Loading skill
Install any skill in seconds. Free to start, no credit card required.
Get Started Free →vibeeval/clickhouse-io
ClickHouse database patterns, query optimization, analytics, and data engineering best practices for high-performance analytical workloads.
Passed 17 of 23 test cases with the skill, and 15 of 23 without it.
2 fixed15 passed either way6 still failing0 broke
Tokens, turns and time describe resource use, not a dollar price.
One of 2 test cases the skill fixed. Same model, same prompt, with and without the skill.
Write a ClickHouse SQL query to compute a 30-day running cumulative sum of trade volume per market from `markets_analytics` using window functions.
| Checked | Without skill | With skill |
|---|---|---|
| Output includes ROWS BETWEEN UNBOUNDED PRECEDING AND CURRENT ROW in the window clause. | Missed | Passed |
The instructions your model reads when the skill loads.
ClickHouse-specific patterns for high-performance analytics and data engineering.
ClickHouse is a column-oriented database management system (DBMS) for online analytical processing (OLAP). It's optimized for fast analytical queries on large datasets.
Key Features:
CREATE TABLE markets_analytics (
date Date,
market_id String,
market_name String,
volume UInt64,
trades UInt32,
unique_traders UInt32,
avg_trade_size Float64,
created_at DateTime
) ENGINE = MergeTree()
PARTITION BY toYYYYMM(date)
ORDER BY (date, market_id)
SETTINGS index_granularity = 8192;
-- For data that may have duplicates (e.g., from multiple sources)
CREATE TABLE user_events (
test cases passed, vs 15 / 23 without
Published skills whose descriptions closely match this one, with their headline benchmark lift.
More skills from the same source and nearby in the registry, with their headline benchmark lift.