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/clickhouse-best-practices

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by clickhouseclickhouse/agent-skills543 stars
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MUST USE when reviewing ClickHouse schemas, queries, or configurations. Contains 31 rules that MUST be checked before providing recommendations. Always read relevant rule files and cite specific rules in responses.

Use this Skill: https://skilld.dev/gh/clickhouse/agent-skills/clickhouse-best-practices

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rulesschema-types-native-types.md

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Use Native Types Instead of String

Impact: CRITICAL

Using String for all data wastes storage, prevents compression optimization, and makes comparisons slower. ClickHouse's column-oriented architecture benefits directly from optimal type selection.

Incorrect (String for everything):

CREATE TABLE events (
    event_id String,        -- "550e8400-e29b-41d4-a716-446655440000" = 36 bytes
    user_id String,         -- "12345" = 5 bytes (no numeric operations)
    created_at String,      -- "2024-01-15 10:30:00" = 19 bytes
    count String,           -- "42" - can't do math!
    is_active String        -- "true" = 4 bytes
)

Correct (native types):

CREATE TABLE events (
    event_id UUID DEFAULT generateUUIDv4(),     -- 16 bytes (vs 36)
    user_id UInt64,                              -- 8 bytes, numeric ops
    created_at DateTime DEFAULT now(),           -- 4 bytes (vs 19)
    count UInt32 DEFAULT 0,                      -- 4 bytes, math works
    is_active Bool DEFAULT true                  -- 1 byte (vs 4)
)

Type Selection Quick Reference:

Data Use Avoid
Sequential IDs UInt32/UInt64 String
UUIDs UUID String
Status/Category Enum8 or LowCardinality(String) String
Timestamps DateTime DateTime64, String
Dates only Date or Date32 DateTime, String
Counts UInt8/16/32 (smallest that fits) Int64, String
Money Decimal(P,S) or Int64 (cents) Float64, String
Booleans Bool or UInt8 String

Reference: Select Data Types

Source: SKILL.md on GitHub

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    This skill provides comprehensive best practices for ClickHouse database management, including schema design, query optimization, and ingestion strategies. It includes robust safety guardrails for AI agents, such as mandatory query limits, execution timeouts, and a structured schema discovery workflow. All external references and tools trace back to official ClickHouse vendor resources.

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Signed by skilld at d284161. This ties the file your Agent reads to that commit on GitHub. It does not review the instructions.

Last checked against GitHub 3 days ago.

Activeupdated 5 months ago
metadata
{
  "author": "ClickHouse Inc",
  "version": "0.4.0"
}

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Provides 31 ClickHouse-specific rules organized by priority across schema design, query optimization, data ingestion, and agent connectivity. Use this skill to validate schemas, review queries, and establish safe agent workflows with proper connection setup, schema discovery, and query safety procedures.

Generated from the current SKILL.md.

When should I use this skill?
Use this skill when reviewing ClickHouse schemas, queries, or data ingestion strategies. It contains 31 rules covering primary key design, data types, JOINs, partitioning, and insert batching that you must check before providing ClickHouse recommendations.
Does this skill help with AI agent connectivity to ClickHouse?
Yes. The skill includes rules for MCP and CLI connection setup, schema discovery workflows, and query safety (LIMIT, timeouts, progressive exploration) specific to AI agents querying ClickHouse.
What should I do if a rule doesn't exist for my question?
Fall back to the LLM's ClickHouse knowledge, search the official ClickHouse documentation, or use web search. Always cite your source in the response.
Are the rules mandatory or advisory?
The rules are mandatory checks before answering ClickHouse questions. They encode ClickHouse-specific behaviors (columnar storage, merge tree mechanics, sparse indexes) where general database intuition can be misleading.
Can I use this skill for INSERT performance tuning?
Yes. The skill covers batch sizing (10K-100K rows), async inserts for high-frequency small batches, mutation avoidance (ReplacingMergeTree instead of ALTER UPDATE), and OPTIMIZE TABLE risks.

Generated from the current SKILL.md. These answers refresh after source changes.