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Agent Skill · 开发规范

clickhouse-best-practices(CLIckHouse 最佳实践)

clickhouse-best-practices 用于记录任务执行中的错误、用户纠正、经验和能力缺口,适合在 Codex、Claude、Cursor、Gemini CLI 中希望让 Agent 持续沉淀问题、修正和最佳实践时使用。可结合来源仓库、安装命令和原始 README 继续核验具体用法。安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。

clickhouse-best-practices 是开发规范类 Agent Skill,可用宿主为 Codex、Claude、Cursor、Gemini CLI,通过GitHub 仓库获取,权限为调用外部服务;许可证信息还不明确,第三方扫描有提醒项,按安装量在开发规范类的 1,265 个 Skill 里排第 52。

总安装 62,130周安装 2,630GitHub Stars 412下载 21,076核验 2026-05-01

安装说明

本站只整理中文说明,不托管安装包,也不代用户安装。
GitHub
许可证
unknown

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:clickhouse-best-practices(CLIckHouse 最佳实践)
来源仓库:https://github.com/clickhouse/agent-skills
仓库路径:skills/clickhouse-best-practices
安装命令:
npx skills add https://github.com/clickhouse/agent-skills --skill clickhouse-best-practices
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。该命令会通过 npx skills 从第三方来源获取 Skill;本站只展示命令,不托管安装包,也不自动执行。

skills.shnpx skills
npx skills add https://github.com/clickhouse/agent-skills --skill clickhouse-best-practices

这个 Skill 是做什么的

开发规范类 Skill 用来统一代码风格、目录结构和评审口径,产出多为检查清单或改写建议。

按架构设计、查询优化和数据摄取策略组织的 28 条 ClickHouse 最佳实践规则。

涵盖三个关键领域:主键和数据类型选择(不可变的设计决策)、JOIN 和查询优化以及避免突变的插入批处理 包括按影响优先级排列的 28 条规则,由于 ClickHouse 的列式存储和稀疏索引机制,模式设计和查询优化规则被标记为“关键” 为模式、查询和插入策略提供结构化审查程序,并提供正式代码审查的清单和规则引用 每个规则文件包含不正确/正确的示例和权衡上下文;完整编译指南可在 AGENTS.md 中找到 用于快速多规则参考

来源仓库内路径:skills/clickhouse-best-practices

上手步骤

4 步
  1. 1

    确认自己的宿主工具

    公开资料标注支持 Codex、Claude、Cursor、Gemini CLI;先确认自己用的是其中之一,再按对应工具的 Skills 目录放置。

  2. 2

    拿到安装命令

    可以直接复制的命令是 npx skills add https://github.com/clickhouse/agent-skills --skill clickhouse-bes…;命令里的占位符换成自己的路径或密钥再执行。

  3. 3

    安装后重启宿主

    命令执行完要完全退出宿主工具再打开,让新装的 Skill 被重新扫描到,否则列表里可能看不到。

  4. 4

    按最小权限试用

    它需要调用外部服务,先在测试目录或测试账号里跑,确认没问题再放到正式项目。

常见问题

6 条

clickhouse-best-practices 怎么安装?

在终端执行 npx skills add https://github.com/clickhouse/agent-skills --skill clickhouse-best-practice…。装完完全退出宿主工具再打开,让它重新扫描本地 Skill。

clickhouse-best-practices 支持哪些 AI 工具?

公开资料标注支持 Codex、Claude、Cursor、Gemini CLI。其他工具只要能读取本地 Skill 目录,一般也能手动放进去,但要自己确认触发方式是否一致。

clickhouse-best-practices 需要什么权限?

权限级别是调用外部服务。该 Skill 可能调用第三方服务、云服务或外部模型 API,使用前需要确认账号、额度、数据发送范围和服务条款。

clickhouse-best-practices 是免费的吗?

公开资料没有标注明确许可证,收费和商用限制都无法确认。正式使用前请到来源仓库核对授权说明。

clickhouse-best-practices 用的人多吗?

公开数据是累计安装 62,130 次,近一周安装 2,630 次,下载 21,076 次,GitHub 412 星。这些数字来自第三方目录统计,只能当作热度参考,不代表质量或安全性。

clickhouse-best-practices 安全吗?

第三方扫描有提醒项,说明存在需要人工确认的行为。安装前请打开源码看清它读了什么、联网到哪里。

值得选的地方和要先想清楚的地方

值得选的地方

  • 同时适配 4 种工具,换客户端不用重新找替代品。

先想清楚的地方

  • 许可证没有明确标注,能不能商用、能不能再分发都不确定。
  • 第三方扫描存在提醒项或未通过项,需要人工逐条确认。
  • 第三方目录整理,版本更新和行为细节以来源仓库为准。

适不适合你

更适合

  • 已经在用 Codex,想直接扩展它能力的人。
  • 需要处理开发规范类任务、又不想每次都手写提示词的人。

不太适合

  • 需要明确授权才能用到公司项目里的场景。
  • 需要厂商级技术支持和 SLA 的生产系统。

开发规范类 Skill 对比

6 个同类
Skill总安装GitHub 星权限许可证扫描
vercel-react-best-practices

Vercel React 最佳实践 · Codex、Claude

8,490,72025,918操作浏览器MIT通过
web-design-guidelines

网页设计指南 · Codex、Claude

6,686,01625,885需要联网MIT有提醒
remotion-best-practices

Remotion 最佳实践 · Codex、Claude

6,505,6323,027操作浏览器MIT有提醒
supabase-postgres-best-practices

Supabase Postgres 最佳实践 · Codex、Claude

3,175,5232,030需要联网MIT通过
next-best-practices

Next.js 最佳实践 · Codex、Claude

1,848,240841操作浏览器MIT通过
clickhouse-best-practices

CLIckHouse 最佳实践 · 本页

62,130412调用外部服务未明确有提醒

按安装量取同分类前几名;数字来自第三方目录统计,只作热度参考,不代表质量结论。

SKILL.md 原文

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.

平台分布

Codex

36.61%
按下载量换算7,716

Claude

27.98%
按下载量换算5,897

Cursor

18%
按下载量换算3,794

Gemini CLI

8.56%
按下载量换算1,804

安全审计

Gen Agent Trust Hub

通过

Socket

通过

Snyk

可疑

权限和风险

调用外部服务

该 Skill 可能调用第三方服务、云服务或外部模型 API,使用前需要确认账号、额度、数据发送范围和服务条款。

安装前确认

本站仅展示第三方公开信息,不托管安装包,不提供自动安装或运行环境。安装前应自行审查源码、依赖和命令行为。来源安全扫描存在提醒或未通过项,安装前请自行复核。目前只有一个公开来源,建议同时核对源仓库。

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