Finding Expensive Queries Agent Skill
| (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 candidates (4) Finding queries that scan the most data or have the most spillage Returns ranked list of queries with metrics and optimization recommendations.
Install
one command, takes just this skill from the repositorynpx skills add https://github.com/AltimateAI/data-engineering-skills --skill finding-expensive-queriesThe instruction itself
8 sections, as written by the authorFinding Expensive Queries
Query history → Rank by metric → Identify patterns → Recommend optimizations
Workflow
1. Ask What to Optimize For
Before querying, clarify:
- Time period? (last day, week, month)
- Metric? (execution time, bytes scanned, cost, spillage)
- Warehouse? (specific or all)
- User? (specific or all)
2. Find Expensive Queries by Cost
Use QUERY_ATTRIBUTION_HISTORY for credit/cost analysis:
SELECT
query_id,
warehouse_name,
user_name,
credits_attributed_compute,
start_time,
end_time,
query_tag
FROM SNOWFLAKE.ACCOUNT_USAGE.QUERY_ATTRIBUTION_HISTORY
WHERE start_time >= DATEADD('days', -7, CURRENT_TIMESTAMP())
ORDER BY credits_attributed_compute DESC
LIMIT 20;
3. Get Performance Stats for Specific Queries
Use QUERY_HISTORY for detailed performance metrics (run separately, not joined):
SELECT
query_id,
query_text,
total_elapsed_time/1000 as seconds,
bytes_scanned/1e9 as gb_scanned,
bytes_spilled_to_local_storage/1e9 as gb_spilled_local,
bytes_spilled_to_remote_storage/1e9 as gb_spilled_remote,
partitions_scanned,
partitions_total
FROM SNOWFLAKE.ACCOUNT_USAGE.QUERY_HISTORY
WHERE query_id IN ('<query_id_1>', '<query_id_2>', ...)
AND start_time >= DATEADD('days', -7, CURRENT_TIMESTAMP());
4. Identify Patterns
Look for:
- High
credits_attributed_computequeries - Same
query_hashrepeated (caching opportunity) partitions_scanned = partitions_total(no pruning)- High
gb_spilled(memory pressure)
5. Return Results
Provide:
- Ranked list of expensive queries with key metrics
- Common patterns identified
- Top 3-5 optimization recommendations
- Specific queries to investigate further
Common Filters
-- Time range (required)
WHERE start_time >= DATEADD('days', -7, CURRENT_TIMESTAMP())
-- By warehouse
AND warehouse_name = 'ANALYTICS_WH'
-- By user
AND user_name = 'ETL_USER'
-- Only queries over cost threshold
AND credits_attributed_compute > 0.01
-- Only queries over time threshold
AND total_elapsed_time > 60000 -- over 1 minute
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How to use it
Take altimateai/finding-expensive-queries from the repository into ~/.claude/skills for personal
use, or into .claude/skills inside a project.
The agent identifies a skill by the name field in its header. Two skills with the
same name cannot sit side by side — one of them will be ignored.