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clickhouse-best-practices

clickhouse/agent-skills

31 ClickHouse best-practice rules for schema design, query optimization, and data ingestion.

What is clickhouse-best-practices?

Comprehensive guidance for reviewing ClickHouse schemas, queries, configurations, and agent connectivity. Contains 31 rules organized by priority (primary key, data types, JOINs, insert batching, mutations, partitioning, indices) that must be checked before providing recommendations. Always cite applicable rules in responses.

  • Check PRIMARY KEY and ORDER BY design against cardinality and filter patterns
  • Validate data type selection (native types, bitwidth, LowCardinality, Nullable)
  • Review JOIN algorithms, pre-join filtering, and query optimization
  • Assess INSERT batching, mutation avoidance, and async insert strategies
  • Evaluate partitioning strategy and lifecycle management
  • Guide agent schema discovery and query safety workflows

How to install clickhouse-best-practices

npx skills add https://github.com/clickhouse/agent-skills --skill clickhouse-best-practices
Claude Code
Cursor
Windsurf
Cline

How to use clickhouse-best-practices

  1. 1.Install the skill: npx skills add https://github.com/clickhouse/agent-skills --skill clickhouse-best-practices
  2. 2.When reviewing a ClickHouse schema, query, or configuration, identify the category (schema design, query optimization, insert strategy, or agent connectivity)
  3. 3.Read the applicable rule files in the priority order specified in the skill documentation
  4. 4.Check each rule against the code or configuration; note violations and compliant items
  5. 5.Structure your response using the provided output format: Rules Checked, Findings (Violations + Compliant), Recommendations
  6. 6.Cite specific rule names (e.g., 'Per rule-schema-pk-cardinality-order...') in all recommendations

Use cases

Good for
  • Review a CREATE TABLE statement for PRIMARY KEY and data type violations before deployment
  • Analyze a slow SELECT query to identify missing ORDER BY prefix filters or suboptimal JOIN algorithms
  • Assess an UPDATE-heavy workflow and recommend ReplacingMergeTree or CollapsingMergeTree alternatives
  • Plan schema discovery and safe query execution for an AI agent connecting to ClickHouse
  • Validate INSERT batch sizes and async insert configuration for high-frequency data ingestion
Who it's for
  • ClickHouse database architects and schema designers
  • Backend engineers optimizing ClickHouse queries and data pipelines
  • AI agents (Claude Code, Cursor) querying ClickHouse databases
  • DevOps and data platform teams reviewing ClickHouse configurations
  • Teams migrating to ClickHouse seeking best-practice validation

clickhouse-best-practices FAQ

What should I do if no applicable rule exists for my ClickHouse question?

Use the LLM's ClickHouse knowledge, consult the official ClickHouse documentation, or perform a web search for current best practices. Always cite your source (rule name, 'general ClickHouse guidance', or URL).

Why do the rules take priority over general database intuition?

ClickHouse has specific behaviors (columnar storage, sparse indexes, merge tree mechanics) where general database intuition can be misleading. The rules encode validated, ClickHouse-specific guidance.

What is the agent connectivity workflow?

Agents must follow: (1) Connect via MCP or CLI (agent-connect-mcp), (2) Discover schema using 7-step workflow (agent-discovery-schema), (3) Plan queries using sort key and skip index knowledge, (4) Execute with LIMIT and timeouts, (5) Recover on errors by narrowing filters (agent-query-safety).

Which rules are CRITICAL vs HIGH priority?

CRITICAL: Primary Key Selection, Data Type Selection, JOIN Optimization, Insert Batching, Mutation Avoidance, Agent Schema Discovery, Agent Query Safety. HIGH: Partitioning, Skipping Indices, Materialized Views, Async Inserts, OPTIMIZE Avoidance, Agent Connectivity.

How should I structure my review response?

Use: Rules Checked (list with Compliant/Violation status), Findings (separate Violations and Compliant sections with specific issues and fixes), Recommendations (prioritized list citing rules).

Full instructions (SKILL.md)

Source of truth, from clickhouse/agent-skills.


name: clickhouse-best-practices description: 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. license: Apache-2.0 metadata: author: ClickHouse Inc version: "0.4.0"

ClickHouse Best Practices

Comprehensive guidance for ClickHouse covering schema design, query optimization, data ingestion, and AI agent connectivity. Contains 31 rules across 4 main categories (schema, query, insert, agent), prioritized by impact.

Official docs: ClickHouse Best Practices

IMPORTANT: How to Apply This Skill

Before answering ClickHouse questions, follow this priority order:

  1. Check for applicable rules in the rules/ directory
  2. If rules exist: Apply them and cite them in your response using "Per rule-name..."
  3. If no rule exists: Use the LLM's ClickHouse knowledge or search documentation
  4. If uncertain: Use web search for current best practices
  5. Always cite your source: rule name, "general ClickHouse guidance", or URL

Why rules take priority: ClickHouse has specific behaviors (columnar storage, sparse indexes, merge tree mechanics) where general database intuition can be misleading. The rules encode validated, ClickHouse-specific guidance.


Agent Connectivity & Query Workflow

Before querying ClickHouse, agents must establish a connection and follow the discovery workflow:

  1. rules/agent-connect-mcp.md - Connection setup (MCP + CLI), credential discovery, output format selection
  2. rules/agent-discovery-schema.md - CRITICAL: 7-step schema discovery workflow
  3. rules/agent-query-safety.md - CRITICAL: LIMIT, timeouts, progressive exploration

Every agent session should follow this sequence:

  1. Connect — establish connection via MCP or CLI (see agent-connect-mcp)
  2. Discover — databases → tables → columns + comments → sort keys → skip indexes → sample → EXPLAIN
  3. Plan — use sort key and skip index knowledge to write efficient WHERE clauses
  4. Execute — run queries with LIMIT and timeouts
  5. Recover — on timeout/memory errors, narrow filters and retry (see agent-query-safety)

Subagent architecture notes

If your system dispatches ClickHouse tasks to specialized subagents:

  • Schema discovery + query execution: any model — the steps are procedural
  • EXPLAIN analysis + query optimization: benefits from mid-tier reasoning
  • Schema design review against all 28 rules: benefits from mid-tier reasoning

Review Procedures

For Schema Reviews (CREATE TABLE, ALTER TABLE)

Read these rule files in order:

  1. rules/schema-pk-plan-before-creation.md - ORDER BY is immutable
  2. rules/schema-pk-cardinality-order.md - Column ordering in keys
  3. rules/schema-pk-prioritize-filters.md - Filter column inclusion
  4. rules/schema-types-native-types.md - Proper type selection
  5. rules/schema-types-minimize-bitwidth.md - Numeric type sizing
  6. rules/schema-types-lowcardinality.md - LowCardinality usage
  7. rules/schema-types-avoid-nullable.md - Nullable vs DEFAULT
  8. rules/schema-partition-low-cardinality.md - Partition count limits
  9. rules/schema-partition-lifecycle.md - Partitioning purpose

Check for:

  • PRIMARY KEY / ORDER BY column order (low-to-high cardinality)
  • Data types match actual data ranges
  • LowCardinality applied to appropriate string columns
  • Partition key cardinality bounded (100-1,000 values)
  • ReplacingMergeTree has version column if used

For Query Reviews (SELECT, JOIN, aggregations)

Read these rule files:

  1. rules/query-join-choose-algorithm.md - Algorithm selection
  2. rules/query-join-filter-before.md - Pre-join filtering
  3. rules/query-join-use-any.md - ANY vs regular JOIN
  4. rules/query-index-skipping-indices.md - Secondary index usage
  5. rules/schema-pk-filter-on-orderby.md - Filter alignment with ORDER BY

Check for:

  • Filters use ORDER BY prefix columns
  • JOINs filter tables before joining (not after)
  • Correct JOIN algorithm for table sizes
  • Skipping indices for non-ORDER BY filter columns

For Insert Strategy Reviews (data ingestion, updates, deletes)

Read these rule files:

  1. rules/insert-batch-size.md - Batch sizing requirements
  2. rules/insert-mutation-avoid-update.md - UPDATE alternatives
  3. rules/insert-mutation-avoid-delete.md - DELETE alternatives
  4. rules/insert-async-small-batches.md - Async insert usage
  5. rules/insert-optimize-avoid-final.md - OPTIMIZE TABLE risks

Check for:

  • Batch size 10K-100K rows per INSERT
  • No ALTER TABLE UPDATE for frequent changes
  • ReplacingMergeTree or CollapsingMergeTree for update patterns
  • Async inserts enabled for high-frequency small batches

Output Format

Structure your response as follows:

## Rules Checked
- `rule-name-1` - Compliant / Violation found
- `rule-name-2` - Compliant / Violation found
...

## Findings

### Violations
- **`rule-name`**: Description of the issue
  - Current: [what the code does]
  - Required: [what it should do]
  - Fix: [specific correction]

### Compliant
- `rule-name`: Brief note on why it's correct

## Recommendations
[Prioritized list of changes, citing rules]

Rule Categories by Priority

PriorityCategoryImpactPrefixRule Count
1Primary Key SelectionCRITICALschema-pk-4
2Data Type SelectionCRITICALschema-types-5
3JOIN OptimizationCRITICALquery-join-5
4Insert BatchingCRITICALinsert-batch-1
5Mutation AvoidanceCRITICALinsert-mutation-2
6Partitioning StrategyHIGHschema-partition-4
7Skipping IndicesHIGHquery-index-1
8Materialized ViewsHIGHquery-mv-2
9Async InsertsHIGHinsert-async-2
10OPTIMIZE AvoidanceHIGHinsert-optimize-1
11JSON UsageMEDIUMschema-json-1
12Agent Schema DiscoveryCRITICALagent-discovery-1
13Agent Query SafetyCRITICALagent-query-1
14Agent Connectivity + FormatsHIGHagent-connect-1

Quick Reference

Schema Design - Primary Key (CRITICAL)

  • schema-pk-plan-before-creation - Plan ORDER BY before table creation (immutable)
  • schema-pk-cardinality-order - Order columns low-to-high cardinality
  • schema-pk-prioritize-filters - Include frequently filtered columns
  • schema-pk-filter-on-orderby - Query filters must use ORDER BY prefix

Schema Design - Data Types (CRITICAL)

  • schema-types-native-types - Use native types, not String for everything
  • schema-types-minimize-bitwidth - Use smallest numeric type that fits
  • schema-types-lowcardinality - LowCardinality for <10K unique strings
  • schema-types-enum - Enum for finite value sets with validation
  • schema-types-avoid-nullable - Avoid Nullable; use DEFAULT instead

Schema Design - Partitioning (HIGH)

  • schema-partition-low-cardinality - Keep partition count 100-1,000
  • schema-partition-lifecycle - Use partitioning for data lifecycle, not queries
  • schema-partition-query-tradeoffs - Understand partition pruning trade-offs
  • schema-partition-start-without - Consider starting without partitioning

Schema Design - JSON (MEDIUM)

  • schema-json-when-to-use - JSON for dynamic schemas; typed columns for known

Query Optimization - JOINs (CRITICAL)

  • query-join-choose-algorithm - Select algorithm based on table sizes
  • query-join-use-any - ANY JOIN when only one match needed
  • query-join-filter-before - Filter tables before joining
  • query-join-consider-alternatives - Dictionaries/denormalization vs JOIN
  • query-join-null-handling - join_use_nulls=0 for default values

Query Optimization - Indices (HIGH)

  • query-index-skipping-indices - Skipping indices for non-ORDER BY filters

Query Optimization - Materialized Views (HIGH)

  • query-mv-incremental - Incremental MVs for real-time aggregations
  • query-mv-refreshable - Refreshable MVs for complex joins

Insert Strategy - Batching (CRITICAL)

  • insert-batch-size - Batch 10K-100K rows per INSERT

Insert Strategy - Async (HIGH)

  • insert-async-small-batches - Async inserts for high-frequency small batches
  • insert-format-native - Native format for best performance

Insert Strategy - Mutations (CRITICAL)

  • insert-mutation-avoid-update - ReplacingMergeTree instead of ALTER UPDATE
  • insert-mutation-avoid-delete - Lightweight DELETE or DROP PARTITION

Insert Strategy - Optimization (HIGH)

  • insert-optimize-avoid-final - Let background merges work

Agent Integration - Discovery (CRITICAL)

  • agent-discovery-schema - Always discover schema before querying

Agent Integration - Safety (CRITICAL)

  • agent-query-safety - LIMIT, timeouts, progressive exploration

Agent Integration - Connectivity + Formats (HIGH)

  • agent-connect-mcp - MCP + CLI setup, credential discovery, output format selection

When to Apply

This skill activates when you encounter:

  • AI agent connecting to ClickHouse (MCP, CLI, HTTP)

  • Agent workflow design for ClickHouse

  • Schema discovery or exploration requests

  • CREATE TABLE statements

  • ALTER TABLE modifications

  • ORDER BY or PRIMARY KEY discussions

  • Data type selection questions

  • Slow query troubleshooting

  • JOIN optimization requests

  • Data ingestion pipeline design

  • Update/delete strategy questions

  • ReplacingMergeTree or other specialized engine usage

  • Partitioning strategy decisions


Rule File Structure

Each rule file in rules/ contains:

  • YAML frontmatter: title, impact level, tags
  • Brief explanation: Why this rule matters
  • Incorrect example: Anti-pattern with explanation
  • Correct example: Best practice with explanation
  • Additional context: Trade-offs, when to apply, references

Full Compiled Document

For the complete guide with all rules expanded inline: AGENTS.md

Use AGENTS.md when you need to check multiple rules quickly without reading individual files.

clickhouse-best-practices — AI Skill | PluginBench