clickhouse-best-practices: Research & Knowledge for AI Agents | OpenAgentSkill

Overview

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.

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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:

Check for applicable rules in the rules/ directory
If rules exist: Apply them and cite them in your response using "Per rule-name..."
If no rule exists: Use the LLM's ClickHouse knowledge or search documentation
If uncertain: Use web search for current best practices
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:

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

Every agent session should follow this sequence:

Connect — establish connection via MCP or CLI (see agent-connect-mcp)
Discover — databases → tables → columns + comments → sort keys → skip indexes → sample → EXPLAIN
Plan — use sort key and skip index knowledge to write efficient WHERE clauses
Execute — run queries with LIMIT and timeouts
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:

rules/schema-pk-plan-before-creation.md - ORDER BY is immutable
rules/schema-pk-cardinality-order.md - Column ordering in keys
rules/schema-pk-prioritize-filters.md - Filter column inclusion
rules/schema-types-native-types.md - Proper type selection
rules/schema-types-minimize-bitwidth.md - Numeric type sizing
rules/schema-types-lowcardinality.md - LowCardinality usage
rules/schema-types-avoid-nullable.md - Nullable vs DEFAULT
rules/schema-partition-low-cardinality.md - Partition count limits
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:

rules/query-join-choose-algorithm.md - Algorithm selection
rules/query-join-filter-before.md - Pre-join filtering
rules/query-join-use-any.md - ANY vs regular JOIN
rules/query-index-skipping-indices.md - Secondary index usage
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:

rules/insert-batch-size.md - Batch sizing requirements
rules/insert-mutation-avoid-update.md - UPDATE alternatives
rules/insert-mutation-avoid-delete.md - DELETE alternatives
rules/insert-async-small-batches.md - Async insert usage
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

Priority	Category	Impact	Prefix	Rule Count
1	Primary Key Selection	CRITICAL	`schema-pk-`	4
2	Data Type Selection	CRITICAL	`schema-types-`	5
3	JOIN Optimization	CRITICAL	`query-join-`	5
4	Insert Batching	CRITICAL	`insert-batch-`	1
5	Mutation Avoidance	CRITICAL	`insert-mutation-`	2
6	Partitioning Strategy	HIGH	`schema-partition-`	4
7	Skipping Indices	HIGH	`query-index-`	1
8	Materialized Views	HIGH	`query-mv-`	2
9	Async Inserts	HIGH	`insert-async-`	2
10	OPTIMIZE Avoidance	HIGH	`insert-optimize-`	1
11	JSON Usage	MEDIUM	`schema-json-`	1
12	Agent Schema Discovery	CRITICAL	`agent-discovery-`	1
13	Agent Query Safety	CRITICAL	`agent-query-`	1
14	Agent Connectivity + Formats	HIGH	`agent-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.

View source ↗

File metadata

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"

View original text

---
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](https://clickhouse.com/docs/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

| Priority | Category | Impact | Prefix | Rule Count |
|----------|----------|--------|--------|------------|
| 1 | Primary Key Selection | CRITICAL | `schema-pk-` | 4 |
| 2 | Data Type Selection | CRITICAL | `schema-types-` | 5 |
| 3 | JOIN Optimization | CRITICAL | `query-join-` | 5 |
| 4 | Insert Batching | CRITICAL | `insert-batch-` | 1 |
| 5 | Mutation Avoidance | CRITICAL | `insert-mutation-` | 2 |
| 6 | Partitioning Strategy | HIGH | `schema-partition-` | 4 |
| 7 | Skipping Indices | HIGH | `query-index-` | 1 |
| 8 | Materialized Views | HIGH | `query-mv-` | 2 |
| 9 | Async Inserts | HIGH | `insert-async-` | 2 |
| 10 | OPTIMIZE Avoidance | HIGH | `insert-optimize-` | 1 |
| 11 | JSON Usage | MEDIUM | `schema-json-` | 1 |
| 12 | Agent Schema Discovery | CRITICAL | `agent-discovery-` | 1 |
| 13 | Agent Query Safety | CRITICAL | `agent-query-` | 1 |
| 14 | Agent Connectivity + Formats | HIGH | `agent-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.

Review the source

Skill source recorded

Skill instructions are recorded. This is not a runtime test, safety guarantee or compatibility certification.

Review before install: Avoid automatic install

License: Apache-2.0

Dependency or permission surface needs review
Permission surface may require sandboxing
No critical security concerns; skill is purely informational and does not execute commands or access secrets.
SKILL.md is comprehensive but may be lengthy; however, it is well-structured and actionable.
Quality score needs review
Permission surface needs review: secrets or environment access, shell or command execution
Dependency/runtime risk: command execution surface, credential or environment access
Permission surface: secrets or environment access, shell or command execution

Open full audit

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Start with one small task

1Read the source. Confirm the input, expected output, dependencies and permissions.
2Ask your agent for a plan. Approve setup and any costs before running a small isolated test.
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Source & usage notes

Indexed

Repository metadata and review signals are advisory. Popularity, source discovery and successful execution are different facts.

Source repository: ClickHouse/agent-skills
License: Apache-2.0
Version: 1.0.0
Last GitHub push: Aug 6, 2026
Registry updated: Sep 5, 2026
Instruction path: skills/clickhouse-best-practices/SKILL.md @ 5aec31143796

Version reported in registry metadata; check source releases before relying on it.

Quality

71/100

Strong

Trust

58/100

Agent access

This page exposes the same decision, trust, audit, use-case, and install signals through the Registry API, so agents can rank this skill without scraping the UI.

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More details

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      "repoActivity": "530 stars, 37 forks",
      "lastPushed": "1mo since push",
      "license": "Apache-2.0",
      "repository": "https://github.com/ClickHouse/agent-skills/tree/main/skills/clickhouse-best-practices",
      "install": "npx skills add ClickHouse/agent-skills --skill clickhouse-best-practices",
      "installSafety": "standard package or runtime install path",
      "permissionSurface": "secrets or environment access, shell or command execution",
      "documentation": "Strong README/SKILL.md context",
      "agentOutcomes": "No agent outcome data yet"
    },
    "outcome_evidence": {
      "total": 0,
      "successes": 0,
      "failures": 0,
      "not_relevant": 0,
      "success_rate": null,
      "recent_success_rate": null,
      "recent_failure_rate": null,
      "install_attempts": 0,
      "install_success_rate": null,
      "risk_blocked": 0,
      "setup_required": 0,
      "avg_output_quality": null,
      "production_outcomes": 0,
      "last_outcome_at": null,
      "label": "No agent outcome data yet"
    },
    "auto_install": {
      "allowed": false,
      "sandbox_required": true,
      "reason": "Do not auto-install. Inspect the source, dependencies, and permission surface first."
    },
    "best_for": [
      "research",
      "agent-skill"
    ],
    "known_risks": [
      "No critical security concerns; skill is purely informational and does not execute commands or access secrets.",
      "Quality score needs review",
      "Permission surface needs review: secrets or environment access, shell or command execution",
      "Dependency/runtime risk: command execution surface, credential or environment access",
      "Permission surface: secrets or environment access, shell or command execution"
    ]
  },
  "agent_proven": {
    "version": "agent-proven-v1",
    "score": 0,
    "tier": "unproven",
    "label": "Needs first agent run",
    "summary": "No agent outcome reports yet. Use Resolve, run one narrow sandbox task, then report the result.",
    "metrics": {
      "totalOutcomes": 0,
      "successfulOutcomes": 0,
      "failedOutcomes": 0,
      "installAttempts": 0,
      "installSuccessRate": null,
      "successRate": null,
      "recentSuccessRate": null,
      "recentFailureRate": null,
      "riskBlocked": 0,
      "setupRequired": 0,
      "notRelevant": 0,
      "avgOutputQuality": null,
      "avgTimeToUsefulMs": null,
      "productionOutcomes": 0,
      "humanReviewRequired": 0,
      "uniqueAgents": 0,
      "lastOutcomeAt": null
    },
    "signals": [],
    "penalties": [
      "No real agent outcome evidence yet"
    ]
  },
  "audit": {
    "score": 74,
    "risk_level": "needs_review",
    "risk_label": "Needs review",
    "warnings": [
      "Dependency or permission surface needs review",
      "Permission surface may require sandboxing",
      "No critical security concerns; skill is purely informational and does not execute commands or access secrets.",
      "SKILL.md is comprehensive but may be lengthy; however, it is well-structured and actionable.",
      "Quality score needs review",
      "Permission surface needs review: secrets or environment access, shell or command execution",
      "Dependency/runtime risk: command execution surface, credential or environment access",
      "Permission surface: secrets or environment access, shell or command execution"
    ]
  },
  "safety_gate": {
    "tier": "blocked",
    "label": "Blocked for auto-install",
    "auto_install_policy": "block",
    "auto_install_allowed": false,
    "human_review_required": true,
    "blocked": true,
    "recommended_action": "Do not auto-install. Inspect the source, dependencies, and permission surface first."
  },
  "quality": {
    "score": 71,
    "label": "Strong"
  },
  "supply": {
    "track": "Research and knowledge work",
    "scenario": "Research agents",
    "maintenance": "1mo since push",
    "risk": "Needs review"
  },
  "alternative_skills": [
    {
      "slug": "yanliudesign-mono-color-skill",
      "name": "mono-color",
      "url": "https://www.openagentskill.com/skills/yanliudesign-mono-color-skill",
      "stars": 1919,
      "install_command": "npx skills add yanliudesign/mono-color-skill --skill mono-color",
      "trust_score": 85,
      "audit_score": 93
    }
  ],
  "do_not_use_when": [
    "teams that need a vendor-supported SLA",
    "production agents without a repository review",
    "No critical security concerns; skill is purely informational and does not execute commands or access secrets.",
    "No OpenAgentSkill engagement data yet",
    "High-risk permission hints: Shell or command execution, Secrets or environment access",
    "Dependency or permission surface needs review",
    "Permission surface may require sandboxing",
    "SKILL.md is comprehensive but may be lengthy; however, it is well-structured and actionable."
  ],
  "agent_contract": {
    "task_input": "Use clickhouse-best-practices in an agent workflow",
    "recommended_action": "Do not auto-install. Inspect the source, dependencies, and permission surface first.",
    "install_policy": "block",
    "minimum_review_before_use": [
      "Trust: 66/100 Manual review",
      "Audit: 74/100 Needs review",
      "Safety: 30/100 Avoid automatic install",
      "Review repository, license, install command, and permission surface before production use."
    ],
    "expected_agent_output": {
      "selected_skill": "clickhouse-clickhouse-best-practices (clickhouse-best-practices)",
      "install_command": "npx skills add ClickHouse/agent-skills --skill clickhouse-best-practices",
      "risk_summary": "Needs review; Blocked for auto-install; Review before production",
      "verification_result": "Report the smallest successful task, files touched, warnings, and any missing setup."
    }
  },
  "outcome_feedback": {
    "endpoint": "https://www.openagentskill.com/api/agent/outcome",
    "method": "POST",
    "requires_resolve_event_id": true,
    "event_id_source": "Use install_receipt.outcome_feedback.event_id or feedback.event_id returned by /api/agent/resolve for the current task.",
    "expected_outcomes": [
      "success",
      "failed",
      "not_relevant",
      "blocked_by_risk",
      "setup_required"
    ],
    "payload_template": {
      "event_id": "<install_receipt.outcome_feedback.event_id or feedback.event_id from /api/agent/resolve>",
      "skill_slug": "clickhouse-clickhouse-best-practices",
      "task": "Use clickhouse-best-practices in an agent workflow",
      "agent": "codex",
      "outcome": "success",
      "install_used": true,
      "risk_blocked": false,
      "setup_required": false,
      "task_success": true,
      "output_quality": 4,
      "error_type": null,
      "human_review_required": false,
      "workspace": "sandbox",
      "time_to_useful_ms": 120000,
      "notes": "Report the smallest successful task, setup friction, files touched, and risk notes."
    }
  },
  "endpoints": {
    "web": "https://www.openagentskill.com/skills/clickhouse-clickhouse-best-practices",
    "api": "https://www.openagentskill.com/api/agent/skills/clickhouse-clickhouse-best-practices",
    "audit": "https://www.openagentskill.com/skills/clickhouse-clickhouse-best-practices/audit",
    "eval": "https://www.openagentskill.com/api/agent/evals?slug=clickhouse-clickhouse-best-practices&task=Use%20clickhouse-best-practices%20in%20an%20agent%20workflow&max_risk=medium",
    "resolve": "https://www.openagentskill.com/api/agent/resolve?task=Use%20clickhouse-best-practices%20in%20an%20agent%20workflow&agent=codex&max_risk=medium",
    "receipt": "https://www.openagentskill.com/api/agent/receipt?task=Use%20clickhouse-best-practices%20in%20an%20agent%20workflow&agent=codex&max_risk=medium&format=text",
    "install": "https://www.openagentskill.com/api/skills/clickhouse-clickhouse-best-practices/install",
    "manifest": "https://www.openagentskill.com/api/registry/manifest/clickhouse-clickhouse-best-practices"
  }
}

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Creator: ClickHouse
Source: ClickHouse/agent-skills
Indexed by: OpenAgentSkill community index

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Overview

ClickHouse Best Practices

IMPORTANT: How to Apply This Skill

Agent Connectivity & Query Workflow

Subagent architecture notes

Review Procedures

For Schema Reviews (CREATE TABLE, ALTER TABLE)

For Query Reviews (SELECT, JOIN, aggregations)

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

Output Format

Rule Categories by Priority

Quick Reference

Schema Design - Primary Key (CRITICAL)

Schema Design - Data Types (CRITICAL)

Schema Design - Partitioning (HIGH)

Schema Design - JSON (MEDIUM)

Query Optimization - JOINs (CRITICAL)

Query Optimization - Indices (HIGH)

Query Optimization - Materialized Views (HIGH)

Insert Strategy - Batching (CRITICAL)

Insert Strategy - Async (HIGH)

Insert Strategy - Mutations (CRITICAL)

Insert Strategy - Optimization (HIGH)

Agent Integration - Discovery (CRITICAL)

Agent Integration - Safety (CRITICAL)

Agent Integration - Connectivity + Formats (HIGH)

When to Apply

Rule File Structure

Full Compiled Document

Review the source

Start with one small task

Source & usage notes

Agent access

Related skills

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