cc-skill-clickhouse-io

ClickHouse database patterns, query optimization, analytics, and data engineering best practices for high-performance analytical workloads.

Install with Tessl CLI

npx tessl i github:sickn33/antigravity-awesome-skills --skill cc-skill-clickhouse-io

What are skills?

1.27x

Review — 48%

Does it follow best practices?

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Learn more

Evaluation — 97%

↑ 1.27x

Agent success when using this skill

Validation — 10 / 11 Passed

Validation for skill structure

SKILL.md

Review

Evals

Evaluation results

98%

10%

E-Commerce Analytics Platform: ClickHouse Schema Design

ClickHouse table schema design

Criteria

Without context

With context

MergeTree engine

100%

index_granularity setting

100%

Time-based partition

100%

DATE partition key type

100%

Filtered columns in ORDER BY

100%

LowCardinality usage

100%

Enum usage

100%

Appropriate integer types

75%

ReplacingMergeTree for deduplication

100%

Avoid too many partitions

100%

Denormalized design

100%

No SELECT * in examples

100%

No FINAL in examples

100%

Without context: $0.4153 · 1m 52s · 13 turns · 14 in / 7,340 out tokens

With context: $0.5009 · 2m 21s · 14 turns · 63 in / 8,705 out tokens

100%

Marketplace Analytics: Query Layer and Real-Time Rollups

Analytics query patterns and materialized views

Criteria

Without context

With context

Indexed columns first in WHERE

100%

uniq() for distinct counts

100%

quantile() for percentiles

100%

No SELECT *

100%

No FINAL modifier

100%

Materialized view created

100%

State functions in MV

100%

Merge functions in queries

100%

toStartOfHour/Day/Month in MV

100%

No excessive JOINs

100%

AggregatingMergeTree destination

100%

Without context: $0.2769 · 1m 9s · 11 turns · 60 in / 4,486 out tokens

With context: $0.3527 · 1m 8s · 14 turns · 667 in / 4,133 out tokens

94%

52%

SaaS Metrics Pipeline: Loading Data into ClickHouse

TypeScript ClickHouse data ingestion pipeline

Criteria

Without context

With context

clickhouse npm package

100%

ClickHouse constructor options

100%

Batch insert pattern

40%

100%

No per-row inserts in loop

100%

.toPromise() usage

90%

Streaming insert API

100%

Environment variable config

100%

Batch sizing for bulk load

100%

TypeScript types

100%

Periodic scheduling

Without context: $0.4358 · 1m 44s · 19 turns · 18 in / 6,274 out tokens

With context: $0.8013 · 2m 55s · 30 turns · 76 in / 10,089 out tokens

Evaluated: 6 days ago
Agent: Claude Code
Model: Unknown

Table of Contents

E-Commerce Analytics Platform: ClickHouse Schema Design Marketplace Analytics: Query Layer and Real-Time Rollups SaaS Metrics Pipeline: Loading Data into ClickHouse

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