Cost Report

Requirements

Agent: any (read-only analysis) Tools used: sql_execute, sql_analyze, finops_analyze_credits, finops_expensive_queries, finops_warehouse_advice, finops_unused_resources, finops_query_history

Analyze Snowflake warehouse query costs, identify the most expensive queries, detect anti-patterns, and recommend optimizations.

Workflow

1. Query SNOWFLAKE.ACCOUNT_USAGE.QUERY_HISTORY for the top 20 most expensive queries by credits used:

   SELECT
       query_id,
       query_text,
       user_name,
       warehouse_name,
       query_type,
       credits_used_cloud_services,
       bytes_scanned,
       rows_produced,
       total_elapsed_time,
       execution_status,
       start_time
   FROM SNOWFLAKE.ACCOUNT_USAGE.QUERY_HISTORY
   WHERE start_time >= DATEADD('day', -30, CURRENT_TIMESTAMP())
     AND execution_status = 'SUCCESS'
     AND credits_used_cloud_services > 0
   ORDER BY credits_used_cloud_services DESC
   LIMIT 20;
   

   Use sql_execute to run this query against the connected Snowflake warehouse.

2. Group and summarize the results by:

   • User: Which users are driving the most cost?
   • Warehouse: Which warehouses consume the most credits?
   • Query type: SELECT vs INSERT vs CREATE TABLE AS SELECT vs MERGE, etc.

   Present each grouping as a markdown table.

3. Analyze the top offenders - For each of the top 10 most expensive queries:

   • Run sql_analyze on the query text to detect anti-patterns (SELECT *, missing LIMIT, cartesian products, correlated subqueries, etc.)
   • Summarize anti-patterns found and their severity

4. Classify each query into a cost tier:

   Tier	Credits	Label	Action
   1	< $0.01	Cheap	No action needed
   2	$0.01 - $1.00	Moderate	Review if frequent
   3	$1.00 - $100.00	Expensive	Optimize or review warehouse sizing
   4	> $100.00	Dangerous	Immediate review required

5. Warehouse analysis - Run finops_warehouse_advice to check if warehouses used by the top offenders are right-sized.

6. Unused resource detection - Run finops_unused_resources to find:

   • Stale tables: Tables not accessed in the last 30+ days (candidates for archival/drop)
   • Idle warehouses: Warehouses with no query activity (candidates for suspension/removal)

   Include findings in the report under a "Waste Detection" section.

7. Query history enrichment - Run finops_query_history to fetch recent execution patterns:

   • Identify frequently-run expensive queries (high frequency × high cost = top optimization target)
   • Find queries that could benefit from result caching or materialization

8. Output the final report as a structured markdown document:

   # Snowflake Cost Report (Last 30 Days)
   
   ## Summary
   - Total credits consumed: X
   - Number of unique queries: Y
   - Most expensive query: Z credits
   
   ## Cost by User
   | User | Total Credits | Query Count | Avg Credits/Query |
   |------|--------------|-------------|-------------------|
   
   ## Cost by Warehouse
   | Warehouse | Total Credits | Query Count | Avg Credits/Query |
   |-----------|--------------|-------------|-------------------|
   
   ## Cost by Query Type
   | Query Type | Total Credits | Query Count | Avg Credits/Query |
   |------------|--------------|-------------|-------------------|
   
   ## Top 10 Expensive Queries (Detailed Analysis)
   
   ### Query 1 (X credits) - DANGEROUS
   **User:** user_name | **Warehouse:** wh_name | **Type:** SELECT
   **Anti-patterns found:**
   - SELECT_STAR (warning): Query uses SELECT * ...
   - MISSING_LIMIT (info): ...
   
   **Optimization suggestions:**
   1. Select only needed columns
   2. Add LIMIT clause
   3. Consider partitioning strategy
   
   **Cost tier:** Tier 1 (based on credits used)
   
   ...
   
   ## Waste Detection
   ### Unused Tables
   | Table | Last Accessed | Size | Recommendation |
   |-------|--------------|------|----------------|
   
   ### Idle Warehouses
   | Warehouse | Last Query | Size | Recommendation |
   |-----------|-----------|------|----------------|
   
   ## Recommendations
   1. Top priority optimizations
   2. Warehouse sizing suggestions
   3. Unused resource cleanup
   4. Scheduling recommendations
   

Usage

The user invokes this skill with:

• /cost-report -- Analyze the last 30 days
• /cost-report 7 -- Analyze the last 7 days (adjust the DATEADD interval)

Use the tools: sql_execute, sql_analyze, finops_analyze_credits, finops_expensive_queries, finops_warehouse_advice, finops_unused_resources, finops_query_history.