description: This is a unique identifier for an order
+        tests:
+          - unique
+          - not_null
+          - relationships:
+              to: ref('stg_orders')
+              field: order_id
+
+      - name: customer_id
+        description: Foreign key to the customers table
+        tests:
+          - not_null
+          - relationships:
+              to: ref('customers')
+              field: customer_id
+
+      - name: order_date
+        description: Date (UTC) that the order was placed
+        tests:
+          - not_null
+
+      - name: status
+        description: Current status of the order
+        tests:
+          - not_null
+          - accepted_values:
+              values: ['placed', 'shipped', 'completed', 'return_pending', 'returned']
+
+      - name: gross_revenue
+        description: Total revenue including coupon amounts
+        tests:
+          - not_null
+
+      - name: net_revenue
+        description: Total revenue excluding coupon amounts
+        tests:
+          - not_null

models/staging/schema.yml

@@ -29,3 +29,11 @@ models:
         tests:
           - accepted_values:
               values: ['credit_card', 'coupon', 'bank_transfer', 'gift_card']
+      - name: amount
+        description: Amount in dollars (converted from cents)
+        tests:
+          - not_null
+      - name: coupon_amount
+        description: Amount of the payment that was paid using a coupon (in dollars)
+        tests:
+          - not_null

models/staging/stg_payments.sql

@@ -16,7 +16,8 @@ renamed as (
         payment_method,
 
         -- `amount` is currently stored in cents, so we convert it to dollars
-        amount / 100 as amount
+        amount / 100 as amount,
+        (payment_method = 'coupon')::int * (amount / 100) as coupon_amount
 
     from source